MongoDB Documentation


MongoDB Documentation Release 3.0.7 MongoDB, Inc. October 24, 2015 2 © MongoDB, Inc. 2008 - 2015 This work is licensed under a Creative Commons Attribution-NonCommercial- ShareAlike 3.0 United States License 3 Contents 1 Introduction to MongoDB 3 1.1 What is MongoDB............................................3 2 Install MongoDB 5 2.1 Recommended Operating Systems for Production Deployments....................5 2.2 Other Supported Operating Systems...................................5 2.3 Installation Guides............................................5 2.4 First Steps with MongoDB........................................ 58 2.5 Additional Resources........................................... 58 3 MongoDB CRUD Operations 59 3.1 MongoDB CRUD Introduction..................................... 59 3.2 MongoDB CRUD Concepts....................................... 62 3.3 MongoDB CRUD Tutorials....................................... 94 3.4 MongoDB CRUD Reference....................................... 132 4 Data Models 147 4.1 Data Modeling Introduction....................................... 147 4.2 Data Modeling Concepts......................................... 149 4.3 Data Model Examples and Patterns................................... 155 4.4 Data Model Reference.......................................... 172 5 Administration 187 5.1 Administration Concepts......................................... 187 5.2 Administration Tutorials......................................... 224 5.3 Administration Reference........................................ 292 5.4 Production Checklist........................................... 317 6 Security 323 6.1 Security Introduction........................................... 323 6.2 Security Concepts............................................ 325 6.3 Security Tutorials............................................. 339 6.4 Security Reference............................................ 405 6.5 Security Checklist............................................ 432 7 Aggregation 435 7.1 Aggregation Introduction........................................ 435 7.2 Aggregation Concepts.......................................... 439 7.3 Aggregation Examples.......................................... 452 i 7.4 Aggregation Reference.......................................... 469 7.5 Additional Resources........................................... 479 8 Indexes 481 8.1 Index Introduction............................................ 481 8.2 Index Concepts.............................................. 485 8.3 Indexing Tutorials............................................ 517 8.4 Indexing Reference............................................ 552 9 Replication 559 9.1 Replication Introduction......................................... 559 9.2 Replication Concepts........................................... 563 9.3 Replica Set Tutorials........................................... 602 9.4 Replication Reference.......................................... 651 10 Sharding 661 10.1 Sharding Introduction.......................................... 661 10.2 Sharding Concepts............................................ 667 10.3 Sharded Cluster Tutorials........................................ 690 10.4 Sharding Reference........................................... 736 11 Frequently Asked Questions 743 11.1 FAQ: MongoDB Fundamentals..................................... 743 11.2 FAQ: MongoDB for Application Developers.............................. 746 11.3 FAQ: The mongo Shell......................................... 756 11.4 FAQ: Concurrency............................................ 758 11.5 FAQ: Sharding with MongoDB..................................... 763 11.6 FAQ: Replication and Replica Sets................................... 768 11.7 FAQ: MongoDB Storage......................................... 772 11.8 FAQ: Indexes............................................... 777 11.9 FAQ: MongoDB Diagnostics....................................... 779 12 Release Notes 785 12.1 Current Stable Release.......................................... 785 12.2 Previous Stable Releases......................................... 837 12.3 Other MongoDB Release Notes..................................... 936 12.4 MongoDB Version Numbers....................................... 936 13 About MongoDB Documentation 939 13.1 License.................................................. 939 13.2 Editions.................................................. 939 13.3 Version and Revisions.......................................... 940 13.4 Report an Issue or Make a Change Request............................... 940 13.5 Contribute to the Documentation.................................... 940 ii MongoDB Documentation, Release 3.0.7 Note: This version of the PDF does not include the reference section, see MongoDB Reference Manual1 for a PDF edition of all MongoDB Reference Material. 1http://docs.mongodb.org/master/MongoDB-reference-manual.pdf Contents 1 MongoDB Documentation, Release 3.0.7 2 Contents CHAPTER 1 Introduction to MongoDB Welcome to MongoDB. This document provides a brief introduction to MongoDB and some key concepts. See the installation guides (page 5) for information on downloading and installing MongoDB. 1.1 What is MongoDB MongoDB is an open-source document database that provides high performance, high availability, and automatic scaling. 1.1.1 Document Database A record in MongoDB is a document, which is a data structure composed of field and value pairs. MongoDB docu- ments are similar to JSON objects. The values of fields may include other documents, arrays, and arrays of documents. The advantages of using documents are: • Documents (i.e. objects) correspond to native data types in many programming languages. • Embedded documents and arrays reduce need for expensive joins. • Dynamic schema supports fluent polymorphism. 3 MongoDB Documentation, Release 3.0.7 1.1.2 Key Features High Performance MongoDB provides high performance data persistence. In particular, • Support for embedded data models reduces I/O activity on database system. • Indexes support faster queries and can include keys from embedded documents and arrays. High Availability To provide high availability, MongoDB’s replication facility, called replica sets, provide: • automatic failover. • data redundancy. A replica set (page 559) is a group of MongoDB servers that maintain the same data set, providing redundancy and increasing data availability. Automatic Scaling MongoDB provides horizontal scalability as part of its core functionality. • Automatic sharding (page 661) distributes data across a cluster of machines. • Replica sets can provide eventually-consistent reads for low-latency high throughput deployments. 4 Chapter 1. Introduction to MongoDB CHAPTER 2 Install MongoDB MongoDB runs on most platforms and supports 64-bit architecture for production use and both 64-bit and 32-bit architectures for testing. 2.1 Recommended Operating Systems for Production Deployments MongoDB MongoDB Enterprise Amazon Linux supported supported Debian 7.1 supported supported RedHat / CentOS 6.2+ supported supported SUSE 11 supported supported Ubuntu LTS 12.04 supported supported Ubuntu LTS 14.04 supported supported Windows Server 2012 & 2012 R2 supported supported 2.2 Other Supported Operating Systems MongoDB MongoDB Enterprise Mac OSX 10.6+ supported RedHat / CentOS 5.5+ supported RedHat / CentOS 5.7+ supported supported RedHat / CentOS 7.0+ supported supported SmartOS supported Solaris 11 / SunOS 5.11 on x86 supported Windows Server 2008 R2 supported supported 2.3 Installation Guides See the Release Notes (page 785) for information about specific releases of MongoDB. Install on Linux (page 6) Documentations for installing the official MongoDB distribution on Linux-based systems. Install on Red Hat (page 7) Install MongoDB on Red Hat Enterprise and related Linux systems using .rpm packages. Install on Amazon Linux (page 14) Install MongoDB on Amazon Linux systems using .rpm packages. 5 MongoDB Documentation, Release 3.0.7 Install on SUSE (page 11) Install MongoDB on SUSE Linux systems using .rpm packages. Install on Ubuntu (page 17) Install MongoDB on Ubuntu Linux systems using .deb packages. Install on Debian (page 20) Install MongoDB on Debian systems using .deb packages. Install MongoDB From Tarball (page 23) Install the official build of MongoDB on other Linux systems from MongoDB archives. Install on OS X (page 25) Install the official build of MongoDB on OS X systems from Homebrew packages or from MongoDB archives. Install on Windows (page 28) Install MongoDB on Windows systems and optionally start MongoDB as a Windows service. Install MongoDB Enterprise (page 33) MongoDB Enterprise is available for MongoDB Enterprise subscribers and includes several additional features including support for SNMP monitoring, LDAP authentication, Kerberos authentication, and System Event Auditing. Install MongoDB Enterprise on Red Hat (page 34) Install the MongoDB Enterprise build and required depen- dencies on Red Hat Enterprise or CentOS Systems using packages. Install MongoDB Enterprise on Ubuntu (page 38) Install the MongoDB Enterprise build and required depen- dencies on Ubuntu Linux Systems using packages. Install MongoDB Enterprise on Amazon AMI (page 49) Install the MongoDB Enterprise build and required dependencies on Amazon Linux AMI. Install MongoDB Enterprise on Windows (page 52) Install the MongoDB Enterprise build and required de- pendencies using the .msi installer. 2.3.1 Install on Linux These documents provide instructions to install MongoDB for various Linux systems. Recommended For the best installation experience, MongoDB provides packages for popular Linux distributions. These packages, which support specific platforms and provide improved performance and TLS/SSL support, are the preferred way to run MongoDB. The following guides detail the installation process for these systems: Install on Red Hat (page 7) Install MongoDB on Red Hat Enterprise and related Linux systems using .rpm pack- ages. Install on SUSE (page 11) Install MongoDB on SUSE Linux systems using .rpm packages. Install on Amazon Linux (page 14) Install MongoDB on Amazon Linux systems using .rpm packages. Install on Ubuntu (page 17) Install MongoDB on Ubuntu Linux systems using .deb packages. Install on Debian (page 20) Install MongoDB on Debian systems using .deb packages. For systems without supported packages, refer to the Manual Installation tutorial. Manual Installation For Linux systems without supported packages, MongoDB provides a generic Linux release. These versions of Mon- goDB don’t include TLS/SSL, and may not perform as well as the targeted packages, but are compatible on most contemporary Linux systems. See the following guides for installation: 6 Chapter 2. Install MongoDB MongoDB Documentation, Release 3.0.7 Install MongoDB From Tarball (page 23) Install the official build of MongoDB on other Linux systems from Mon- goDB archives. Install MongoDB on Red Hat Enterprise or CentOS Linux Overview Use this tutorial to install MongoDB on Red Hat Enterprise Linux or CentOS Linux versions 5, 6, and 7 using .rpm packages. While some of these distributions include their own MongoDB packages, the official MongoDB packages are generally more up to date. Platform Support This installation guide only supports 64-bit systems. See Platform Support (page 819) for details. Packages MongoDB provides officially supported packages in their own repository. This repository contains the following packages: • mongodb-org This package is a metapackage that will automatically install the four component packages listed below. • mongodb-org-server This package contains the mongod daemon and associated configuration and init scripts. • mongodb-org-mongos This package contains the mongos daemon. • mongodb-org-shell This package contains the mongo shell. • mongodb-org-tools This package contains the following MongoDB tools: mongoimport bsondump, mongodump, mongoexport, mongofiles, mongooplog, mongoperf, mongorestore, mongostat, and mongotop. Init Scripts The mongodb-org package includes various init scripts, including the init script /etc/rc.d/init.d/mongod. These scripts are used to stop, start, and restart daemon processes. The package configures MongoDB using the /etc/mongod.conf file in conjunction with the init scripts. See the Configuration File reference for documentation of settings available in the configuration file. As of version 3.0.7, there are no init scripts for mongos. The mongos process is used only in sharding (page 667). You can use the mongod init script to derive your own mongos init script for use in such environments. See the mongos reference for configuration details. Considerations This installation guide only supports 64-bit systems. See Platform Support (page 819) for details. The default /etc/mongod.conf configuration file supplied by the 3.0 series packages has bind_ip set to 127.0.0.1 by default. Modify this setting as needed for your environment before initializing a replica set. Changed in version 2.6: The package structure and names have changed as of version 2.6. For instructions on instal- lation of an older release, please refer to the documentation for the appropriate version. Install MongoDB 2.3. Installation Guides 7 MongoDB Documentation, Release 3.0.7 Step 1: Configure the package management system (yum). Create a /etc/yum.repos.d/mongodb-org-3.0.repo file so that you can install MongoDB directly, using yum. Changed in version 3.0: MongoDB Linux packages for 3.0 are in a new repository. For the latest stable release of MongoDB Use the following repository file: [mongodb-org-3.0] name=MongoDB Repository baseurl=https://repo.mongodb.org/yum/redhat/$releasever/mongodb-org/3.0/x86_64/ gpgcheck=0 enabled=1 For versions of MongoDB earlier than 3.0 To install the packages from an earlier release series (page 936), such as 2.4 or 2.6, you can specify the release series in the repository configuration. For example, to restrict your system to the 2.6 release series, create a /etc/yum.repos.d/mongodb-org-2.6.repo file to hold the following configuration information for the MongoDB 2.6 repository: [mongodb-org-2.6] name=MongoDB 2.6 Repository baseurl=http://downloads-distro.mongodb.org/repo/redhat/os/x86_64/ gpgcheck=0 enabled=1 .repo files for each release can also be found in the repository itself1. Remember that odd-numbered minor release versions (e.g. 2.5) are development versions and are unsuitable for production use. Step 2: Install the MongoDB packages and associated tools. When you install the packages, you choose whether to install the current release or a previous one. This step provides the commands for both. To install the latest stable version of MongoDB, issue the following command: sudo yum install -y mongodb-org To install a specific release of MongoDB, specify each component package individually and append the version number to the package name, as in the following example: sudo yum install -y mongodb-org-3.0.7 mongodb-org-server-3.0.7 mongodb-org-shell-3.0.7 mongodb-org-mongos-3.0.7 mongodb-org-tools-3.0.7 You can specify any available version of MongoDB. However yum will upgrade the packages when a newer version becomes available. To prevent unintended upgrades, pin the package. To pin a package, add the following exclude directive to your /etc/yum.conf file: exclude=mongodb-org,mongodb-org-server,mongodb-org-shell,mongodb-org-mongos,mongodb-org-tools Versions of the MongoDB packages before 2.6 use a different repo location. Refer to the version of the documentation appropriate for your MongoDB version. Run MongoDB Prerequisites 1https://repo.mongodb.org/yum/redhat/ 8 Chapter 2. Install MongoDB MongoDB Documentation, Release 3.0.7 Configure SELinux Important: You must configure SELinux to allow MongoDB to start on Red Hat Linux-based systems (Red Hat Enterprise Linux or CentOS Linux). To configure SELinux, administrators have three options: Note: All three options require root privileges. The first two options each requires a system reboot and may have larger implications for your deployment. • Disable SELinux entirely by changing the SELINUX setting to disabled in /etc/selinux/config. SELINUX=disabled • Set SELinux to permissive mode in /etc/selinux/config by changing the SELINUX setting to permissive . SELINUX=permissive Note: You can use setenforce to change to permissive mode; this method does not require a reboot but is not persistent. • Enable access to the relevant ports (e.g. 27017) for SELinux if in enforcing mode. See Default MongoDB Port (page 425) for more information on MongoDB’s default ports. For default settings, this can be accom- plished by running semanage port -a -t mongod_port_t -p tcp 27017 Warning: On RHEL 7.0, if you change the data path, the default SELinux policies will prevent mongod from having write access on the new data path if you do not change the security context. You may alternatively choose not to install the SELinux packages when you are installing your Linux operating system, or choose to remove the relevant packages. This option is the most invasive and is not recommended. Data Directories and Permissions Warning: On RHEL 7.0, if you change the data path, the default SELinux policies will prevent mongod from having write access on the new data path if you do not change the security context. The MongoDB instance stores its data files in /var/lib/mongo and its log files in /var/log/mongodb by default, and runs using the mongod user account. You can specify alternate log and data file directories in /etc/mongod.conf. See systemLog.path and storage.dbPath for additional information. If you change the user that runs the MongoDB process, you must modify the access control rights to the /var/lib/mongo and /var/log/mongodb directories to give this user access to these directories. Procedure Step 1: Start MongoDB. You can start the mongod process by issuing the following command: sudo service mongod start Step 2: Verify that MongoDB has started successfully You can verify that the mongod process has started suc- cessfully by checking the contents of the log file at /var/log/mongodb/mongod.log for a line reading 2.3. Installation Guides 9 MongoDB Documentation, Release 3.0.7 [initandlisten] waiting for connections on port where is the port configured in /etc/mongod.conf, 27017 by default. You can optionally ensure that MongoDB will start following a system reboot by issuing the following command: sudo chkconfig mongod on Step 3: Stop MongoDB. As needed, you can stop the mongod process by issuing the following command: sudo service mongod stop Step 4: Restart MongoDB. You can restart the mongod process by issuing the following command: sudo service mongod restart You can follow the state of the process for errors or important messages by watching the output in the /var/log/mongodb/mongod.log file. Step 5: Begin using MongoDB. To help you start using MongoDB, MongoDB provides Getting Started Guides in various driver editions. See getting-started for the available editions. Before deploying MongoDB in a production environment, consider the Production Notes (page 201) document. Later, to stop MongoDB, press Control+C in the terminal where the mongod instance is running. Uninstall MongoDB To completely remove MongoDB from a system, you must remove the MongoDB applications themselves, the configuration files, and any directories containing data and logs. The following section guides you through the necessary steps. Warning: This process will completely remove MongoDB, its configuration, and all databases. This process is not reversible, so ensure that all of your configuration and data is backed up before proceeding. Step 1: Stop MongoDB. Stop the mongod process by issuing the following command: sudo service mongod stop Step 2: Remove Packages. Remove any MongoDB packages that you had previously installed. sudo yum erase $(rpm -qa | grep mongodb-org) Step 3: Remove Data Directories. Remove MongoDB databases and log files. sudo rm -r /var/log/mongodb sudo rm -r /var/lib/mongo 10 Chapter 2. Install MongoDB MongoDB Documentation, Release 3.0.7 Install MongoDB on SUSE Overview Use this tutorial to install MongoDB on SUSE Linux from .rpm packages. While SUSE distributions include their own MongoDB packages, the official MongoDB packages are generally more up to date. Platform Support This installation guide only supports 64-bit systems. See Platform Support (page 819) for details. Packages MongoDB provides officially supported packages in their own repository. This repository contains the following packages: • mongodb-org This package is a metapackage that will automatically install the four component packages listed below. • mongodb-org-server This package contains the mongod daemon and associated configuration and init scripts. • mongodb-org-mongos This package contains the mongos daemon. • mongodb-org-shell This package contains the mongo shell. • mongodb-org-tools This package contains the following MongoDB tools: mongoimport bsondump, mongodump, mongoexport, mongofiles, mongooplog, mongoperf, mongorestore, mongostat, and mongotop. Init Scripts The mongodb-org package includes various init scripts, including the init script /etc/rc.d/init.d/mongod. These scripts are used to stop, start, and restart daemon processes. The package configures MongoDB using the /etc/mongod.conf file in conjunction with the init scripts. See the Configuration File reference for documentation of settings available in the configuration file. As of version 3.0.7, there are no init scripts for mongos. The mongos process is used only in sharding (page 667). You can use the mongod init script to derive your own mongos init script for use in such environments. See the mongos reference for configuration details. Considerations This installation guide only supports 64-bit systems. See Platform Support (page 819) for details. The default /etc/mongod.conf configuration file supplied by the 3.0 series packages has bind_ip set to 127.0.0.1 by default. Modify this setting as needed for your environment before initializing a replica set. Changed in version 2.6: The package structure and names have changed as of version 2.6. For instructions on instal- lation of an older release, please refer to the documentation for the appropriate version. Note: SUSE Linux Enterprise Server 11 and potentially other versions of SLES and other SUSE distributions ship with virtual memory address space limited to 8GB by default. This must be adjusted in order to prevent virtual memory allocation failures as the database grows. The SLES packages for MongoDB adjust these limits in the default scripts, but you will need to make this change manually if you are using custom scripts and/or the tarball release rather than the SLES packages. 2.3. Installation Guides 11 MongoDB Documentation, Release 3.0.7 Install MongoDB Step 1: Configure the package management system (zypper). Add the repository so that you can install Mon- goDB using zypper. Changed in version 3.0: MongoDB Linux packages for 3.0 are in a new repository. For the latest stable release of MongoDB Use the following command: sudo zypper addrepo --no-gpgcheck https://repo.mongodb.org/zypper/suse/11/mongodb-org/3.0/x86_64/ mongodb For versions of MongoDB earlier than 3.0 To install MongoDB packages from a previous release series (page 936), such as 2.6, you can specify the release series in the repository configuration. For example, to restrict your system to the 2.6 release series, use the following command: sudo zypper addrepo --no-gpgcheck http://downloads-distro.mongodb.org/repo/suse/os/x86_64/ mongodb Step 2: Install the MongoDB packages and associated tools. When you install the packages, you choose whether to install the current release or a previous one. This step provides the commands for both. To install the latest stable version of MongoDB, issue the following command: sudo zypper -n install mongodb-org To install a specific release of MongoDB, specify each component package individually and append the version number to the package name, as in the following example: sudo zypper install mongodb-org-3.0.7 mongodb-org-server-3.0.7 mongodb-org-shell-3.0.7 mongodb-org-mongos-3.0.7 mongodb-org-tools-3.0.7 You can specify any available version of MongoDB. However zypper will upgrade the packages when a newer version becomes available. To prevent unintended upgrades, pin the packages by running the following command: sudo zypper addlock mongodb-org-3.0.7 mongodb-org-server-3.0.7 mongodb-org-shell-3.0.7 mongodb-org-mongos-3.0.7 mongodb-org-tools-3.0.7 Previous versions of MongoDB packages use a different repository location. Refer to the version of the documentation appropriate for your MongoDB version. Run MongoDB Prerequisites The MongoDB instance stores its data files in /var/lib/mongo and its log files in /var/log/mongodb by default, and runs using the mongod user account. You can specify alternate log and data file directories in /etc/mongod.conf. See systemLog.path and storage.dbPath for additional in- formation. If you change the user that runs the MongoDB process, you must modify the access control rights to the /var/lib/mongo and /var/log/mongodb directories to give this user access to these directories. Procedure Step 1: Start MongoDB. You can start the mongod process by issuing the following command: 12 Chapter 2. Install MongoDB MongoDB Documentation, Release 3.0.7 sudo service mongod start Step 2: Verify that MongoDB has started successfully You can verify that the mongod process has started suc- cessfully by checking the contents of the log file at /var/log/mongodb/mongod.log for a line reading [initandlisten] waiting for connections on port where is the port configured in /etc/mongod.conf, 27017 by default. You can optionally ensure that MongoDB will start following a system reboot by issuing the following command: sudo chkconfig mongod on Step 3: Stop MongoDB. As needed, you can stop the mongod process by issuing the following command: sudo service mongod stop Step 4: Restart MongoDB. You can restart the mongod process by issuing the following command: sudo service mongod restart You can follow the state of the process for errors or important messages by watching the output in the /var/log/mongodb/mongod.log file. Step 5: Begin using MongoDB. To help you start using MongoDB, MongoDB provides Getting Started Guides in various driver editions. See getting-started for the available editions. Before deploying MongoDB in a production environment, consider the Production Notes (page 201) document. Later, to stop MongoDB, press Control+C in the terminal where the mongod instance is running. Uninstall MongoDB To completely remove MongoDB from a system, you must remove the MongoDB applications themselves, the configuration files, and any directories containing data and logs. The following section guides you through the necessary steps. Warning: This process will completely remove MongoDB, its configuration, and all databases. This process is not reversible, so ensure that all of your configuration and data is backed up before proceeding. Step 1: Stop MongoDB. Stop the mongod process by issuing the following command: sudo service mongod stop Step 2: Remove Packages. Remove any MongoDB packages that you had previously installed. sudo zypper remove $(rpm -qa | grep mongodb-org) Step 3: Remove Data Directories. Remove MongoDB databases and log files. sudo rm -r /var/log/mongodb sudo rm -r /var/lib/mongo 2.3. Installation Guides 13 MongoDB Documentation, Release 3.0.7 Install MongoDB on Amazon Linux Overview Use this tutorial to install MongoDB on Amazon Linux from .rpm packages. This installation guide only supports 64-bit systems. See Platform Support (page 819) for details. Packages MongoDB provides officially supported packages in their own repository. This repository contains the following packages: • mongodb-org This package is a metapackage that will automatically install the four component packages listed below. • mongodb-org-server This package contains the mongod daemon and associated configuration and init scripts. • mongodb-org-mongos This package contains the mongos daemon. • mongodb-org-shell This package contains the mongo shell. • mongodb-org-tools This package contains the following MongoDB tools: mongoimport bsondump, mongodump, mongoexport, mongofiles, mongooplog, mongoperf, mongorestore, mongostat, and mongotop. Init Scripts The mongodb-org package includes various init scripts, including the init script /etc/rc.d/init.d/mongod. These scripts are used to stop, start, and restart daemon processes. The package configures MongoDB using the /etc/mongod.conf file in conjunction with the init scripts. See the Configuration File reference for documentation of settings available in the configuration file. As of version 3.0.7, there are no init scripts for mongos. The mongos process is used only in sharding (page 667). You can use the mongod init script to derive your own mongos init script for use in such environments. See the mongos reference for configuration details. Considerations This installation guide only supports 64-bit systems. See Platform Support (page 819) for details. The default /etc/mongod.conf configuration file supplied by the 3.0 series packages has bind_ip set to 127.0.0.1 by default. Modify this setting as needed for your environment before initializing a replica set. Changed in version 2.6: The package structure and names have changed as of version 2.6. For instructions on instal- lation of an older release, please refer to the documentation for the appropriate version. Install MongoDB Step 1: Configure the package management system (yum). Create a /etc/yum.repos.d/mongodb-org-3.0.repo file so that you can install MongoDB directly, using yum. Changed in version 3.0: MongoDB Linux packages for 3.0 are in a new repository. 14 Chapter 2. Install MongoDB MongoDB Documentation, Release 3.0.7 For the latest stable release of MongoDB Use the following repository file: [mongodb-org-3.0] name=MongoDB Repository baseurl=https://repo.mongodb.org/yum/amazon/2013.03/mongodb-org/3.0/x86_64/ gpgcheck=0 enabled=1 For versions of MongoDB earlier than 3.0 To install the packages from an earlier release series (page 936), such as 2.4 or 2.6, you can specify the release series in the repository configuration. For example, to restrict your system to the 2.6 release series, create a /etc/yum.repos.d/mongodb-org-2.6.repo file to hold the following configuration information for the MongoDB 2.6 repository: [mongodb-org-2.6] name=MongoDB 2.6 Repository baseurl=http://downloads-distro.mongodb.org/repo/redhat/os/x86_64/ gpgcheck=0 enabled=1 .repo files for each release can also be found in the repository itself2. Remember that odd-numbered minor release versions (e.g. 2.5) are development versions and are unsuitable for production use. Step 2: Install the MongoDB packages and associated tools. When you install the packages, you choose whether to install the current release or a previous one. This step provides the commands for both. To install the latest stable version of MongoDB, issue the following command: sudo yum install -y mongodb-org To install a specific release of MongoDB, specify each component package individually and append the version number to the package name, as in the following example: sudo yum install -y mongodb-org-3.0.7 mongodb-org-server-3.0.7 mongodb-org-shell-3.0.7 mongodb-org-mongos-3.0.7 mongodb-org-tools-3.0.7 You can specify any available version of MongoDB. However yum will upgrade the packages when a newer version becomes available. To prevent unintended upgrades, pin the package. To pin a package, add the following exclude directive to your /etc/yum.conf file: exclude=mongodb-org,mongodb-org-server,mongodb-org-shell,mongodb-org-mongos,mongodb-org-tools Versions of the MongoDB packages before 2.6 use a different repo location. Refer to the version of the documentation appropriate for your MongoDB version. Run MongoDB The MongoDB instance stores its data files in /var/lib/mongo and its log files in /var/log/mongodb by default, and runs using the mongod user account. You can specify alternate log and data file directories in /etc/mongod.conf. See systemLog.path and storage.dbPath for additional in- formation. If you change the user that runs the MongoDB process, you must modify the access control rights to the /var/lib/mongo and /var/log/mongodb directories to give this user access to these directories. Step 1: Start MongoDB. You can start the mongod process by issuing the following command: 2https://repo.mongodb.org/yum/redhat/ 2.3. Installation Guides 15 MongoDB Documentation, Release 3.0.7 sudo service mongod start Step 2: Verify that MongoDB has started successfully You can verify that the mongod process has started suc- cessfully by checking the contents of the log file at /var/log/mongodb/mongod.log for a line reading [initandlisten] waiting for connections on port where is the port configured in /etc/mongod.conf, 27017 by default. You can optionally ensure that MongoDB will start following a system reboot by issuing the following command: sudo chkconfig mongod on Step 3: Stop MongoDB. As needed, you can stop the mongod process by issuing the following command: sudo service mongod stop Step 4: Restart MongoDB. You can restart the mongod process by issuing the following command: sudo service mongod restart You can follow the state of the process for errors or important messages by watching the output in the /var/log/mongodb/mongod.log file. Step 5: Begin using MongoDB. To help you start using MongoDB, MongoDB provides Getting Started Guides in various driver editions. See getting-started for the available editions. Before deploying MongoDB in a production environment, consider the Production Notes (page 201) document. Later, to stop MongoDB, press Control+C in the terminal where the mongod instance is running. Uninstall MongoDB To completely remove MongoDB from a system, you must remove the MongoDB applications themselves, the configuration files, and any directories containing data and logs. The following section guides you through the necessary steps. Warning: This process will completely remove MongoDB, its configuration, and all databases. This process is not reversible, so ensure that all of your configuration and data is backed up before proceeding. Step 1: Stop MongoDB. Stop the mongod process by issuing the following command: sudo service mongod stop Step 2: Remove Packages. Remove any MongoDB packages that you had previously installed. sudo yum erase $(rpm -qa | grep mongodb-org) Step 3: Remove Data Directories. Remove MongoDB databases and log files. sudo rm -r /var/log/mongodb sudo rm -r /var/lib/mongo 16 Chapter 2. Install MongoDB MongoDB Documentation, Release 3.0.7 Install MongoDB on Ubuntu Overview Use this tutorial to install MongoDB on LTS Ubuntu Linux systems from .deb packages. While Ubuntu includes its own MongoDB packages, the official MongoDB packages are generally more up-to-date. Platform Support MongoDB only provides packages for 64-bit long-term support Ubuntu releases. Currently, this means 12.04 LTS (Precise Pangolin) and 14.04 LTS (Trusty Tahr). While the packages may work with other Ubuntu releases, this is not a supported configuration. Packages MongoDB provides officially supported packages in their own repository. This repository contains the following packages: • mongodb-org This package is a metapackage that will automatically install the four component packages listed below. • mongodb-org-server This package contains the mongod daemon and associated configuration and init scripts. • mongodb-org-mongos This package contains the mongos daemon. • mongodb-org-shell This package contains the mongo shell. • mongodb-org-tools This package contains the following MongoDB tools: mongoimport bsondump, mongodump, mongoexport, mongofiles, mongooplog, mongoperf, mongorestore, mongostat, and mongotop. Init Scripts The mongodb-org package includes various init scripts, including the init script /etc/init.d/mongod. These scripts are used to stop, start, and restart daemon processes. The package configures MongoDB using the /etc/mongod.conf file in conjunction with the init scripts. See the Configuration File reference for documentation of settings available in the configuration file. As of version 3.0.7, there are no init scripts for mongos. The mongos process is used only in sharding (page 667). You can use the mongod init script to derive your own mongos init script for use in such environments. See the mongos reference for configuration details. Considerations MongoDB only provides packages for 64-bit long-term support Ubuntu releases. Currently, this means 12.04 LTS (Precise Pangolin) and 14.04 LTS (Trusty Tahr). While the packages may work with other Ubuntu releases, this is not a supported configuration. You cannot install these packages concurrently with the mongodb, mongodb-server, or mongodb-clients packages provided by Ubuntu. The default /etc/mongod.conf configuration file supplied by the 3.0 series packages has bind_ip set to 127.0.0.1 by default. Modify this setting as needed for your environment before initializing a replica set. Changed in version 2.6: The package structure and names have changed as of version 2.6. For instructions on instal- lation of an older release, please refer to the documentation for the appropriate version. 2.3. Installation Guides 17 MongoDB Documentation, Release 3.0.7 Install MongoDB Step 1: Import the public key used by the package management system. The Ubuntu package management tools (i.e. dpkg and apt) ensure package consistency and authenticity by requiring that distributors sign packages with GPG keys. Issue the following command to import the MongoDB public GPG Key3: sudo apt-key adv --keyserver hkp://keyserver.ubuntu.com:80 --recv 7F0CEB10 Step 2: Create a list file for MongoDB. Create the /etc/apt/sources.list.d/mongodb-org-3.0.list list file using the command appropriate for your version of Ubuntu: Ubuntu 12.04 echo "deb http://repo.mongodb.org/apt/ubuntu precise/mongodb-org/3.0 multiverse" | sudo tee /etc/apt/sources.list.d/mongodb-org-3.0.list Ubuntu 14.04 echo "deb http://repo.mongodb.org/apt/ubuntu trusty/mongodb-org/3.0 multiverse" | sudo tee /etc/apt/sources.list.d/mongodb-org-3.0.list Step 3: Reload local package database. Issue the following command to reload the local package database: sudo apt-get update Step 4: Install the MongoDB packages. You can install either the latest stable version of MongoDB or a specific version of MongoDB. Install the latest stable version of MongoDB. Issue the following command: sudo apt-get install -y mongodb-org Install a specific release of MongoDB. To install a specific release, you must specify each component package individually along with the version number, as in the following example: sudo apt-get install -y mongodb-org=3.0.7 mongodb-org-server=3.0.7 mongodb-org-shell=3.0.7 mongodb-org-mongos=3.0.7 mongodb-org-tools=3.0.7 If you only install mongodb-org=3.0.7 and do not include the component packages, the latest version of each MongoDB package will be installed regardless of what version you specified. Pin a specific version of MongoDB. Although you can specify any available version of MongoDB, apt-get will upgrade the packages when a newer version becomes available. To prevent unintended upgrades, pin the package. To pin the version of MongoDB at the currently installed version, issue the following command sequence: echo "mongodb-org hold" | sudo dpkg --set-selections echo "mongodb-org-server hold" | sudo dpkg --set-selections echo "mongodb-org-shell hold" | sudo dpkg --set-selections echo "mongodb-org-mongos hold" | sudo dpkg --set-selections echo "mongodb-org-tools hold" | sudo dpkg --set-selections Versions of the MongoDB packages before 2.6 use a different repository location. Refer to the version of the docu- mentation appropriate for your MongoDB version. 3https://docs.mongodb.org/10gen-gpg-key.asc 18 Chapter 2. Install MongoDB MongoDB Documentation, Release 3.0.7 Run MongoDB The MongoDB instance stores its data files in /var/lib/mongodb and its log files in /var/log/mongodb by default, and runs using the mongodb user account. You can specify alternate log and data file directories in /etc/mongod.conf. See systemLog.path and storage.dbPath for additional in- formation. If you change the user that runs the MongoDB process, you must modify the access control rights to the /var/lib/mongodb and /var/log/mongodb directories to give this user access to these directories. Step 1: Start MongoDB. Issue the following command to start mongod: sudo service mongod start Step 2: Verify that MongoDB has started successfully Verify that the mongod process has started successfully by checking the contents of the log file at /var/log/mongodb/mongod.log for a line reading [initandlisten] waiting for connections on port where is the port configured in /etc/mongod.conf, 27017 by default. Step 3: Stop MongoDB. As needed, you can stop the mongod process by issuing the following command: sudo service mongod stop Step 4: Restart MongoDB. Issue the following command to restart mongod: sudo service mongod restart Step 5: Begin using MongoDB. To help you start using MongoDB, MongoDB provides Getting Started Guides in various driver editions. See getting-started for the available editions. Before deploying MongoDB in a production environment, consider the Production Notes (page 201) document. Later, to stop MongoDB, press Control+C in the terminal where the mongod instance is running. Uninstall MongoDB To completely remove MongoDB from a system, you must remove the MongoDB applications themselves, the configuration files, and any directories containing data and logs. The following section guides you through the necessary steps. Warning: This process will completely remove MongoDB, its configuration, and all databases. This process is not reversible, so ensure that all of your configuration and data is backed up before proceeding. Step 1: Stop MongoDB. Stop the mongod process by issuing the following command: sudo service mongod stop Step 2: Remove Packages. Remove any MongoDB packages that you had previously installed. sudo apt-get purge mongodb-org* 2.3. Installation Guides 19 MongoDB Documentation, Release 3.0.7 Step 3: Remove Data Directories. Remove MongoDB databases and log files. sudo rm -r /var/log/mongodb sudo rm -r /var/lib/mongodb Install MongoDB on Debian Overview Use this tutorial to install MongoDB from .deb packages on Debian 7 “Wheezy”. While Debian includes its own MongoDB packages, the official MongoDB packages are more up to date. MongoDB only provides packages for 64-bit Debian “Wheezy”. These packages may work with other Debian releases, but this is not a supported configuration. Packages MongoDB provides officially supported packages in their own repository. This repository contains the following packages: • mongodb-org This package is a metapackage that will automatically install the four component packages listed below. • mongodb-org-server This package contains the mongod daemon and associated configuration and init scripts. • mongodb-org-mongos This package contains the mongos daemon. • mongodb-org-shell This package contains the mongo shell. • mongodb-org-tools This package contains the following MongoDB tools: mongoimport bsondump, mongodump, mongoexport, mongofiles, mongooplog, mongoperf, mongorestore, mongostat, and mongotop. Init Scripts The mongodb-org package includes various init scripts, including the init script /etc/init.d/mongod. These scripts are used to stop, start, and restart daemon processes. The package configures MongoDB using the /etc/mongod.conf file in conjunction with the init scripts. See the Configuration File reference for documentation of settings available in the configuration file. As of version 3.0.7, there are no init scripts for mongos. The mongos process is used only in sharding (page 667). You can use the mongod init script to derive your own mongos init script for use in such environments. See the mongos reference for configuration details. Considerations This installation guide only supports 64-bit systems. See Platform Support (page 819) for details. You cannot install this package concurrently with the mongodb, mongodb-server, or mongodb-clients pack- ages that your release of Debian may include. The default /etc/mongod.conf configuration file supplied by the 3.0 series packages has bind_ip set to 127.0.0.1 by default. Modify this setting as needed for your environment before initializing a replica set. Changed in version 2.6: The package structure and names have changed as of version 2.6. For instructions on instal- lation of an older release, please refer to the documentation for the appropriate version. 20 Chapter 2. Install MongoDB MongoDB Documentation, Release 3.0.7 Install MongoDB The Debian package management tools (i.e. dpkg and apt) ensure package consistency and authenticity by requiring that distributors sign packages with GPG keys. Step 1: Import the public key used by the package management system. Issue the following command to add the MongoDB public GPG Key4 to the system key ring. sudo apt-key adv --keyserver keyserver.ubuntu.com --recv 7F0CEB10 Step 2: Create a /etc/apt/sources.list.d/mongodb-org-3.0.list file for MongoDB. Create the list file using the following command: echo "deb http://repo.mongodb.org/apt/debian wheezy/mongodb-org/3.0 main" | sudo tee /etc/apt/sources.list.d/mongodb-org-3.0.list Currently packages are only available for Debian 7 (Wheezy). Step 3: Reload local package database. Issue the following command to reload the local package database: sudo apt-get update Step 4: Install the MongoDB packages. You can install either the latest stable version of MongoDB or a specific version of MongoDB. Install the latest stable version of MongoDB. Issue the following command: sudo apt-get install -y mongodb-org Install a specific release of MongoDB. To install a specific release, you must specify each component package individually along with the version number, as in the following example: sudo apt-get install -y mongodb-org=3.0.7 mongodb-org-server=3.0.7 mongodb-org-shell=3.0.7 mongodb-org-mongos=3.0.7 mongodb-org-tools=3.0.7 If you only install mongodb-org=3.0.7 and do not include the component packages, the latest version of each MongoDB package will be installed regardless of what version you specified. Pin a specific version of MongoDB. Although you can specify any available version of MongoDB, apt-get will upgrade the packages when a newer version becomes available. To prevent unintended upgrades, pin the package. To pin the version of MongoDB at the currently installed version, issue the following command sequence: echo "mongodb-org hold" | sudo dpkg --set-selections echo "mongodb-org-server hold" | sudo dpkg --set-selections echo "mongodb-org-shell hold" | sudo dpkg --set-selections echo "mongodb-org-mongos hold" | sudo dpkg --set-selections echo "mongodb-org-tools hold" | sudo dpkg --set-selections Versions of the MongoDB packages before 2.6 use a different repository location. Refer to the version of the docu- mentation appropriate for your MongoDB version. 4https://docs.mongodb.org/10gen-gpg-key.asc 2.3. Installation Guides 21 MongoDB Documentation, Release 3.0.7 Run MongoDB The MongoDB instance stores its data files in /var/lib/mongodb and its log files in /var/log/mongodb by default, and runs using the mongodb user account. You can specify alternate log and data file directories in /etc/mongod.conf. See systemLog.path and storage.dbPath for additional in- formation. If you change the user that runs the MongoDB process, you must modify the access control rights to the /var/lib/mongodb and /var/log/mongodb directories to give this user access to these directories. Step 1: Start MongoDB. Issue the following command to start mongod: sudo service mongod start Step 2: Verify that MongoDB has started successfully Verify that the mongod process has started successfully by checking the contents of the log file at /var/log/mongodb/mongod.log for a line reading [initandlisten] waiting for connections on port where is the port configured in /etc/mongod.conf, 27017 by default. Step 3: Stop MongoDB. As needed, you can stop the mongod process by issuing the following command: sudo service mongod stop Step 4: Restart MongoDB. Issue the following command to restart mongod: sudo service mongod restart Step 5: Begin using MongoDB. To help you start using MongoDB, MongoDB provides Getting Started Guides in various driver editions. See getting-started for the available editions. Before deploying MongoDB in a production environment, consider the Production Notes (page 201) document. Later, to stop MongoDB, press Control+C in the terminal where the mongod instance is running. Uninstall MongoDB To completely remove MongoDB from a system, you must remove the MongoDB applications themselves, the configuration files, and any directories containing data and logs. The following section guides you through the necessary steps. Warning: This process will completely remove MongoDB, its configuration, and all databases. This process is not reversible, so ensure that all of your configuration and data is backed up before proceeding. Step 1: Stop MongoDB. Stop the mongod process by issuing the following command: sudo service mongod stop Step 2: Remove Packages. Remove any MongoDB packages that you had previously installed. sudo apt-get purge mongodb-org* 22 Chapter 2. Install MongoDB MongoDB Documentation, Release 3.0.7 Step 3: Remove Data Directories. Remove MongoDB databases and log files. sudo rm -r /var/log/mongodb sudo rm -r /var/lib/mongodb Install MongoDB From Tarball Overview Compiled versions of MongoDB for Linux provide a simple option for installing MongoDB for other Linux systems without supported packages. Considerations For production deployments, always run MongoDB on 64-bit systems. Install MongoDB MongoDB provides archives for both 64-bit and 32-bit Linux. Follow the installation procedure appropriate for your system. Install for 64-bit Linux Step 1: Download the binary files for the desired release of MongoDB. Download the binaries from https://www.mongodb.org/downloads. For example, to download the latest release through the shell, issue the following: curl -O https://fastdl.mongodb.org/linux/mongodb-linux-x86_64-3.0.7.tgz Step 2: Extract the files from the downloaded archive. For example, from a system shell, you can extract through the tar command: tar -zxvf mongodb-linux-x86_64-3.0.7.tgz Step 3: Copy the extracted archive to the target directory. Copy the extracted folder to the location from which MongoDB will run. mkdir -p mongodb cp -R -n mongodb-linux-x86_64-3.0.7/ mongodb Step 4: Ensure the location of the binaries is in the PATH variable. The MongoDB binaries are in the bin/ directory of the archive. To ensure that the binaries are in your PATH, you can modify your PATH. For example, you can add the following line to your shell’s rc file (e.g. ~/.bashrc): export PATH=/bin:$PATH Replace with the path to the extracted MongoDB archive. Install for 32-bit Linux 2.3. Installation Guides 23 MongoDB Documentation, Release 3.0.7 Step 1: Download the binary files for the desired release of MongoDB. Download the binaries from https://www.mongodb.org/downloads. For example, to download the latest release through the shell, issue the following: curl -O https://fastdl.mongodb.org/linux/mongodb-linux-i686-3.0.7.tgz Step 2: Extract the files from the downloaded archive. For example, from a system shell, you can extract through the tar command: tar -zxvf mongodb-linux-i686-3.0.7.tgz Step 3: Copy the extracted archive to the target directory. Copy the extracted folder to the location from which MongoDB will run. mkdir -p mongodb cp -R -n mongodb-linux-i686-3.0.7/ mongodb Step 4: Ensure the location of the binaries is in the PATH variable. The MongoDB binaries are in the bin/ directory of the archive. To ensure that the binaries are in your PATH, you can modify your PATH. For example, you can add the following line to your shell’s rc file (e.g. ~/.bashrc): export PATH=/bin:$PATH Replace with the path to the extracted MongoDB archive. Run MongoDB Step 1: Create the data directory. Before you start MongoDB for the first time, create the directory to which the mongod process will write data. By default, the mongod process uses the /data/db directory. If you create a directory other than this one, you must specify that directory in the dbpath option when starting the mongod process later in this procedure. The following example command creates the default /data/db directory: mkdir -p /data/db Step 2: Set permissions for the data directory. Before running mongod for the first time, ensure that the user account running mongod has read and write permissions for the directory. Step 3: Run MongoDB. To run MongoDB, run the mongod process at the system prompt. If necessary, specify the path of the mongod or the data directory. See the following examples. Run without specifying paths If your system PATH variable includes the location of the mongod binary and if you use the default data directory (i.e., /data/db), simply enter mongod at the system prompt: mongod 24 Chapter 2. Install MongoDB MongoDB Documentation, Release 3.0.7 Specify the path of the mongod If your PATH does not include the location of the mongod binary, enter the full path to the mongod binary at the system prompt: /mongod Specify the path of the data directory If you do not use the default data directory (i.e., /data/db), specify the path to the data directory using the --dbpath option: mongod --dbpath Step 4: Begin using MongoDB. To help you start using MongoDB, MongoDB provides Getting Started Guides in various driver editions. See getting-started for the available editions. Before deploying MongoDB in a production environment, consider the Production Notes (page 201) document. Later, to stop MongoDB, press Control+C in the terminal where the mongod instance is running. 2.3.2 Install MongoDB on OS X Overview Use this tutorial to install MongoDB on OS X systems. Platform Support Starting in version 3.0, MongoDB only supports OS X versions 10.7 (Lion) on Intel x86-64 and later. MongoDB is available through the popular OS X package manager Homebrew5 or through the MongoDB Download site6. Install MongoDB You can install MongoDB with Homebrew7 or manually. This section describes both. Install MongoDB with Homebrew Homebrew8 installs binary packages based on published “formulae.” This section describes how to update brew to the latest packages and install MongoDB. Homebrew requires some initial setup and configuration, which is beyond the scope of this document. Step 1: Update Homebrew’s package database. In a system shell, issue the following command: brew update Step 2: Install MongoDB. You can install MongoDB via brew with several different options. Use one of the following operations: 5http://brew.sh/ 6http://www.mongodb.org/downloads 7http://brew.sh/ 8http://brew.sh/ 2.3. Installation Guides 25 MongoDB Documentation, Release 3.0.7 Install the MongoDB Binaries To install the MongoDB binaries, issue the following command in a system shell: brew install mongodb Build MongoDB from Source with TLS/SSL Support To build MongoDB from the source files and include TLS/SSL support, issue the following from a system shell: brew install mongodb --with-openssl Install the Latest Development Release of MongoDB To install the latest development release for use in testing and development, issue the following command in a system shell: brew install mongodb --devel Install MongoDB Manually Only install MongoDB using this procedure if you cannot use homebrew (page 25). Step 1: Download the binary files for the desired release of MongoDB. Download the binaries from https://www.mongodb.org/downloads. For example, to download the latest release through the shell, issue the following: curl -O https://fastdl.mongodb.org/osx/mongodb-osx-x86_64-3.0.7.tgz Step 2: Extract the files from the downloaded archive. For example, from a system shell, you can extract through the tar command: tar -zxvf mongodb-osx-x86_64-3.0.7.tgz Step 3: Copy the extracted archive to the target directory. Copy the extracted folder to the location from which MongoDB will run. mkdir -p mongodb cp -R -n mongodb-osx-x86_64-3.0.7/ mongodb Step 4: Ensure the location of the binaries is in the PATH variable. The MongoDB binaries are in the bin/ directory of the archive. To ensure that the binaries are in your PATH, you can modify your PATH. For example, you can add the following line to your shell’s rc file (e.g. ~/.bashrc): export PATH=/bin:$PATH Replace with the path to the extracted MongoDB archive. 26 Chapter 2. Install MongoDB MongoDB Documentation, Release 3.0.7 Run MongoDB Step 1: Create the data directory. Before you start MongoDB for the first time, create the directory to which the mongod process will write data. By default, the mongod process uses the /data/db directory. If you create a directory other than this one, you must specify that directory in the dbpath option when starting the mongod process later in this procedure. The following example command creates the default /data/db directory: mkdir -p /data/db Step 2: Set permissions for the data directory. Before running mongod for the first time, ensure that the user account running mongod has read and write permis- sions for the directory. Step 3: Run MongoDB. To run MongoDB, run the mongod process at the system prompt. If necessary, specify the path of the mongod or the data directory. See the following examples. Run without specifying paths If your system PATH variable includes the location of the mongod binary and if you use the default data directory (i.e., /data/db), simply enter mongod at the system prompt: mongod Specify the path of the mongod If your PATH does not include the location of the mongod binary, enter the full path to the mongod binary at the system prompt: /mongod Specify the path of the data directory If you do not use the default data directory (i.e., /data/db), specify the path to the data directory using the --dbpath option: mongod --dbpath Step 4: Begin using MongoDB. To help you start using MongoDB, MongoDB provides Getting Started Guides in various driver editions. See getting- started for the available editions. Before deploying MongoDB in a production environment, consider the Production Notes (page 201) document. Later, to stop MongoDB, press Control+C in the terminal where the mongod instance is running. 2.3. Installation Guides 27 MongoDB Documentation, Release 3.0.7 2.3.3 Install MongoDB on Windows Overview Use this tutorial to install MongoDB on Windows systems. Platform Support Starting in version 2.2, MongoDB does not support Windows XP. Please use a more recent version of Windows to use more recent releases of MongoDB. Important: If you are running any edition of Windows Server 2008 R2 or Windows 7, please install a hotfix to resolve an issue with memory mapped files on Windows9. Requirements On Windows MongoDB requires Windows Server 2008 R2, Windows Vista, or later. The .msi installer includes all other software dependencies and will automatically upgrade any older version of MongoDB installed using an .msi file. Get MongoDB Step 1: Determine which MongoDB build you need. There are three builds of MongoDB for Windows: MongoDB for Windows 64-bit runs only on Windows Server 2008 R2, Windows 7 64-bit, and newer versions of Windows. This build takes advantage of recent enhancements to the Windows Platform and cannot operate on older versions of Windows. MongoDB for Windows 32-bit runs on any 32-bit version of Windows newer than Windows Vista. 32-bit versions of MongoDB are only intended for older systems and for use in testing and development systems. 32-bit versions of MongoDB only support databases smaller than 2GB. MongoDB for Windows 64-bit Legacy runs on Windows Vista, Windows Server 2003, and Windows Server 2008 and does not include recent performance enhancements. To find which version of Windows you are running, enter the following commands in the Command Prompt or Pow- ershell: wmic os get caption wmic os get osarchitecture Step 2: Download MongoDB for Windows. Download the latest production release of MongoDB from the MongoDB downloads page10. Ensure you download the correct version of MongoDB for your Windows system. The 64-bit versions of MongoDB do not work with 32-bit Windows. 9http://support.microsoft.com/kb/2731284 10http://www.mongodb.org/downloads 28 Chapter 2. Install MongoDB MongoDB Documentation, Release 3.0.7 Install MongoDB Interactive Installation Step 1: Install MongoDB for Windows. In Windows Explorer, locate the downloaded MongoDB .msi file, which typically is located in the default Downloads folder. Double-click the .msi file. A set of screens will appear to guide you through the installation process. You may specify an installation directory if you choose the “Custom” installation option. Note: These instructions assume that you have installed MongoDB to C:\mongodb. MongoDB is self-contained and does not have any other system dependencies. You can run MongoDB from any folder you choose. You may install MongoDB in any folder (e.g. D:\test\mongodb). Unattended Installation You may install MongoDB unattended on Windows from the command line using msiexec.exe. Step 1: Open an Administrator command prompt. Press the Win key, type cmd.exe, and press Ctrl + Shift + Enter to run the Command Prompt as Administrator. Execute the remaining steps from the Administrator command prompt. Step 2: Install MongoDB for Windows. Change to the directory containing the .msi installation binary of your choice and invoke: msiexec.exe /q /i mongodb-win32-x86_64-2008plus-ssl-3.0.7-signed.msi ^ INSTALLLOCATION="C:\mongodb"^ ADDLOCAL="all" You can specify the installation location for the executable by modifying the INSTALLLOCATION value. By default, this method installs all MongoDB binaries. To install specific MongoDB component sets, you can specify them in the ADDLOCAL argument using a comma-separated list including one or more of the following component sets: Component Set Binaries Server mongod.exe Router mongos.exe Client mongo.exe MonitoringTools mongostat.exe, mongotop.exe ImportExportTools mongodump.exe, mongorestore.exe, mongoexport.exe, mongoimport.exe MiscellaneousTools bsondump.exe, mongofiles.exe, mongooplog.exe, mongoperf.exe For instance, to install only the MongoDB utilities, invoke: msiexec.exe /q /i mongodb-win32-x86_64-2008plus-ssl-3.0.7-signed.msi ^ INSTALLLOCATION="C:\mongodb"^ ADDLOCAL="MonitoringTools,ImportExportTools,MiscellaneousTools" 2.3. Installation Guides 29 MongoDB Documentation, Release 3.0.7 Run MongoDB Warning: Do not make mongod.exe visible on public networks without running in “Secure Mode” with the auth setting. MongoDB is designed to be run in trusted environments, and the database does not enable “Secure Mode” by default. Step 1: Set up the MongoDB environment. MongoDB requires a data directory to store all data. MongoDB’s default data directory path is \data\db. Create this folder using the following commands from a Command Prompt: md \data\db You can specify an alternate path for data files using the --dbpath option to mongod.exe, for example: C:\mongodb\bin\mongod.exe --dbpath d:\test\mongodb\data If your path includes spaces, enclose the entire path in double quotes, for example: C:\mongodb\bin\mongod.exe --dbpath "d:\test\mongo db data" You may also specify the dbpath in a configuration file. Step 2: Start MongoDB. To start MongoDB, run mongod.exe. For example, from the Command Prompt: C:\mongodb\bin\mongod.exe This starts the main MongoDB database process. The waiting for connections message in the console output indicates that the mongod.exe process is running successfully. Depending on the security level of your system, Windows may pop up a Security Alert dialog box about blocking “some features” of C:\mongodb\bin\mongod.exe from communicating on networks. All users should select Private Networks, such as my home or work network and click Allow access. For additional information on security and MongoDB, please see the Security Documentation (page 323). Step 3: Connect to MongoDB. To connect to MongoDB through the mongo.exe shell, open another Command Prompt. C:\mongodb\bin\mongo.exe If you want to develop applications using .NET, see the documentation of C# and MongoDB11 for more information. Step 4: Begin using MongoDB. To help you start using MongoDB, MongoDB provides Getting Started Guides in various driver editions. See getting- started for the available editions. Before deploying MongoDB in a production environment, consider the Production Notes (page 201) document. Later, to stop MongoDB, press Control+C in the terminal where the mongod instance is running. 11https://docs.mongodb.org/ecosystem/drivers/csharp 30 Chapter 2. Install MongoDB MongoDB Documentation, Release 3.0.7 Configure a Windows Service for MongoDB Step 1: Open an Administrator command prompt. Press the Win key, type cmd.exe, and press Ctrl + Shift + Enter to run the Command Prompt as Adminis- trator. Execute the remaining steps from the Administrator command prompt. Step 2: Create directories. Create directories for your database and log files: mkdir c:\data\db mkdir c:\data\log Step 3: Create a configuration file. Create a configuration file. The file must set systemLog.path. Include additional configuration options as appropriate. For example, create a file at C:\mongodb\mongod.cfg that specifies both systemLog.path and storage.dbPath: systemLog: destination: file path: c:\data\log\mongod.log storage: dbPath: c:\data\db Step 4: Install the MongoDB service. Important: Run all of the following commands in Command Prompt with “Administrative Privileges”. Install the MongoDB service by starting mongod.exe with the --install option and the -config option to specify the previously created configuration file. "C:\mongodb\bin\mongod.exe" --config"C:\mongodb\mongod.cfg" --install To use an alternate dbpath, specify the path in the configuration file (e.g. C:\mongodb\mongod.cfg) or on the command line with the --dbpath option. If needed, you can install services for multiple instances of mongod.exe or mongos.exe. Install each service with a unique --serviceName and --serviceDisplayName. Use multiple instances only when sufficient system resources exist and your system design requires it. Step 5: Start the MongoDB service. net start MongoDB 2.3. Installation Guides 31 MongoDB Documentation, Release 3.0.7 Step 6: Stop or remove the MongoDB service as needed. To stop the MongoDB service use the following command: net stop MongoDB To remove the MongoDB service use the following command: "C:\mongodb\bin\mongod.exe" --remove Manually Create a Windows Service for MongoDB You can set up the MongoDB server as a Windows Service that starts automatically at boot time. The following procedure assumes you have installed MongoDB using the .msi installer with the path C:\mongodb\. If you have installed in an alternative directory, you will need to adjust the paths as appropriate. Step 1: Open an Administrator command prompt. Press the Win key, type cmd.exe, and press Ctrl + Shift + Enter to run the Command Prompt as Adminis- trator. Execute the remaining steps from the Administrator command prompt. Step 2: Create directories. Create directories for your database and log files: mkdir c:\data\db mkdir c:\data\log Step 3: Create a configuration file. Create a configuration file. The file must set systemLog.path. Include additional configuration options as appropriate. For example, create a file at C:\mongodb\mongod.cfg that specifies both systemLog.path and storage.dbPath: systemLog: destination: file path: c:\data\log\mongod.log storage: dbPath: c:\data\db Step 4: Create the MongoDB service. Create the MongoDB service. sc.exe create MongoDB binPath= "C:\mongodb\bin\mongod.exe --service --config=\"C:\mongodb\mongod.cfg\"" DisplayName= "MongoDB" start= "auto" 32 Chapter 2. Install MongoDB MongoDB Documentation, Release 3.0.7 sc.exe requires a space between “=” and the configuration values (eg “binPath= ”), and a “\” to escape double quotes. If successfully created, the following log message will display: [SC] CreateService SUCCESS Step 5: Start the MongoDB service. net start MongoDB Step 6: Stop or remove the MongoDB service as needed. To stop the MongoDB service, use the following command: net stop MongoDB To remove the MongoDB service, first stop the service and then run the following command: sc.exe delete MongoDB Additional Resources • MongoDB for Developers Free Course12 • MongoDB for .NET Developers Free Online Course13 • MongoDB Architecture Guide14 2.3.4 Install MongoDB Enterprise These documents provide instructions to install MongoDB Enterprise for Linux and Windows Systems. Install MongoDB Enterprise on Red Hat (page 34) Install the MongoDB Enterprise build and required dependen- cies on Red Hat Enterprise or CentOS Systems using packages. Install MongoDB Enterprise on Ubuntu (page 38) Install the MongoDB Enterprise build and required dependencies on Ubuntu Linux Systems using packages. Install MongoDB Enterprise on Debian (page 42) Install the MongoDB Enterprise build and required dependencies on Debian Linux Systems using packages. Install MongoDB Enterprise on SUSE (page 45) Install the MongoDB Enterprise build and required dependencies on SUSE Enterprise Linux. Install MongoDB Enterprise on Amazon AMI (page 49) Install the MongoDB Enterprise build and required depen- dencies on Amazon Linux AMI. Install MongoDB Enterprise From Tarball (page 50) Install the official build of MongoDB Enterprise from Mon- goDB archives. Install MongoDB Enterprise on Windows (page 52) Install the MongoDB Enterprise build and required dependen- cies using the .msi installer. 12https://university.mongodb.com/courses/M101P/about?jmp=docs 13https://university.mongodb.com/courses/M101N/about?jmp=docs 14https://www.mongodb.com/lp/white-paper/architecture-guide?jmp=docs 2.3. Installation Guides 33 MongoDB Documentation, Release 3.0.7 Install MongoDB Enterprise on Red Hat Enterprise or CentOS Overview Use this tutorial to install MongoDB Enterprise15 on Red Hat Enterprise Linux or CentOS Linux versions 5, 6, and 7 from .rpm packages. Platform Support This installation guide only supports 64-bit systems. See Platform Support (page 819) for details. Packages MongoDB provides officially supported Enterprise packages in their own repository. This repository contains the following packages: • mongodb-enterprise This package is a metapackage that will automatically install the four component packages listed below. • mongodb-enterprise-server This package contains the mongod daemon and associated configuration and init scripts. • mongodb-enterprise-mongos This package contains the mongos daemon. • mongodb-enterprise-shell This package contains the mongo shell. • mongodb-enterprise-tools This package contains the following MongoDB tools: mongoimport bsondump, mongodump, mongoexport, mongofiles, mongoimport, mongooplog, mongoperf, mongorestore, mongostat, and mongotop. Init Scripts The mongodb-enterprise package includes various init scripts, including the init script /etc/rc.d/init.d/mongod. The package configures MongoDB using the /etc/mongod.conf file in conjunction with the init scripts. See the Configuration File reference for documentation of settings available in the configuration file. As of version 3.0.7, there are no init scripts for mongos. The mongos process is used only in sharding (page 667). You can use the mongod init script to derive your own mongos init script. Considerations Use the provided distribution packages as described in this page if possible. These packages will automatically install all of MongoDB’s dependencies, and are the recommended installation method. The default /etc/mongod.conf configuration file supplied by the 3.0 series packages has bind_ip set to 127.0.0.1 by default. Modify this setting as needed for your environment before initializing a replica set. 15https://www.mongodb.com/products/mongodb-enterprise-advanced?jmp=docs 34 Chapter 2. Install MongoDB MongoDB Documentation, Release 3.0.7 Changed in version 2.6: The package structure and names have changed as of version 2.6. For instructions on instal- lation of an older release, please refer to the documentation for the appropriate version. Install MongoDB Enterprise When you install the packages for MongoDB Enterprise, you choose whether to install the current release or a previous one. This procedure describes how to do both. Step 1: Configure repository. Create an /etc/yum.repos.d/mongodb-enterprise.repo file so that you can install MongoDB enterprise directly, using yum. For the latest stable release of MongoDB Enterprise Use the following repository file: [mongodb-enterprise] name=MongoDB Enterprise Repository baseurl=https://repo.mongodb.com/yum/redhat/$releasever/mongodb-enterprise/stable/$basearch/ gpgcheck=0 enabled=1 For specific version of MongoDB Enterprise To install MongoDB Enterprise packages from a specific release se- ries (page 936), such as 2.4 or 2.6, you can specify the release series in the repository configuration. For example, to re- strict your system to the 2.6 release series, create a /etc/yum.repos.d/mongodb-enterprise-2.6.repo file to hold the following configuration information for the MongoDB Enterprise 2.6 repository: [mongodb-enterprise-2.6] name=MongoDB Enterprise 2.6 Repository baseurl=https://repo.mongodb.com/yum/redhat/$releasever/mongodb-enterprise/2.6/$basearch/ gpgcheck=0 enabled=1 .repo files for each release can also be found in the repository itself16. Remember that odd-numbered minor release versions (e.g. 2.5) are development versions and are unsuitable for production deployment. Step 2: Install the MongoDB Enterprise packages and associated tools. You can install either the latest stable version of MongoDB Enterprise or a specific version of MongoDB Enterprise. To install the latest stable version of MongoDB Enterprise, issue the following command: sudo yum install -y mongodb-enterprise Step 3: Optional: Manage Installed Version Install a specific release of MongoDB Enterprise. Specify each component package individually and append the version number to the package name, as in the following example that installs the 2.6.1 release of MongoDB: sudo yum install -y mongodb-enterprise-2.6.1 mongodb-enterprise-server-2.6.1 mongodb-enterprise-shell-2.6.1 mongodb-enterprise-mongos-2.6.1 mongodb-enterprise-tools-2.6.1 16https://repo.mongodb.com/yum/redhat/ 2.3. Installation Guides 35 MongoDB Documentation, Release 3.0.7 Pin a specific version of MongoDB Enterprise. Although you can specify any available version of MongoDB Enterprise, yum will upgrade the packages when a newer version becomes available. To prevent unintended upgrades, pin the package. To pin a package, add the following exclude directive to your /etc/yum.conf file: exclude=mongodb-enterprise,mongodb-enterprise-server,mongodb-enterprise-shell,mongodb-enterprise-mongos,mongodb-enterprise-tools Previous versions of MongoDB packages use different naming conventions. See the 2.4 version of documentation for more information17. Step 4: When the install completes, you can run MongoDB. Install MongoDB Enterprise From Tarball While you should use the .rpm packages as previously described, you may also manually install MongoDB using the tarballs. First you must install any dependencies as appropriate: Version 5 yum install perl cyrus-sasl cyrus-sasl-plain cyrus-sasl-gssapi krb5-libs \ lm_sensors net-snmp openssl popt rpm-libs tcp_wrappers zlib Version 6 yum install cyrus-sasl cyrus-sasl-plain cyrus-sasl-gssapi krb5-libs \ net-snmp openssl Version 7 yum install cyrus-sasl cyrus-sasl-plain cyrus-sasl-gssapi krb5-libs \ lm_sensors-libs net-snmp-agent-libs net-snmp openssl rpm-libs \ tcp_wrappers-libs To perform the installation, see Install MongoDB Enterprise From Tarball (page 50). Run MongoDB Enterprise Prerequisites Configure SELinux Important: You must configure SELinux to allow MongoDB to start on Red Hat Linux-based systems (Red Hat Enterprise Linux or CentOS Linux). To configure SELinux, administrators have three options: Note: All three options require root privileges. The first two options each requires a system reboot and may have larger implications for your deployment. • Disable SELinux entirely by changing the SELINUX setting to disabled in /etc/selinux/config. SELINUX=disabled 17https://docs.mongodb.org/v2.4/tutorial/install-mongodb-on-linux 36 Chapter 2. Install MongoDB MongoDB Documentation, Release 3.0.7 • Set SELinux to permissive mode in /etc/selinux/config by changing the SELINUX setting to permissive . SELINUX=permissive Note: You can use setenforce to change to permissive mode; this method does not require a reboot but is not persistent. • Enable access to the relevant ports (e.g. 27017) for SELinux if in enforcing mode. See Default MongoDB Port (page 425) for more information on MongoDB’s default ports. For default settings, this can be accom- plished by running semanage port -a -t mongod_port_t -p tcp 27017 Warning: On RHEL 7.0, if you change the data path, the default SELinux policies will prevent mongod from having write access on the new data path if you do not change the security context. You may alternatively choose not to install the SELinux packages when you are installing your Linux operating system, or choose to remove the relevant packages. This option is the most invasive and is not recommended. Data Directories and Permissions Warning: On RHEL 7.0, if you change the data path, the default SELinux policies will prevent mongod from having write access on the new data path if you do not change the security context. The MongoDB instance stores its data files in /var/lib/mongo and its log files in /var/log/mongodb by default, and runs using the mongod user account. You can specify alternate log and data file directories in /etc/mongod.conf. See systemLog.path and storage.dbPath for additional information. If you change the user that runs the MongoDB process, you must modify the access control rights to the /var/lib/mongo and /var/log/mongodb directories to give this user access to these directories. Procedure Step 1: Start MongoDB. You can start the mongod process by issuing the following command: sudo service mongod start Step 2: Verify that MongoDB has started successfully You can verify that the mongod process has started suc- cessfully by checking the contents of the log file at /var/log/mongodb/mongod.log for a line reading [initandlisten] waiting for connections on port where is the port configured in /etc/mongod.conf, 27017 by default. You can optionally ensure that MongoDB will start following a system reboot by issuing the following command: sudo chkconfig mongod on Step 3: Stop MongoDB. As needed, you can stop the mongod process by issuing the following command: sudo service mongod stop 2.3. Installation Guides 37 MongoDB Documentation, Release 3.0.7 Step 4: Restart MongoDB. You can restart the mongod process by issuing the following command: sudo service mongod restart You can follow the state of the process for errors or important messages by watching the output in the /var/log/mongodb/mongod.log file. Step 5: Begin using MongoDB. To help you start using MongoDB, MongoDB provides Getting Started Guides in various driver editions. See getting-started for the available editions. Before deploying MongoDB in a production environment, consider the Production Notes (page 201) document. Later, to stop MongoDB, press Control+C in the terminal where the mongod instance is running. Uninstall MongoDB To completely remove MongoDB from a system, you must remove the MongoDB applications themselves, the con- figuration files, and any directories containing data and logs. The following section guides you through the necessary steps. Warning: This process will completely remove MongoDB, its configuration, and all databases. This process is not reversible, so ensure that all of your configuration and data is backed up before proceeding. Step 1: Stop MongoDB. Stop the mongod process by issuing the following command: sudo service mongod stop Step 2: Remove Packages. Remove any MongoDB packages that you had previously installed. sudo yum erase $(rpm -qa | grep mongodb-enterprise) Step 3: Remove Data Directories. Remove MongoDB databases and log files. sudo rm -r /var/log/mongodb sudo rm -r /var/lib/mongo Install MongoDB Enterprise on Ubuntu Overview Use this tutorial to install MongoDB Enterprise18 on LTS Ubuntu Linux systems from .deb packages. Platform Support MongoDB only provides packages for 64-bit long-term support Ubuntu releases. Currently, this means 12.04 LTS (Precise Pangolin) and 14.04 LTS (Trusty Tahr). While the packages may work with other Ubuntu releases, this is not a supported configuration. 18https://www.mongodb.com/products/mongodb-enterprise-advanced?jmp=docs 38 Chapter 2. Install MongoDB MongoDB Documentation, Release 3.0.7 Packages MongoDB provides officially supported Enterprise packages in their own repository. This repository contains the following packages: • mongodb-enterprise This package is a metapackage that will automatically install the four component packages listed below. • mongodb-enterprise-server This package contains the mongod daemon and associated configuration and init scripts. • mongodb-enterprise-mongos This package contains the mongos daemon. • mongodb-enterprise-shell This package contains the mongo shell. • mongodb-enterprise-tools This package contains the following MongoDB tools: mongoimport bsondump, mongodump, mongoexport, mongofiles, mongoimport, mongooplog, mongoperf, mongorestore, mongostat, and mongotop. Init Scripts The mongodb-enterprise package includes various init scripts, including the init script /etc/rc.d/init.d/mongod. The package configures MongoDB using the /etc/mongod.conf file in conjunction with the init scripts. See the Configuration File reference for documentation of settings available in the configuration file. As of version 3.0.7, there are no init scripts for mongos. The mongos process is used only in sharding (page 667). You can use the mongod init script to derive your own mongos init script. Considerations MongoDB only provides packages for 64-bit long-term support Ubuntu releases. Currently, this means 12.04 LTS (Precise Pangolin) and 14.04 LTS (Trusty Tahr). While the packages may work with other Ubuntu releases, this is not a supported configuration. Changed in version 2.6: The package structure and names have changed as of version 2.6. For instructions on instal- lation of an older release, please refer to the documentation for the appropriate version. Use the provided distribution packages as described in this page if possible. These packages will automatically install all of MongoDB’s dependencies, and are the recommended installation method. Install MongoDB Enterprise Step 1: Import the public key used by the package management system. The Ubuntu package management tools (i.e. dpkg and apt) ensure package consistency and authenticity by requiring that distributors sign packages with GPG keys. Issue the following command to import the MongoDB public GPG Key19: 19https://docs.mongodb.org/10gen-gpg-key.asc 2.3. Installation Guides 39 MongoDB Documentation, Release 3.0.7 sudo apt-key adv --keyserver hkp://keyserver.ubuntu.com:80 --recv 7F0CEB10 Step 2: Create a /etc/apt/sources.list.d/mongodb-enterprise.list file for MongoDB. Create the list file using the command appropriate for your version of Ubuntu: Ubuntu 12.04 echo "deb http://repo.mongodb.com/apt/ubuntu precise/mongodb-enterprise/stable multiverse" | sudo tee /etc/apt/sources.list.d/mongodb-enterprise.list Ubuntu 14.04 echo "deb http://repo.mongodb.com/apt/ubuntu trusty/mongodb-enterprise/stable multiverse" | sudo tee /etc/apt/sources.list.d/mongodb-enterprise.list If you’d like to install MongoDB Enterprise packages from a particular release series (page 936), such as 2.4 or 2.6, you can specify the release series in the repository configuration. For example, to restrict your system to the 2.6 release series, add the following repository: echo "deb http://repo.mongodb.com/apt/ubuntu "$(lsb_release -sc)"/mongodb-enterprise/2.6 multiverse" | sudo tee /etc/apt/sources.list.d/mongodb-enterprise-2.6.list Step 3: Reload local package database. Issue the following command to reload the local package database: sudo apt-get update Step 4: Install the MongoDB Enterprise packages. You can install either the latest stable version of MongoDB or a specific version of MongoDB. Install the latest stable version of MongoDB Enterprise. Issue the following command: sudo apt-get install -y mongodb-enterprise Install a specific release of MongoDB Enterprise. To install a specific release, you must specify each component package individually along with the version number, as in the following example: sudo apt-get install -y mongodb-enterprise=3.0.7 mongodb-enterprise-server=3.0.7 mongodb-enterprise-shell=3.0.7 mongodb-enterprise-mongos=3.0.7 mongodb-enterprise-tools=3.0.7 If you only install mongodb-enterprise=3.0.7 and do not include the component packages, the latest version of each MongoDB package will be installed regardless of what version you specified. Pin a specific version of MongoDB Enterprise. Although you can specify any available version of MongoDB, apt-get will upgrade the packages when a newer version becomes available. To prevent unintended upgrades, pin the package. To pin the version of MongoDB at the currently installed version, issue the following command sequence: echo "mongodb-enterprise hold" | sudo dpkg --set-selections echo "mongodb-enterprise-server hold" | sudo dpkg --set-selections echo "mongodb-enterprise-shell hold" | sudo dpkg --set-selections echo "mongodb-enterprise-mongos hold" | sudo dpkg --set-selections echo "mongodb-enterprise-tools hold" | sudo dpkg --set-selections Versions of the MongoDB packages before 2.6 use a different repository location. Refer to the version of the docu- mentation appropriate for your MongoDB version. 40 Chapter 2. Install MongoDB MongoDB Documentation, Release 3.0.7 Install MongoDB Enterprise From Tarball While you should use the .deb packages as previously described, you may also manually install MongoDB using the tarballs. First you must install any dependencies as appropriate: sudo apt-get install libgssapi-krb5-2 libsasl2-2 libssl1.0.0 libstdc++6 snmp To perform the installation, see Install MongoDB Enterprise From Tarball (page 50). Run MongoDB Enterprise The MongoDB instance stores its data files in /var/lib/mongodb and its log files in /var/log/mongodb by default, and runs using the mongodb user account. You can specify alternate log and data file directories in /etc/mongod.conf. See systemLog.path and storage.dbPath for additional information. If you change the user that runs the MongoDB process, you must modify the access control rights to the /var/lib/mongodb and /var/log/mongodb directories to give this user access to these directories. Step 1: Start MongoDB. Issue the following command to start mongod: sudo service mongod start Step 2: Verify that MongoDB has started successfully Verify that the mongod process has started successfully by checking the contents of the log file at /var/log/mongodb/mongod.log for a line reading [initandlisten] waiting for connections on port where is the port configured in /etc/mongod.conf, 27017 by default. Step 3: Stop MongoDB. As needed, you can stop the mongod process by issuing the following command: sudo service mongod stop Step 4: Restart MongoDB. Issue the following command to restart mongod: sudo service mongod restart Step 5: Begin using MongoDB. To help you start using MongoDB, MongoDB provides Getting Started Guides in various driver editions. See getting-started for the available editions. Before deploying MongoDB in a production environment, consider the Production Notes (page 201) document. Later, to stop MongoDB, press Control+C in the terminal where the mongod instance is running. Uninstall MongoDB To completely remove MongoDB from a system, you must remove the MongoDB applications themselves, the con- figuration files, and any directories containing data and logs. The following section guides you through the necessary steps. 2.3. Installation Guides 41 MongoDB Documentation, Release 3.0.7 Warning: This process will completely remove MongoDB, its configuration, and all databases. This process is not reversible, so ensure that all of your configuration and data is backed up before proceeding. Step 1: Stop MongoDB. Stop the mongod process by issuing the following command: sudo service mongod stop Step 2: Remove Packages. Remove any MongoDB packages that you had previously installed. sudo apt-get purge mongodb-enterprise* Step 3: Remove Data Directories. Remove MongoDB databases and log files. sudo rm -r /var/log/mongodb sudo rm -r /var/lib/mongodb Install MongoDB Enterprise on Debian Overview Use this tutorial to install MongoDB Enterprise20 from .deb packages on Debian 7 “Wheezy”. Platform Support This installation guide only supports 64-bit systems. See Platform Support (page 819) for details. Packages MongoDB provides officially supported Enterprise packages in their own repository. This repository contains the following packages: • mongodb-enterprise This package is a metapackage that will automatically install the four component packages listed below. • mongodb-enterprise-server This package contains the mongod daemon and associated configuration and init scripts. • mongodb-enterprise-mongos This package contains the mongos daemon. • mongodb-enterprise-shell This package contains the mongo shell. • mongodb-enterprise-tools This package contains the following MongoDB tools: mongoimport bsondump, mongodump, mongoexport, mongofiles, mongoimport, mongooplog, mongoperf, mongorestore, mongostat, and mongotop. 20https://www.mongodb.com/products/mongodb-enterprise-advanced?jmp=docs 42 Chapter 2. Install MongoDB MongoDB Documentation, Release 3.0.7 Init Scripts The mongodb-enterprise package includes various init scripts, including the init script /etc/rc.d/init.d/mongod. The package configures MongoDB using the /etc/mongod.conf file in conjunction with the init scripts. See the Configuration File reference for documentation of settings available in the configuration file. As of version 3.0.7, there are no init scripts for mongos. The mongos process is used only in sharding (page 667). You can use the mongod init script to derive your own mongos init script. Considerations This installation guide only supports 64-bit systems. See Platform Support (page 819) for details. Changed in version 2.6: The package structure and names have changed as of version 2.6. For instructions on instal- lation of an older release, please refer to the documentation for the appropriate version. Use the provided distribution packages as described in this page if possible. These packages will automatically install all of MongoDB’s dependencies, and are the recommended installation method. Install MongoDB Enterprise Step 1: Import the public key used by the package management system. Issue the following command to add the MongoDB public GPG Key21 to the system key ring. sudo apt-key adv --keyserver keyserver.ubuntu.com --recv 7F0CEB10 Step 2: Create a /etc/apt/sources.list.d/mongodb-enterprise.list file for MongoDB. Create the list file using the following command: echo "deb http://repo.mongodb.com/apt/debian wheezy/mongodb-enterprise/stable main" | sudo tee /etc/apt/sources.list.d/mongodb-enterprise.list If you’d like to install MongoDB Enterprise packages from a particular release series (page 936), such as 2.6, you can specify the release series in the repository configuration. For example, to restrict your system to the 2.6 release series, add the following repository: echo "deb http://repo.mongodb.com/apt/debian wheezy/mongodb-enterprise/2.6 main" | sudo tee /etc/apt/sources.list.d/mongodb-enterprise-2.6.list Currently packages are only available for Debian 7 (Wheezy). Step 3: Reload local package database. Issue the following command to reload the local package database: sudo apt-get update Step 4: Install the MongoDB Enterprise packages. You can install either the latest stable version of MongoDB or a specific version of MongoDB. Install the latest stable version of MongoDB Enterprise. Issue the following command: 21https://docs.mongodb.org/10gen-gpg-key.asc 2.3. Installation Guides 43 MongoDB Documentation, Release 3.0.7 sudo apt-get install -y mongodb-enterprise Install a specific release of MongoDB Enterprise. To install a specific release, you must specify each component package individually along with the version number, as in the following example: sudo apt-get install -y mongodb-enterprise=3.0.7 mongodb-enterprise-server=3.0.7 mongodb-enterprise-shell=3.0.7 mongodb-enterprise-mongos=3.0.7 mongodb-enterprise-tools=3.0.7 If you only install mongodb-enterprise=3.0.7 and do not include the component packages, the latest version of each MongoDB package will be installed regardless of what version you specified. Pin a specific version of MongoDB Enterprise. Although you can specify any available version of MongoDB, apt-get will upgrade the packages when a newer version becomes available. To prevent unintended upgrades, pin the package. To pin the version of MongoDB at the currently installed version, issue the following command sequence: echo "mongodb-enterprise hold" | sudo dpkg --set-selections echo "mongodb-enterprise-server hold" | sudo dpkg --set-selections echo "mongodb-enterprise-shell hold" | sudo dpkg --set-selections echo "mongodb-enterprise-mongos hold" | sudo dpkg --set-selections echo "mongodb-enterprise-tools hold" | sudo dpkg --set-selections Versions of the MongoDB packages before 2.6 use a different repository location. Refer to the version of the docu- mentation appropriate for your MongoDB version. Install MongoDB Enterprise From Tarball While you should use the .deb packages as previously described, you may also manually install MongoDB using the tarballs. First you must install any dependencies as appropriate: sudo apt-get install libgssapi-krb5-2 libsasl2-2 libssl1.0.0 libstdc++6 snmp To perform the installation, see Install MongoDB Enterprise From Tarball (page 50). Run MongoDB Enterprise The MongoDB instance stores its data files in /var/lib/mongodb and its log files in /var/log/mongodb by default, and runs using the mongodb user account. You can specify alternate log and data file directories in /etc/mongod.conf. See systemLog.path and storage.dbPath for additional information. If you change the user that runs the MongoDB process, you must modify the access control rights to the /var/lib/mongodb and /var/log/mongodb directories to give this user access to these directories. Step 1: Start MongoDB. Issue the following command to start mongod: sudo service mongod start Step 2: Verify that MongoDB has started successfully Verify that the mongod process has started successfully by checking the contents of the log file at /var/log/mongodb/mongod.log for a line reading [initandlisten] waiting for connections on port where is the port configured in /etc/mongod.conf, 27017 by default. 44 Chapter 2. Install MongoDB MongoDB Documentation, Release 3.0.7 Step 3: Stop MongoDB. As needed, you can stop the mongod process by issuing the following command: sudo service mongod stop Step 4: Restart MongoDB. Issue the following command to restart mongod: sudo service mongod restart Step 5: Begin using MongoDB. To help you start using MongoDB, MongoDB provides Getting Started Guides in various driver editions. See getting-started for the available editions. Before deploying MongoDB in a production environment, consider the Production Notes (page 201) document. Later, to stop MongoDB, press Control+C in the terminal where the mongod instance is running. Uninstall MongoDB To completely remove MongoDB from a system, you must remove the MongoDB applications themselves, the con- figuration files, and any directories containing data and logs. The following section guides you through the necessary steps. Warning: This process will completely remove MongoDB, its configuration, and all databases. This process is not reversible, so ensure that all of your configuration and data is backed up before proceeding. Step 1: Stop MongoDB. Stop the mongod process by issuing the following command: sudo service mongod stop Step 2: Remove Packages. Remove any MongoDB packages that you had previously installed. sudo apt-get purge mongodb-enterprise* Step 3: Remove Data Directories. Remove MongoDB databases and log files. sudo rm -r /var/log/mongodb sudo rm -r /var/lib/mongodb Install MongoDB Enterprise on SUSE Overview Use this tutorial to install MongoDB Enterprise22 on SUSE Linux. MongoDB Enterprise is available on select plat- forms and contains support for several features related to security and monitoring. Platform Support This installation guide only supports 64-bit systems. See Platform Support (page 819) for details. 22https://www.mongodb.com/products/mongodb-enterprise-advanced?jmp=docs 2.3. Installation Guides 45 MongoDB Documentation, Release 3.0.7 Packages MongoDB provides officially supported Enterprise packages in their own repository. This repository contains the following packages: • mongodb-enterprise This package is a metapackage that will automatically install the four component packages listed below. • mongodb-enterprise-server This package contains the mongod daemon and associated configuration and init scripts. • mongodb-enterprise-mongos This package contains the mongos daemon. • mongodb-enterprise-shell This package contains the mongo shell. • mongodb-enterprise-tools This package contains the following MongoDB tools: mongoimport bsondump, mongodump, mongoexport, mongofiles, mongoimport, mongooplog, mongoperf, mongorestore, mongostat, and mongotop. Init Scripts The mongodb-enterprise package includes various init scripts, including the init script /etc/rc.d/init.d/mongod. The package configures MongoDB using the /etc/mongod.conf file in conjunction with the init scripts. See the Configuration File reference for documentation of settings available in the configuration file. As of version 3.0.7, there are no init scripts for mongos. The mongos process is used only in sharding (page 667). You can use the mongod init script to derive your own mongos init script. Considerations MongoDB only provides Enterprise packages for 64-bit builds of SUSE Enterprise Linux version 11. Use the provided distribution packages as described in this page if possible. These packages will automatically install all of MongoDB’s dependencies, and are the recommended installation method. Note: SUSE Linux Enterprise Server 11 and potentially other versions of SLES and other SUSE distributions ship with virtual memory address space limited to 8GB by default. This must be adjusted in order to prevent virtual memory allocation failures as the database grows. The SLES packages for MongoDB adjust these limits in the default scripts, but you will need to make this change manually if you are using custom scripts and/or the tarball release rather than the SLES packages. Install MongoDB Enterprise Step 1: Configure the package management system (zypper). Add the repository so that you can install Mon- goDB using zypper. Use the following command to specify the latest stable release of MongoDB. 46 Chapter 2. Install MongoDB MongoDB Documentation, Release 3.0.7 sudo zypper addrepo --no-gpgcheck https://repo.mongodb.com/zypper/suse/11/mongodb-enterprise/stable/x86_64/ mongodb If you’d like to install MongoDB packages from a previous release series (page 936), such as 2.6, you can specify the release series in the repository configuration. For example, to restrict your system to the 2.6 release series, use the following command: sudo zypper addrepo --no-gpgcheck https://repo.mongodb.com/zypper/suse/11/mongodb-enterprise/2.6/x86_64/ mongodb Step 2: Install the MongoDB packages and associated tools. When you install the packages, you choose whether to install the current release or a previous one. This step provides the commands for both. To install the latest stable version of MongoDB, issue the following command: sudo zypper -n install mongodb-enterprise To install a specific release of MongoDB, specify each component package individually and append the version number to the package name, as in the following example: sudo zypper install mongodb-enterprise-3.0.7 mongodb-enterprise-server-3.0.7 mongodb-enterprise-shell-3.0.7 mongodb-enterprise-mongos-3.0.7 mongodb-enterprise-tools-3.0.7 You can specify any available version of MongoDB. However zypper will upgrade the packages when a newer version becomes available. To prevent unintended upgrades, pin the packages by running the following command: sudo zypper addlock mongodb-enterprise-3.0.7 mongodb-enterprise-server-3.0.7 mongodb-enterprise-shell-3.0.7 mongodb-enterprise-mongos-3.0.7 mongodb-enterprise-tools-3.0.7 Previous versions of MongoDB packages use a different repository location. Refer to the version of the documentation appropriate for your MongoDB version. Install MongoDB Enterprise From Tarball While you should use the .rpm packages as previously described, you may also manually install MongoDB using the tarballs. First you must install any dependencies as appropriate: zypper install cyrus-sasl cyrus-sasl-plain cyrus-sasl-gssapi krb5 \ libopenssl0_9_8 net-snmp libstdc++46 zlib To perform the installation, see Install MongoDB Enterprise From Tarball (page 50). Run MongoDB Enterprise Prerequisites The MongoDB instance stores its data files in /var/lib/mongo and its log files in /var/log/mongodb by default, and runs using the mongod user account. You can specify alternate log and data file directories in /etc/mongod.conf. See systemLog.path and storage.dbPath for additional in- formation. If you change the user that runs the MongoDB process, you must modify the access control rights to the /var/lib/mongo and /var/log/mongodb directories to give this user access to these directories. Procedure 2.3. Installation Guides 47 MongoDB Documentation, Release 3.0.7 Step 1: Start MongoDB. You can start the mongod process by issuing the following command: sudo service mongod start Step 2: Verify that MongoDB has started successfully You can verify that the mongod process has started suc- cessfully by checking the contents of the log file at /var/log/mongodb/mongod.log for a line reading [initandlisten] waiting for connections on port where is the port configured in /etc/mongod.conf, 27017 by default. You can optionally ensure that MongoDB will start following a system reboot by issuing the following command: sudo chkconfig mongod on Step 3: Stop MongoDB. As needed, you can stop the mongod process by issuing the following command: sudo service mongod stop Step 4: Restart MongoDB. You can restart the mongod process by issuing the following command: sudo service mongod restart You can follow the state of the process for errors or important messages by watching the output in the /var/log/mongodb/mongod.log file. Step 5: Begin using MongoDB. To help you start using MongoDB, MongoDB provides Getting Started Guides in various driver editions. See getting-started for the available editions. Before deploying MongoDB in a production environment, consider the Production Notes (page 201) document. Later, to stop MongoDB, press Control+C in the terminal where the mongod instance is running. Uninstall MongoDB To completely remove MongoDB from a system, you must remove the MongoDB applications themselves, the con- figuration files, and any directories containing data and logs. The following section guides you through the necessary steps. Warning: This process will completely remove MongoDB, its configuration, and all databases. This process is not reversible, so ensure that all of your configuration and data is backed up before proceeding. Step 1: Stop MongoDB. Stop the mongod process by issuing the following command: sudo service mongod stop Step 2: Remove Packages. Remove any MongoDB packages that you had previously installed. sudo zypper remove $(rpm -qa | grep mongodb-enterprise) 48 Chapter 2. Install MongoDB MongoDB Documentation, Release 3.0.7 Step 3: Remove Data Directories. Remove MongoDB databases and log files. sudo rm -r /var/log/mongodb sudo rm -r /var/lib/mongo Install MongoDB Enterprise on Amazon Linux AMI Overview Use this tutorial to install MongoDB Enterprise23 on Amazon Linux AMI. MongoDB Enterprise is available on select platforms and contains support for several features related to security and monitoring. This installation guide only supports 64-bit systems. See Platform Support (page 819) for details. Prerequisites To install all of MongoDB’s dependencies, run the following command: yum install cyrus-sasl cyrus-sasl-plain cyrus-sasl-gssapi krb5-libs \ lm_sensors-libs net-snmp-agent-libs net-snmp openssl rpm-libs \ tcp_wrappers-libs Install MongoDB Enterprise Note: The Enterprise packages include an example SNMP configuration file named mongod.conf. This file is not a MongoDB configuration file. Step 1: Download and install the MongoDB Enterprise packages. After you have installed the required pre- requisite packages, download and install the MongoDB Enterprise packages from https://mongodb.com/download/. The MongoDB binaries are located in the bin/ directory of the archive. To download and install, use the following sequence of commands. curl -O https://downloads.mongodb.com/linux/mongodb-linux-x86_64-enterprise-amzn64-3.0.7.tgz tar -zxvf mongodb-linux-x86_64-enterprise-amzn64-3.0.7.tgz cp -R -n mongodb-linux-x86_64-enterprise-amzn64-3.0.7/ mongodb Step 2: Ensure the location of the MongoDB binaries is included in the PATH variable. Once you have copied the MongoDB binaries to their target location, ensure that the location is included in your PATH variable. If it is not, either include it or create symbolic links from the binaries to a directory that is included. Run MongoDB Enterprise The MongoDB instance stores its data files in /data/db and its log files in /var/log/mongodb by default, and runs using the mongod user account. You can specify alternate log and data file directories in /etc/mongod.conf. See systemLog.path and storage.dbPath for additional information. If you change the user that runs the MongoDB process, you must modify the access control rights to the /data/db and /var/log/mongodb directories to give this user access to these directories. 23https://www.mongodb.com/products/mongodb-enterprise-advanced?jmp=docs 2.3. Installation Guides 49 MongoDB Documentation, Release 3.0.7 Step 1: Create the data directory. Before you start MongoDB for the first time, create the directory to which the mongod process will write data. By default, the mongod process uses the /data/db directory. If you create a directory other than this one, you must specify that directory in the dbpath option when starting the mongod process later in this procedure. The following example command creates the default /data/db directory: mkdir -p /data/db Step 2: Set permissions for the data directory. Before running mongod for the first time, ensure that the user account running mongod has read and write permissions for the directory. Step 3: Run MongoDB. To run MongoDB, run the mongod process at the system prompt. If necessary, specify the path of the mongod or the data directory. See the following examples. Run without specifying paths If your system PATH variable includes the location of the mongod binary and if you use the default data directory (i.e., /data/db), simply enter mongod at the system prompt: mongod Specify the path of the mongod If your PATH does not include the location of the mongod binary, enter the full path to the mongod binary at the system prompt: /mongod Specify the path of the data directory If you do not use the default data directory (i.e., /data/db), specify the path to the data directory using the --dbpath option: mongod --dbpath Step 4: Begin using MongoDB. To help you start using MongoDB, MongoDB provides Getting Started Guides in various driver editions. See getting-started for the available editions. Before deploying MongoDB in a production environment, consider the Production Notes (page 201) document. Later, to stop MongoDB, press Control+C in the terminal where the mongod instance is running. Install MongoDB Enterprise From Tarball Overview Compiled versions of MongoDB Enterprise for Linux provide a simple option for installing MongoDB for other Linux systems without supported packages. Install MongoDB Step 1: Install any missing dependencies. To manually install MongoDB Enterprise, first install any dependencies as appropriate. 50 Chapter 2. Install MongoDB MongoDB Documentation, Release 3.0.7 Step 2: Download and install the MongoDB Enterprise packages. After you have installed the required pre- requisite packages, download and install the MongoDB Enterprise packages from https://mongodb.com/download/. The MongoDB binaries are located in the bin/ directory of the archive. To download and install, use the following sequence of commands. Step 3: Ensure the location of the MongoDB binaries is included in the PATH variable. Once you have copied the MongoDB binaries to their target location, ensure that the location is included in your PATH variable. If it is not, either include it or create symbolic links from the binaries to a directory that is included. Run MongoDB Step 1: Create the data directory. Before you start MongoDB for the first time, create the directory to which the mongod process will write data. By default, the mongod process uses the /data/db directory. If you create a directory other than this one, you must specify that directory in the dbpath option when starting the mongod process later in this procedure. The following example command creates the default /data/db directory: mkdir -p /data/db Step 2: Set permissions for the data directory. Before running mongod for the first time, ensure that the user account running mongod has read and write permissions for the directory. Step 3: Run MongoDB. To run MongoDB, run the mongod process at the system prompt. If necessary, specify the path of the mongod or the data directory. See the following examples. Run without specifying paths If your system PATH variable includes the location of the mongod binary and if you use the default data directory (i.e., /data/db), simply enter mongod at the system prompt: mongod Specify the path of the mongod If your PATH does not include the location of the mongod binary, enter the full path to the mongod binary at the system prompt: /mongod Specify the path of the data directory If you do not use the default data directory (i.e., /data/db), specify the path to the data directory using the --dbpath option: mongod --dbpath Step 4: Begin using MongoDB. To help you start using MongoDB, MongoDB provides Getting Started Guides in various driver editions. See getting-started for the available editions. Before deploying MongoDB in a production environment, consider the Production Notes (page 201) document. Later, to stop MongoDB, press Control+C in the terminal where the mongod instance is running. 2.3. Installation Guides 51 MongoDB Documentation, Release 3.0.7 Install MongoDB Enterprise on Windows New in version 2.6. Overview Use this tutorial to install MongoDB Enterprise24 on Windows systems. MongoDB Enterprise is available on select platforms and contains support for several features related to security and monitoring. Prerequisites MongoDB Enterprise Server for Windows requires Windows Server 2008 R2 or later. The .msi installer includes all other software dependencies and will automatically upgrade any older version of MongoDB installed using an .msi file. Get MongoDB Enterprise Step 1: Download MongoDB Enterprise for Windows. Download the latest production release of MongoDB Enterprise25. To find which version of Windows you are running, enter the following commands in the Command Prompt or Pow- ershell: wmic os get caption wmic os get osarchitecture Install MongoDB Enterprise Interactive Installation Step 1: Install MongoDB Enterprise for Windows. In Windows Explorer, locate the downloaded MongoDB .msi file, which typically is located in the default Downloads folder. Double-click the .msi file. A set of screens will appear to guide you through the installation process. You may specify an installation directory if you choose the “Custom” installation option. Note: These instructions assume that you have installed MongoDB to C:\mongodb. MongoDB is self-contained and does not have any other system dependencies. You can run MongoDB from any folder you choose. You may install MongoDB in any folder (e.g. D:\test\mongodb). Unattended Installation You may install MongoDB unattended on Windows from the command line using msiexec.exe. 24https://www.mongodb.com/products/mongodb-enterprise-advanced?jmp=docs 25http://www.mongodb.com/products/mongodb-enterprise?jmp=docs 52 Chapter 2. Install MongoDB MongoDB Documentation, Release 3.0.7 Step 1: Install MongoDB Enterprise for Windows. Change to the directory containing the .msi installation binary of your choice and invoke: msiexec.exe /q /i mongodb-win32-x86_64-2008plus-ssl-3.0.7-signed.msi ^ INSTALLLOCATION="C:\mongodb"^ ADDLOCAL="all" You can specify the installation location for the executable by modifying the INSTALLLOCATION value. By default, this method installs all MongoDB binaries. To install specific MongoDB component sets, you can specify them in the ADDLOCAL argument using a comma-separated list including one or more of the following component sets: Component Set Binaries Server mongod.exe Router mongos.exe Client mongo.exe MonitoringTools mongostat.exe, mongotop.exe ImportExportTools mongodump.exe, mongorestore.exe, mongoexport.exe, mongoimport.exe MiscellaneousTools bsondump.exe, mongofiles.exe, mongooplog.exe, mongoperf.exe For instance, to install only the MongoDB utilities, invoke: msiexec.exe /q /i mongodb-win32-x86_64-2008plus-ssl-3.0.7-signed.msi ^ INSTALLLOCATION="C:\mongodb"^ ADDLOCAL="MonitoringTools,ImportExportTools,MiscellaneousTools" Run MongoDB Enterprise Warning: Do not make mongod.exe visible on public networks without running in “Secure Mode” with the auth setting. MongoDB is designed to be run in trusted environments, and the database does not enable “Secure Mode” by default. Step 1: Set up the MongoDB environment. MongoDB requires a data directory to store all data. MongoDB’s default data directory path is \data\db. Create this folder using the following commands from a Command Prompt: md \data\db You can specify an alternate path for data files using the --dbpath option to mongod.exe, for example: C:\mongodb\bin\mongod.exe --dbpath d:\test\mongodb\data If your path includes spaces, enclose the entire path in double quotes, for example: C:\mongodb\bin\mongod.exe --dbpath "d:\test\mongo db data" You may also specify the dbpath in a configuration file. Step 2: Start MongoDB. To start MongoDB, run mongod.exe. For example, from the Command Prompt: C:\mongodb\bin\mongod.exe This starts the main MongoDB database process. The waiting for connections message in the console output indicates that the mongod.exe process is running successfully. 2.3. Installation Guides 53 MongoDB Documentation, Release 3.0.7 Depending on the security level of your system, Windows may pop up a Security Alert dialog box about blocking “some features” of C:\mongodb\bin\mongod.exe from communicating on networks. All users should select Private Networks, such as my home or work network and click Allow access. For additional information on security and MongoDB, please see the Security Documentation (page 323). Step 3: Connect to MongoDB. To connect to MongoDB through the mongo.exe shell, open another Command Prompt. C:\mongodb\bin\mongo.exe If you want to develop applications using .NET, see the documentation of C# and MongoDB26 for more information. Step 4: Begin using MongoDB. To help you start using MongoDB, MongoDB provides Getting Started Guides in various driver editions. See getting-started for the available editions. Before deploying MongoDB in a production environment, consider the Production Notes (page 201) document. Later, to stop MongoDB, press Control+C in the terminal where the mongod instance is running. Configure a Windows Service for MongoDB Enterprise Step 1: Open an Administrator command prompt. Press the Win key, type cmd.exe, and press Ctrl + Shift + Enter to run the Command Prompt as Administrator. Execute the remaining steps from the Administrator command prompt. Step 2: Create directories. Create directories for your database and log files: mkdir c:\data\db mkdir c:\data\log Step 3: Create a configuration file. Create a configuration file. The file must set systemLog.path. Include additional configuration options as appropriate. For example, create a file at C:\mongodb\mongod.cfg that specifies both systemLog.path and storage.dbPath: systemLog: destination: file path: c:\data\log\mongod.log storage: dbPath: c:\data\db Step 4: Install the MongoDB service. Important: Run all of the following commands in Command Prompt with “Administrative Privileges”. Install the MongoDB service by starting mongod.exe with the --install option and the -config option to specify the previously created configuration file. "C:\mongodb\bin\mongod.exe" --config"C:\mongodb\mongod.cfg" --install 26https://docs.mongodb.org/ecosystem/drivers/csharp 54 Chapter 2. Install MongoDB MongoDB Documentation, Release 3.0.7 To use an alternate dbpath, specify the path in the configuration file (e.g. C:\mongodb\mongod.cfg) or on the command line with the --dbpath option. If needed, you can install services for multiple instances of mongod.exe or mongos.exe. Install each service with a unique --serviceName and --serviceDisplayName. Use multiple instances only when sufficient system resources exist and your system design requires it. Step 5: Start the MongoDB service. net start MongoDB Step 6: Stop or remove the MongoDB service as needed. To stop the MongoDB service use the following com- mand: net stop MongoDB To remove the MongoDB service use the following command: "C:\mongodb\bin\mongod.exe" --remove Manually Create a Windows Service for MongoDB Enterprise You can set up the MongoDB server as a Windows Service that starts automatically at boot time. The following procedure assumes you have installed MongoDB using the .msi installer with the path C:\mongodb\. If you have installed in an alternative directory, you will need to adjust the paths as appropriate. Step 1: Open an Administrator command prompt. Press the Win key, type cmd.exe, and press Ctrl + Shift + Enter to run the Command Prompt as Administrator. Execute the remaining steps from the Administrator command prompt. Step 2: Create directories. Create directories for your database and log files: mkdir c:\data\db mkdir c:\data\log Step 3: Create a configuration file. Create a configuration file. The file must set systemLog.path. Include additional configuration options as appropriate. For example, create a file at C:\mongodb\mongod.cfg that specifies both systemLog.path and storage.dbPath: systemLog: destination: file path: c:\data\log\mongod.log storage: dbPath: c:\data\db Step 4: Create the MongoDB service. Create the MongoDB service. 2.3. Installation Guides 55 MongoDB Documentation, Release 3.0.7 sc.exe create MongoDB binPath= "C:\mongodb\bin\mongod.exe --service --config=\"C:\mongodb\mongod.cfg\"" DisplayName= "MongoDB" start= "auto" sc.exe requires a space between “=” and the configuration values (eg “binPath= ”), and a “\” to escape double quotes. If successfully created, the following log message will display: [SC] CreateService SUCCESS Step 5: Start the MongoDB service. net start MongoDB Step 6: Stop or remove the MongoDB service as needed. To stop the MongoDB service, use the following com- mand: net stop MongoDB To remove the MongoDB service, first stop the service and then run the following command: sc.exe delete MongoDB 2.3.5 Verify Integrity of MongoDB Packages Overview The MongoDB release team digitally signs all software packages to certify that a particular MongoDB package is a valid and unaltered MongoDB release. Before installing MongoDB, you should validate the package using either the provided PGP signature or SHA-256 checksum. PGP signatures provide the strongest guarantees by checking both the authenticity and integrity of a file to prevent tampering. Cryptographic checksums only validate file integrity to prevent network transmission errors. Procedures Use PGP/GPG MongoDB signs each release branch with a different PGP key. The public key files for each release branch since MongoDB 2.2 are available for download from the key server27 in both textual .asc and binary .pub formats. Step 1: Download the MongoDB installation file. Download the binaries from https://www.mongodb.org/downloads based on your environment. For example, to download the 3.0.5 release for OS X through the shell, type this command: curl -LO https://fastdl.mongodb.org/osx/mongodb-osx-x86_64-3.0.5.tgz Step 2: Download the public signature file. 27https://www.mongodb.org/static/pgp/ 56 Chapter 2. Install MongoDB MongoDB Documentation, Release 3.0.7 curl -LO https://fastdl.mongodb.org/osx/mongodb-osx-x86_64-3.0.5.tgz.sig Step 3: Download then import the key file. If you have not downloaded and imported the MongoDB 3.0 public key, enter these commands: curl -LO https://www.mongodb.org/static/pgp/server-3.0.asc gpg --import server-3.0.asc You should receive this message: gpg: key 24F3C978: public key "MongoDB 3.0 Release Signing Key " imported gpg: Total number processed: 1 gpg: imported: 1 Step 4: Verify the MongoDB installation file. Type this command: gpg --verify mongodb-osx-x86_64-3.0.5.tgz.sig mongodb-osx-x86_64-3.0.5.tgz You should receive this message: gpg: Signature made Mon 27 Jul 2015 07:51:53 PM EDT using RSA key ID 24F3C978 gpg: Good signature from "MongoDB 3.0 Release Signing Key "[unknown] If you receive a message such as the following, confirm that you imported the correct public key: gpg: Signature made Mon 27 Jul 2015 07:51:53 PM EDT using RSA key ID 24F3C978 gpg: Can't check signature: public key not found gpg will return the following message if the package is properly signed, but you do not currently trust the signing key in your local trustdb. gpg: WARNING: This key is not certified with a trusted signature! gpg: There is no indication that the signature belongs to the owner. Primary key fingerprint: 89AE C6ED 5423 0831 793F 1384 BE0E B6AA 24F3 C978 Use SHA-256 Step 1: Download the MongoDB installation file. Download the binaries from https://www.mongodb.org/downloads based on your environment. For example, to download the 3.0.5 release for OS X through the shell, type this command: curl -LO https://fastdl.mongodb.org/osx/mongodb-osx-x86_64-3.0.5.tgz Step 2: Download the SHA256 file. curl -LO https://fastdl.mongodb.org/osx/mongodb-osx-x86_64-3.0.5.tgz.sha256 Step 3: Use the SHA-256 checksum to verify the MongoDB package file. Compute the checksum of the package file: shasum -c mongodb-osx-x86_64-3.0.5.tgz.sha256 which should return the following if the checksum matched the downloaded package: 2.3. Installation Guides 57 MongoDB Documentation, Release 3.0.7 mongodb-osx-x86_64-3.0.5.tgz: OK 2.4 First Steps with MongoDB Once you have installed MongoDB, consider the Getting Started Guides to learn about MongoDB. The guides are available in various driver editions. 2.5 Additional Resources • Install MongoDB using MongoDB Cloud Manager28 • Create a New MongoDB Deployment with Ops Manager29: Ops Manager is an on-premise solution available in MongoDB Enterprise Advanced30. • MongoDB CRUD Concepts (page 62) • Data Models (page 147) 28https://docs.cloud.mongodb.com/tutorial/getting-started?jmp=docs 29https://docs.opsmanager.mongodb.com/current/tutorial/nav/management 30https://www.mongodb.com/products/mongodb-enterprise-advanced?jmp=docs 58 Chapter 2. Install MongoDB CHAPTER 3 MongoDB CRUD Operations MongoDB provides rich semantics for reading and manipulating data. CRUD stands for create, read, update, and delete. These terms are the foundation for all interactions with the database. MongoDB CRUD Introduction (page 59) An introduction to the MongoDB data model as well as queries and data manipulations. MongoDB CRUD Concepts (page 62) The core documentation of query and data manipulation. MongoDB CRUD Tutorials (page 94) Examples of basic query and data modification operations. MongoDB CRUD Reference (page 132) Reference material for the query and data manipulation interfaces. 3.1 MongoDB CRUD Introduction MongoDB stores data in the form of documents, which are JSON-like field and value pairs. Documents are analogous to structures in programming languages that associate keys with values (e.g. dictionaries, hashes, maps, and associative arrays). Formally, MongoDB documents are BSON documents. BSON is a binary representation of JSON with additional type information. In the documents, the value of a field can be any of the BSON data types, including other documents, arrays, and arrays of documents. For more information, see Documents (page 172). MongoDB stores all documents in collections. A collection is a group of related documents that have a set of shared common indexes. Collections are analogous to a table in relational databases. 59 MongoDB Documentation, Release 3.0.7 3.1.1 Database Operations Query In MongoDB a query targets a specific collection of documents. Queries specify criteria, or conditions, that identify the documents that MongoDB returns to the clients. A query may include a projection that specifies the fields from the matching documents to return. You can optionally modify queries to impose limits, skips, and sort orders. In the following diagram, the query process specifies a query criteria and a sort modifier: See Read Operations Overview (page 63) for more information. 60 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 Data Modification Data modification refers to operations that create, update, or delete data. In MongoDB, these operations modify the data of a single collection. For the update and delete operations, you can specify the criteria to select the documents to update or remove. In the following diagram, the insert operation adds a new document to the users collection. See Write Operations Overview (page 76) for more information. 3.1.2 Related Features Indexes To enhance the performance of common queries and updates, MongoDB has full support for secondary indexes. These indexes allow applications to store a view of a portion of the collection in an efficient data structure. Most indexes store an ordered representation of all values of a field or a group of fields. Indexes may also enforce uniqueness (page 504), store objects in a geospatial representation (page 493), and facilitate text search (page 500). 3.1. MongoDB CRUD Introduction 61 MongoDB Documentation, Release 3.0.7 Replica Set Read Preference For replica sets and sharded clusters with replica set components, applications specify read preferences (page 588). A read preference determines how the client directs read operations to the set. Write Concern Applications can also control the behavior of write operations using write concern (page 80). Particularly useful for deployments with replica sets, the write concern semantics allow clients to specify the assurance that MongoDB provides when reporting on the success of a write operation. Aggregation In addition to the basic queries, MongoDB provides several data aggregation features. For example, MongoDB can return counts of the number of documents that match a query, or return the number of distinct values for a field, or process a collection of documents using a versatile stage-based data processing pipeline or map-reduce operations. 3.2 MongoDB CRUD Concepts The Read Operations (page 62) and Write Operations (page 75) documents introduce the behavior and operations of read and write operations for MongoDB deployments. Read Operations (page 62) Queries are the core operations that return data in MongoDB. Introduces queries, their behavior, and performances. Cursors (page 66) Queries return iterable objects, called cursors, that hold the full result set. Query Optimization (page 67) Analyze and improve query performance. Distributed Queries (page 71) Describes how sharded clusters and replica sets affect the performance of read operations. Write Operations (page 75) Write operations insert, update, or remove documents in MongoDB. Introduces data create and modify operations, their behavior, and performances. Write Concern (page 80) Describes the kind of guarantee MongoDB provides when reporting on the success of a write operation. Distributed Write Operations (page 84) Describes how MongoDB directs write operations on sharded clusters and replica sets and the performance characteristics of these operations. Continue reading from Write Operations (page 75) for additional background on the behavior of data modifica- tion operations in MongoDB. 3.2.1 Read Operations The following documents describe read operations: Read Operations Overview (page 63) A high level overview of queries and projections in MongoDB, including a discussion of syntax and behavior. Cursors (page 66) Queries return iterable objects, called cursors, that hold the full result set. Query Optimization (page 67) Analyze and improve query performance. Query Plans (page 70) MongoDB executes queries using optimal plans. 62 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 Distributed Queries (page 71) Describes how sharded clusters and replica sets affect the performance of read opera- tions. Read Operations Overview Read operations, or queries, retrieve data stored in the database. In MongoDB, queries select documents from a single collection. Queries specify criteria, or conditions, that identify the documents that MongoDB returns to the clients. A query may include a projection that specifies the fields from the matching documents to return. The projection limits the amount of data that MongoDB returns to the client over the network. Query Interface For query operations, MongoDB provides a db.collection.find() method. The method accepts both the query criteria and projections and returns a cursor (page 66) to the matching documents. You can optionally modify the query to impose limits, skips, and sort orders. The following diagram highlights the components of a MongoDB query operation: The next diagram shows the same query in SQL: Example db.users.find( { age: { $gt: 18 } }, { name:1, address:1 } ).limit(5) This query selects the documents in the users collection that match the condition age is greater than 18. To specify the greater than condition, query criteria uses the greater than (i.e. $gt) query selection operator. The query returns at most 5 matching documents (or more precisely, a cursor to those documents). The matching documents will return with only the _id, name and address fields. See Projections (page 64) for details. See SQL to MongoDB Mapping Chart (page 134) for additional examples of MongoDB queries and the corresponding SQL statements. 3.2. MongoDB CRUD Concepts 63 MongoDB Documentation, Release 3.0.7 Query Behavior MongoDB queries exhibit the following behavior: • All queries in MongoDB address a single collection. • You can modify the query to impose limits, skips, and sort orders. • The order of documents returned by a query is not defined unless you specify a sort(). • Operations that modify existing documents (page 104) (i.e. updates) use the same query syntax as queries to select documents to update. • In aggregation (page 439) pipeline, the $match pipeline stage provides access to MongoDB queries. MongoDB provides a db.collection.findOne() method as a special case of find() that returns a single document. Query Statements Consider the following diagram of the query process that specifies a query criteria and a sort modifier: In the diagram, the query selects documents from the users collection. Using a query selection operator to define the conditions for matching documents, the query selects documents that have age greater than (i.e. $gt) 18. Then the sort() modifier sorts the results by age in ascending order. For additional examples of queries, see Query Documents (page 98). Projections Queries in MongoDB return all fields in all matching documents by default. To limit the amount of data that MongoDB sends to applications, include a projection in the queries. By projecting results with a subset of fields, applications reduce their network overhead and processing requirements. 64 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 Projections, which are the second argument to the find() method, may either specify a list of fields to return or list fields to exclude in the result documents. Important: Except for excluding the _id field in inclusive projections, you cannot mix exclusive and inclusive projections. Consider the following diagram of the query process that specifies a query criteria and a projection: In the diagram, the query selects from the users collection. The criteria matches the documents that have age equal to 18. Then the projection specifies that only the name field should return in the matching documents. Projection Examples Exclude One Field From a Result Set db.records.find( { "user_id": { $lt: 42}},{ "history":0}) This query selects documents in the records collection that match the condition { "user_id": { $lt: 42 }}, and uses the projection { "history": 0 } to exclude the history field from the documents in the result set. Return Two fields and the _id Field db.records.find( { "user_id": { $lt: 42}},{ "name":1, "email":1}) This query selects documents in the records collection that match the query { "user_id": { $lt: 42 } } and uses the projection { "name": 1, "email": 1 } to return just the _id field (implicitly included), name field, and the email field in the documents in the result set. 3.2. MongoDB CRUD Concepts 65 MongoDB Documentation, Release 3.0.7 Return Two Fields and Exclude _id db.records.find( { "user_id": { $lt: 42} }, { "_id":0, "name":1, "email":1}) This query selects documents in the records collection that match the query { "user_id": { $lt: 42} }, and only returns the name and email fields in the documents in the result set. See Limit Fields to Return from a Query (page 109) for more examples of queries with projection statements. Projection Behavior MongoDB projections have the following properties: • By default, the _id field is included in the results. To suppress the _id field from the result set, specify _id: 0 in the projection document. • For fields that contain arrays, MongoDB provides the following projection operators: $elemMatch, $slice, and $. • For related projection functionality in the aggregation framework (page 439) pipeline, use the $project pipeline stage. Cursors In the mongo shell, the primary method for the read operation is the db.collection.find() method. This method queries a collection and returns a cursor to the returning documents. To access the documents, you need to iterate the cursor. However, in the mongo shell, if the returned cursor is not assigned to a variable using the var keyword, then the cursor is automatically iterated up to 20 times 1 to print up to the first 20 documents in the results. For example, in the mongo shell, the following read operation queries the inventory collection for documents that have type equal to ’food’ and automatically print up to the first 20 matching documents: db.inventory.find( { type: 'food'}); To manually iterate the cursor to access the documents, see Iterate a Cursor in the mongo Shell (page 113). Cursor Behaviors Closure of Inactive Cursors By default, the server will automatically close the cursor after 10 minutes of inactivity or if client has exhausted the cursor. To override this behavior, you can specify the noTimeout flag in your query using cursor.addOption(); however, you should either close the cursor manually or exhaust the cursor. In the mongo shell, you can set the noTimeout flag: var myCursor= db.inventory.find().addOption(DBQuery.Option.noTimeout); See your driver documentation for information on setting the noTimeout flag. For the mongo shell, see cursor.addOption() for a complete list of available cursor flags. Cursor Isolation Because the cursor is not isolated during its lifetime, intervening write operations on a document may result in a cursor that returns a document more than once if that document has changed. To handle this situation, see the information on snapshot mode (page 754). 1 You can use the DBQuery.shellBatchSize to change the number of iteration from the default value 20. See Executing Queries (page 278) for more information. 66 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 Cursor Batches The MongoDB server returns the query results in batches. Batch size will not exceed the maximum BSON document size. For most queries, the first batch returns 101 documents or just enough documents to exceed 1 megabyte. Subsequent batch size is 4 megabytes. To override the default size of the batch, see batchSize() and limit(). For queries that include a sort operation without an index, the server must load all the documents in memory to perform the sort before returning any results. As you iterate through the cursor and reach the end of the returned batch, if there are more results, cursor.next() will perform a getmore operation to retrieve the next batch. To see how many documents remain in the batch as you iterate the cursor, you can use the objsLeftInBatch() method, as in the following example: var myCursor= db.inventory.find(); var myFirstDocument= myCursor.hasNext()? myCursor.next(): null; myCursor.objsLeftInBatch(); Cursor Information The db.serverStatus() method returns a document that includes a metrics field. The metrics field con- tains a cursor field with the following information: • number of timed out cursors since the last server restart • number of open cursors with the option DBQuery.Option.noTimeout set to prevent timeout after a period of inactivity • number of “pinned” open cursors • total number of open cursors Consider the following example which calls the db.serverStatus() method and accesses the metrics field from the results and then the cursor field from the metrics field: db.serverStatus().metrics.cursor The result is the following document: { "timedOut": "open":{ "noTimeout":, "pinned":, "total": } } See also: db.serverStatus() Query Optimization Indexes improve the efficiency of read operations by reducing the amount of data that query operations need to process. This simplifies the work associated with fulfilling queries within MongoDB. 3.2. MongoDB CRUD Concepts 67 MongoDB Documentation, Release 3.0.7 Create an Index to Support Read Operations If your application queries a collection on a particular field or set of fields, then an index on the queried field or a compound index (page 488) on the set of fields can prevent the query from scanning the whole collection to find and return the query results. For more information about indexes, see the complete documentation of indexes in MongoDB (page 485). Example An application queries the inventory collection on the type field. The value of the type field is user-driven. var typeValue=; db.inventory.find( { type: typeValue } ); To improve the performance of this query, add an ascending or a descending index to the inventory collection on the type field. 2 In the mongo shell, you can create indexes using the db.collection.createIndex() method: db.inventory.createIndex( { type:1}) This index can prevent the above query on type from scanning the whole collection to return the results. To analyze the performance of the query with an index, see Analyze Query Performance (page 114). In addition to optimizing read operations, indexes can support sort operations and allow for a more efficient storage utilization. See db.collection.createIndex() and Indexing Tutorials (page 517) for more information about index creation. Query Selectivity Query selectivity refers to how well the query predicate excludes or filters out documents in a collection. Query selectivity can determine whether or not queries can use indexes effectively or even use indexes at all. More selective queries match a smaller percentage of documents. For instance, an equality match on the unique _id field is highly selective as it can match at most one document. Less selective queries match a larger percentage of documents. Less selective queries cannot use indexes effectively or even at all. For instance, the inequality operators $nin and $ne are not very selective since they often match a large portion of the index. As a result, in many cases, a $nin or $ne query with an index may perform no better than a $nin or $ne query that must scan all documents in a collection. The selectivity of regular expressions depends on the expressions themselves. For details, see regular expres- sion and index use. Covered Query An index covers (page 68) a query when both of the following apply: • all the fields in the query (page 98) are part of an index, and • all the fields returned in the results are in the same index. For example, a collection inventory has the following index on the type and item fields: 2 For single-field indexes, the selection between ascending and descending order is immaterial. For compound indexes, the selection is important. See indexing order (page 489) for more details. 68 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 db.inventory.createIndex( { type:1, item:1}) This index will cover the following operation which queries on the type and item fields and returns only the item field: db.inventory.find( { type: "food", item:/^c/}, { item:1, _id:0} ) For the specified index to cover the query, the projection document must explicitly specify _id: 0 to exclude the _id field from the result since the index does not include the _id field. Performance Because the index contains all fields required by the query, MongoDB can both match the query conditions (page 98) and return the results using only the index. Querying only the index can be much faster than querying documents outside of the index. Index keys are typically smaller than the documents they catalog, and indexes are typically available in RAM or located sequentially on disk. Limitations Restrictions on Indexed Fields An index cannot cover a query if: • any of the indexed fields in any of the documents in the collection includes an array. If an indexed field is an array, the index becomes a multi-key index (page 491) and cannot support a covered query. • any of the indexed fields in the query predicate or returned in the projection are fields in embedded documents. 3 For example, consider a collection users with documents of the following form: { _id:1, user: { login: "tester"}} The collection has the following index: { "user.login": 1 } The { "user.login": 1 } index does not cover the following query: db.users.find( { "user.login": "tester" }, { "user.login": 1, _id: 0 } ) However, the query can use the { "user.login": 1 } index to find matching documents. Restrictions on Sharded Collection An index cannot cover a query on a sharded collection when run against a mongos if the index does not contain the shard key, with the following exception for the _id index: If a query on a sharded collection only specifies a condition on the _id field and returns only the _id field, the _id index can cover the query when run against a mongos even if the _id field is not the shard key. Changed in version 3.0: In previous versions, an index cannot cover (page 68) a query on a sharded collection when run against a mongos. explain To determine whether a query is a covered query, use the db.collection.explain() or the explain() method and review the results. db.collection.explain() provides information on the execution of other operations, such as db.collection.update(). See db.collection.explain() for details. 3 To index fields in embedded documents, use dot notation. 3.2. MongoDB CRUD Concepts 69 MongoDB Documentation, Release 3.0.7 For more information see Measure Index Use (page 529). Query Plans The MongoDB query optimizer processes queries and chooses the most efficient query plan for a query given the available indexes. The query system then uses this query plan each time the query runs. The query optimizer only caches the plans for those query shapes that can have more than one viable plan. The query optimizer occasionally reevaluates query plans as the content of the collection changes to ensure optimal query plans. You can also specify which indexes the optimizer evaluates with Index Filters (page 71). You can use the db.collection.explain() or the cursor.explain() method to view statistics about the query plan for a given query. This information can help as you develop indexing strategies (page 547). db.collection.explain() provides information on the execution of other operations, such as db.collection.update(). See db.collection.explain() for details. Query Optimization To create a new query plan, the query optimizer: 1. runs the query against several candidate indexes in parallel. 2. records the matches in a common results buffer or buffers. • If the candidate plans include only ordered query plans, there is a single common results buffer. • If the candidate plans include only unordered query plans, there is a single common results buffer. • If the candidate plans include both ordered query plans and unordered query plans, there are two common results buffers, one for the ordered plans and the other for the unordered plans. If an index returns a result already returned by another index, the optimizer skips the duplicate match. In the case of the two buffers, both buffers are de-duped. 3. stops the testing of candidate plans and selects an index when one of the following events occur: • An unordered query plan has returned all the matching results; or • An ordered query plan has returned all the matching results; or • An ordered query plan has returned a threshold number of matching results: – Version 2.0: Threshold is the query batch size. The default batch size is 101. – Version 2.2: Threshold is 101. The selected index becomes the index specified in the query plan; future iterations of this query or queries with the same query pattern will use this index. Query pattern refers to query select conditions that differ only in the values, as in the following two queries with the same query pattern: db.inventory.find( { type: 'food'}) db.inventory.find( { type: 'utensil'}) Query Plan Revision As collections change over time, the query optimizer deletes the query plan and re-evaluates after any of the following events: • The collection receives 1,000 write operations. 70 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 • The reIndex rebuilds the index. • You add or drop an index. • The mongod process restarts. Changed in version 2.6: explain() operations no longer read from or write to the query planner cache. Cached Query Plan Interface New in version 2.6. MongoDB provides https://docs.mongodb.org/manual/reference/method/js-plan-cache to view and modify the cached query plans. Index Filters New in version 2.6. Index filters determine which indexes the optimizer evaluates for a query shape. A query shape consists of a combi- nation of query, sort, and projection specifications. If an index filter exists for a given query shape, the optimizer only considers those indexes specified in the filter. When an index filter exists for the query shape, MongoDB ignores the hint(). To see whether MongoDB applied an index filter for a query shape, check the indexFilterSet field of either the db.collection.explain() or the cursor.explain() method. Index filters only affects which indexes the optimizer evaluates; the optimizer may still select the collection scan as the winning plan for a given query shape. Index filters exist for the duration of the server process and do not persist after shutdown. MongoDB also provides a command to manually remove filters. Because index filters overrides the expected behavior of the optimizer as well as the hint() method, use index filters sparingly. See planCacheListFilters, planCacheClearFilters, and planCacheSetFilter. Distributed Queries Read Operations to Sharded Clusters Sharded clusters allow you to partition a data set among a cluster of mongod instances in a way that is nearly trans- parent to the application. For an overview of sharded clusters, see the Sharding (page 661) section of this manual. For a sharded cluster, applications issue operations to one of the mongos instances associated with the cluster. Read operations on sharded clusters are most efficient when directed to a specific shard. Queries to sharded collections should include the collection’s shard key (page 674). When a query includes a shard key, the mongos can use cluster metadata from the config database (page 670) to route the queries to shards. If a query does not include the shard key, the mongos must direct the query to all shards in the cluster. These scatter gather queries can be inefficient. On larger clusters, scatter gather queries are unfeasible for routine operations. For more information on read operations in sharded clusters, see the Sharded Cluster Query Routing (page 678) and Shard Keys (page 674) sections. 3.2. MongoDB CRUD Concepts 71 MongoDB Documentation, Release 3.0.7 72 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 3.2. MongoDB CRUD Concepts 73 MongoDB Documentation, Release 3.0.7 74 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 Read Operations to Replica Sets Replica sets use read preferences to determine where and how to route read operations to members of the replica set. By default, MongoDB always reads data from a replica set’s primary. You can modify that behavior by changing the read preference mode (page 657). You can configure the read preference mode (page 657) on a per-connection or per-operation basis to allow reads from secondaries to: • reduce latency in multi-data-center deployments, • improve read throughput by distributing high read-volumes (relative to write volume), • for backup operations, and/or • to allow reads during failover (page 580) situations. Read operations from secondary members of replica sets are not guaranteed to reflect the current state of the primary, and the state of secondaries trails the primary by some amount of time. 4 For more information on read preference or on the read preference modes, see Read Preference (page 588) and Read Preference Modes (page 657). 3.2.2 Write Operations The following documents describe write operations: 4 In some circumstances, two nodes in a replica set may transiently believe that they are the primary, but at most, one of them will be able to complete writes with {w: majority} write concern (page 133). The node that can complete {w: majority} (page 133) writes is the current primary, and the other node is a former primary that has not yet recognized its demotion, typically due to a network partition. When this occurs, clients that connect to the former primary may observe stale data despite having requested read preference primary (page 657). 3.2. MongoDB CRUD Concepts 75 MongoDB Documentation, Release 3.0.7 Write Operations Overview (page 76) Provides an overview of MongoDB’s data insertion and modification opera- tions, including aspects of the syntax, and behavior. Write Concern (page 80) Describes the kind of guarantee MongoDB provides when reporting on the success of a write operation. Atomicity and Transactions (page 82) Describes write operation atomicity in MongoDB. Distributed Write Operations (page 84) Describes how MongoDB directs write operations on sharded clusters and replica sets and the performance characteristics of these operations. Write Operation Performance (page 88) Introduces the performance constraints and factors for writing data to Mon- goDB deployments. Bulk Write Operations (page 89) Provides an overview of MongoDB’s bulk write operations. Storage (page 91) Introduces the storage allocation strategies available for MongoDB collections. Write Operations Overview A write operation is any operation that creates or modifies data in the MongoDB instance. In MongoDB, write operations target a single collection. All write operations in MongoDB are atomic on the level of a single document. There are three classes of write operations in MongoDB: insert (page 76), update (page 77), and remove (page 79). Insert operations add new data to a collection. Update operations modify existing data, and remove operations delete data from a collection. No insert, update, or remove can affect more than one document atomically. For the update and remove operations, you can specify criteria, or conditions, that identify the documents to update or remove. These operations use the same query syntax to specify the criteria as read operations (page 62). MongoDB allows applications to determine the acceptable level of acknowledgement required of write operations. See Write Concern (page 80) for more information. Insert In MongoDB, the db.collection.insert() method adds new documents to a collection. The following diagram highlights the components of a MongoDB insert operation: The following diagram shows the same query in SQL: Example 76 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 The following operation inserts a new document into the users collection. The new document has four fields name, age, and status, and an _id field. MongoDB always adds the _id field to the new document if that field does not exist. db.users.insert( { name: "sue", age: 26, status: "A" } ) For more information and examples, see db.collection.insert(). Insert Behavior If you add a new document without the _id field, the client library or the mongod instance adds an _id field and populates the field with a unique ObjectId. If you specify the _id field, the value must be unique within the collection. For operations with write concern (page 80), if you try to create a document with a duplicate _id value, mongod returns a duplicate key exception. Other Methods to Add Documents You can also add new documents to a collection using methods that have an upsert (page 78) option. If the option is set to true, these methods will either modify existing documents or add a new document when no matching documents exist for the query. For more information, see Update Behavior with the upsert Option (page 78). Update In MongoDB, the db.collection.update() method modifies existing documents in a collection. The db.collection.update() method can accept query criteria to determine which documents to update as well as an options document that affects its behavior, such as the multi option to update multiple documents. Operations performed by an update are atomic within a single document. For example, you can safely use the $inc and $mul operators to modify frequently-changed fields in concurrent applications. The following diagram highlights the components of a MongoDB update operation: The following diagram shows the same query in SQL: Example db.users.update( { age: { $gt: 18}}, { $set: { status: "A"}}, { multi: true } ) 3.2. MongoDB CRUD Concepts 77 MongoDB Documentation, Release 3.0.7 This update operation on the users collection sets the status field to A for the documents that match the criteria of age greater than 18. For more information, see db.collection.update() and update() Examples. Default Update Behavior By default, the db.collection.update() method updates a single document. However, with the multi option, update() can update all documents in a collection that match a query. The db.collection.update() method either updates specific fields in the existing document or replaces the document. See db.collection.update() for details as well as examples. When performing update operations that increase the document size beyond the allocated space for that document, the update operation relocates the document on disk. MongoDB preserves the order of the document fields following write operations except for the following cases: • The _id field is always the first field in the document. • Updates that include renaming of field names may result in the reordering of fields in the document. Changed in version 2.6: Starting in version 2.6, MongoDB actively attempts to preserve the field order in a document. Before version 2.6, MongoDB did not actively preserve the order of the fields in a document. Update Behavior with the upsert Option If the update() method includes upsert: true and no documents match the query portion of the update operation, then the update operation creates a new document. If there are matching documents, then the update operation with the upsert: true modifies the matching document or documents. By specifying upsert: true, applications can indicate, in a single operation, that if no matching documents are found for the update, an insert should be performed. See update() for details on performing an upsert. Changed in version 2.6: In 2.6, the new Bulk() methods and the underlying update command allow you to perform many updates with upsert: true operations in a single call. If you create documents using the upsert option to update() consider using a a unique index to prevent duplicated operations. 78 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 Remove In MongoDB, the db.collection.remove() method deletes documents from a collection. The db.collection.remove() method accepts a query criteria to determine which documents to remove. The following diagram highlights the components of a MongoDB remove operation: The following diagram shows the same query in SQL: Example db.users.remove( { status: "D"} ) This delete operation on the users collection removes all documents that match the criteria of status equal to D. For more information, see db.collection.remove() method and Remove Documents (page 108). Remove Behavior By default, db.collection.remove() method removes all documents that match its query. However, the method can accept a flag to limit the delete operation to a single document. Isolation of Write Operations The modification of a single document is always atomic, even if the write operation modifies multiple embedded documents within that document. No other operations are atomic. If a write operation modifies multiple documents, the operation as a whole is not atomic, and other operations may in- terleave. You can, however, attempt to isolate a write operation that affects multiple documents using the isolation operator. For more information Atomicity and Transactions (page 82). Additional Methods The db.collection.save() method can either update an existing document or insert a document if the docu- ment cannot be found by the _id field. See db.collection.save() for more information and examples. MongoDB also provides methods to perform write operations in bulk. See Bulk() for more information. 3.2. MongoDB CRUD Concepts 79 MongoDB Documentation, Release 3.0.7 Write Concern Write concern describes the guarantee that MongoDB provides when reporting on the success of a write operation. The strength of the write concerns determine the level of guarantee. When inserts, updates and deletes have a weak write concern, write operations return quickly. In some failure cases, write operations issued with weak write concerns may not persist. With stronger write concerns, clients wait after sending a write operation for MongoDB to confirm the write operations. MongoDB provides different levels of write concern to better address the specific needs of applications. Clients may adjust write concern to ensure that the most important operations persist successfully to an entire MongoDB deployment. For other less critical operations, clients can adjust the write concern to ensure faster performance rather than ensure persistence to the entire deployment. Changed in version 2.6: A new protocol for write operations (page 863) integrates write concern with the write operations. For details on write concern configurations, see Write Concern Reference (page 133). Considerations Default Write Concern The mongo shell and the MongoDB drivers use Acknowledged (page 80) as the default write concern. See Acknowledged (page 80) for more information, including when this write concern became the default. Timeouts Clients can set a wtimeout (page 134) value as part of a replica acknowledged (page 82) write concern. If the write concern is not satisfied in the specified interval, the operation returns an error, even if the write concern will eventually succeed. MongoDB does not “rollback” or undo modifications made before the wtimeout interval expired. Write Concern Levels MongoDB has the following levels of conceptual write concern, listed from weakest to strongest: Unacknowledged With an unacknowledged write concern, MongoDB does not acknowledge the receipt of write operations. Unacknowledged is similar to errors ignored; however, drivers will attempt to receive and handle network errors when possible. The driver’s ability to detect network errors depends on the system’s networking configuration. Before the releases outlined in Default Write Concern Change (page 936), this was the default write concern. Acknowledged With a receipt acknowledged write concern, the mongod confirms that it received the write oper- ation and applied the change to the in-memory view of data. Acknowledged write concern allows clients to catch network, duplicate key, and other errors. MongoDB uses the acknowledged write concern by default starting in the driver releases outlined in Releases (page 936). Changed in version 2.6: The mongo shell write methods now incorporates the write concern (page 80) in the write methods and provide the default write concern whether run interactively or in a script. See Write Method Acknowl- edgements (page 869) for details. Acknowledged write concern does not confirm that the write operation has persisted to the disk system. 80 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 3.2. MongoDB CRUD Concepts 81 MongoDB Documentation, Release 3.0.7 Journaled With a journaled write concern, the MongoDB acknowledges the write operation only after committing the data to the journal. This write concern ensures that MongoDB can recover the data following a shutdown or power interruption. You must have journaling enabled to use this write concern. With a journaled write concern, write operations must wait for the next journal commit. To reduce latency for these operations, MongoDB also increases the frequency that it commits operations to the journal. See storage.mmapv1.journal.commitIntervalMs for more information. Note: Requiring journaled write concern in a replica set only requires a journal commit of the write operation to the primary of the set regardless of the level of replica acknowledged write concern. Replica Acknowledged Replica sets present additional considerations with regards to write concern. The default write concern only requires acknowledgement from the primary. With replica acknowledged write concern, you can guarantee that the write operation propagates to additional members of the replica set. See Write Concern for Replica Sets (page 586) for more information. Note: Requiring journaled write concern in a replica set only requires a journal commit of the write operation to the primary of the set regardless of the level of replica acknowledged write concern. See also: Write Concern Reference (page 133) Atomicity and Transactions In MongoDB, a write operation is atomic on the level of a single document, even if the operation modifies multiple embedded documents within a single document. 82 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 3.2. MongoDB CRUD Concepts 83 MongoDB Documentation, Release 3.0.7 When a single write operation modifies multiple documents, the modification of each document is atomic, but the operation as a whole is not atomic and other operations may interleave. However, you can isolate a single write operation that affects multiple documents using the $isolated operator. $isolated Operator Using the $isolated operator, a write operation that affect multiple documents can prevent other processes from interleaving once the write operation modifies the first document. This ensures that no client sees the changes until the write operation completes or errors out. Isolated write operation does not provide “all-or-nothing” atomicity. That is, an error during the write operation does not roll back all its changes that preceded the error. The $isolated operator does not work on sharded clusters. For an example of an update operation that uses the $isolated operator, see $isolated. For an example of a remove operation that uses the $isolated operator, see isolate-remove-operations. Transaction-Like Semantics Since a single document can contain multiple embedded documents, single-document atomicity is sufficient for many practical use cases. For cases where a sequence of write operations must operate as if in a single transaction, you can implement a two-phase commit (page 119) in your application. However, two-phase commits can only offer transaction-like semantics. Using two-phase commit ensures data consis- tency, but it is possible for applications to return intermediate data during the two-phase commit or rollback. For more information on two-phase commit and rollback, see Perform Two Phase Commits (page 119). Concurrency Control Concurrency control allows multiple applications to run concurrently without causing data inconsistency or conflicts. An approach may be to create a unique index (page 504) on a field (or fields) that should have only unique values (or unique combination of values) prevents duplicate insertions or updates that result in duplicate values. For examples of use cases, see update() and Unique Index and findAndModify() and Unique Index. Another approach is to specify the expected current value of a field in the query predicate for the write operations. For an example, see Update if Current (page 125). The two-phase commit pattern provides a variation where the query predicate includes the application identifier (page 123) as well as the expected state of the data in the write operation. Distributed Write Operations Write Operations on Sharded Clusters For sharded collections in a sharded cluster, the mongos directs write operations from applications to the shards that are responsible for the specific portion of the data set. The mongos uses the cluster metadata from the config database (page 670) to route the write operation to the appropriate shards. MongoDB partitions data in a sharded collection into ranges based on the values of the shard key. Then, MongoDB distributes these chunks to shards. The shard key determines the distribution of chunks to shards. This can affect the performance of write operations in the cluster. 84 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 3.2. MongoDB CRUD Concepts 85 MongoDB Documentation, Release 3.0.7 Important: Update operations that affect a single document must include the shard key or the _id field. Updates that affect multiple documents are more efficient in some situations if they have the shard key, but can be broadcast to all shards. If the value of the shard key increases or decreases with every insert, all insert operations target a single shard. As a result, the capacity of a single shard becomes the limit for the insert capacity of the sharded cluster. For more information, see Sharded Cluster Tutorials (page 690) and Bulk Write Operations (page 89). Write Operations on Replica Sets In replica sets, all write operations go to the set’s primary, which applies the write operation then records the oper- ations on the primary’s operation log or oplog. The oplog is a reproducible sequence of operations to the data set. Secondary members of the set are continuously replicating the oplog and applying the operations to themselves in an asynchronous process. Large volumes of write operations, particularly bulk operations, may create situations where the secondary members have difficulty applying the replicating operations from the primary at a sufficient rate: this can cause the secondary’s state to fall behind that of the primary. Secondaries that are significantly behind the primary present problems for 86 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 normal operation of the replica set, particularly failover (page 580) in the form of rollbacks (page 584) as well as general read consistency (page 585). To help avoid this issue, you can customize the write concern (page 80) to return confirmation of the write operation to another member 5 of the replica set every 100 or 1,000 operations. This provides an opportunity for secondaries to catch up with the primary. Write concern can slow the overall progress of write operations but ensure that the secondaries can maintain a largely current state with respect to the primary. For more information on replica sets and write operations, see Replica Acknowledged (page 82), Oplog Size (page 593), and Change the Size of the Oplog (page 628). 5 Intermittently issuing a write concern with a w value of 2 or majority will slow the throughput of write traffic; however, this practice will allow the secondaries to remain current with the state of the primary. Changed in version 2.6: In Master/Slave (page 596) deployments, MongoDB treats w: "majority" as equivalent to w: 1. In earlier versions of MongoDB, w: "majority" produces an error in master/slave (page 596) deployments. 3.2. MongoDB CRUD Concepts 87 MongoDB Documentation, Release 3.0.7 Write Operation Performance Indexes After every insert, update, or delete operation, MongoDB must update every index associated with the collection in addition to the data itself. Therefore, every index on a collection adds some amount of overhead for the performance of write operations. 6 In general, the performance gains that indexes provide for read operations are worth the insertion penalty. However, in order to optimize write performance when possible, be careful when creating new indexes and evaluate the existing indexes to ensure that your queries actually use these indexes. For indexes and queries, see Query Optimization (page 67). For more information on indexes, see Indexes (page 481) and Indexing Strategies (page 547). Document Growth and the MMAPv1 Storage Engine Some update operations can increase the size of the document; for instance, if an update adds a new field to the document. For the MMAPv1 storage engine, if an update operation causes a document to exceed the currently allocated record size, MongoDB relocates the document on disk with enough contiguous space to hold the document. Updates that require relocations take longer than updates that do not, particularly if the collection has indexes. If a collection has indexes, MongoDB must update all index entries. Thus, for a collection with many indexes, the move will impact the write throughput. Changed in version 3.0.0: By default, MongoDB uses Power of 2 Sized Allocations (page 93) to add padding automat- ically (page 93) for the MMAPv1 storage engine. The Power of 2 Sized Allocations (page 93) ensures that MongoDB allocates document space in sizes that are powers of 2, which helps ensure that MongoDB can efficiently reuse free space created by document deletion or relocation as well as reduce the occurrences of reallocations in many cases. Although Power of 2 Sized Allocations (page 93) minimizes the occurrence of re-allocation, it does not eliminate document re-allocation. See Storage (page 91) for more information. Storage Performance Hardware The capability of the storage system creates some important physical limits for the performance of Mon- goDB’s write operations. Many unique factors related to the storage system of the drive affect write performance, including random access patterns, disk caches, disk readahead and RAID configurations. Solid state drives (SSDs) can outperform spinning hard disks (HDDs) by 100 times or more for random workloads. See Production Notes (page 201) for recommendations regarding additional hardware and configuration options. Journaling MongoDB uses write ahead logging to an on-disk journal to guarantee write operation (page 75) dura- bility and to provide crash resiliency. Before applying a change to the data files, MongoDB writes the change operation to the journal. 6 For inserts and updates to un-indexed fields, the overhead for sparse indexes (page 506) is less than for non-sparse indexes. Also for non-sparse indexes, updates that do not change the record size have less indexing overhead. 88 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 While the durability assurance provided by the journal typically outweigh the performance costs of the additional write operations, consider the following interactions between the journal and performance: • if the journal and the data file reside on the same block device, the data files and the journal may have to contend for a finite number of available write operations. Moving the journal to a separate device may increase the capacity for write operations. • if applications specify write concern (page 80) that includes journaled (page 82), mongod will decrease the duration between journal commits, which can increases the overall write load. • the duration between journal commits is configurable using the commitIntervalMs run-time option. De- creasing the period between journal commits will increase the number of write operations, which can limit MongoDB’s capacity for write operations. Increasing the amount of time between commits may decrease the total number of write operation, but also increases the chance that the journal will not record a write operation in the event of a failure. For additional information on journaling, see Journaling Mechanics (page 314). Additional Resources • MongoDB Performance Evaluation and Tuning Consulting Package7 Bulk Write Operations Overview MongoDB provides clients the ability to perform write operations in bulk. Bulk write operations affect a single collection. MongoDB allows applications to determine the acceptable level of acknowledgement required for bulk write operations. New Bulk methods provide the ability to perform bulk insert, update, and remove operations. MongoDB also supports bulk insert through passing an array of documents to the db.collection.insert() method. Changed in version 2.6: Previous versions of MongoDB provided the ability for bulk inserts only. With previous versions, clients could perform bulk inserts by passing an array of documents to the db.collection.insert()8 method. To see the documentation for earlier versions, see Bulk Inserts9. Ordered vs Unordered Operations Bulk write operations can be either ordered or unordered. With an ordered list of operations, MongoDB executes the operations serially. If an error occurs during the processing of one of the write operations, MongoDB will return without processing any remaining write operations in the list. With an unordered list of operations, MongoDB can execute the operations in parallel. If an error occurs during the processing of one of the write operations, MongoDB will continue to process remaining write operations in the list. Executing an ordered list of operations on a sharded collection will generally be slower than executing an unordered list since with an ordered list, each operation must wait for the previous operation to finish. 7https://www.mongodb.com/products/consulting?jmp=docs#performance_evaluation 8https://docs.mongodb.org/v2.4/core/bulk-inserts 9https://docs.mongodb.org/v2.4/core/bulk-inserts 3.2. MongoDB CRUD Concepts 89 MongoDB Documentation, Release 3.0.7 Bulk Methods To use the Bulk() methods: 1. Initialize a list of operations using either db.collection.initializeUnorderedBulkOp() or db.collection.initializeOrderedBulkOp(). 2. Add write operations to the list using the following methods: • Bulk.insert() • Bulk.find() • Bulk.find.upsert() • Bulk.find.update() • Bulk.find.updateOne() • Bulk.find.replaceOne() • Bulk.find.remove() • Bulk.find.removeOne() 3. To execute the list of operations, use the Bulk.execute() method. You can specify the write concern for the list in the Bulk.execute() method. Once executed, you cannot re-execute the list without reinitializing. For example, var bulk= db.items.initializeUnorderedBulkOp(); bulk.insert( { _id:1, item: "abc123", status: "A", soldQty: 5000}); bulk.insert( { _id:2, item: "abc456", status: "A", soldQty: 150}); bulk.insert( { _id:3, item: "abc789", status: "P", soldQty:0}); bulk.execute( { w: "majority", wtimeout: 5000}); For more examples, refer to the reference page for each https://docs.mongodb.org/manual/reference/method/js-bulk method. For information and examples on performing bulk insert using the db.collection.insert(), see db.collection.insert(). See also: New Write Operation Protocol (page 863) Bulk Execution Mechanics When executing an ordered list of operations, MongoDB groups adjacent operations by the operation type. When executing an unordered list of operations, MongoDB groups and may also reorder the operations to increase performance. As such, when performing unordered bulk operations, applications should not depend on the ordering. Each group of operations can have at most 1000 operations. If a group exceeds this limit, MongoDB will divide the group into smaller groups of 1000 or less. For example, if the bulk operations list consists of 2000 insert operations, MongoDB creates 2 groups, each with 1000 operations. The sizes and grouping mechanics are internal performance details and are subject to change in future versions. To see how the operations are grouped for a bulk operation execution, call Bulk.getOperations() after the execution. For more information, see Bulk.execute(). 90 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 Strategies for Bulk Inserts to a Sharded Collection Large bulk insert operations, including initial data inserts or routine data import, can affect sharded cluster perfor- mance. For bulk inserts, consider the following strategies: Pre-Split the Collection If the sharded collection is empty, then the collection has only one initial chunk, which resides on a single shard. MongoDB must then take time to receive data, create splits, and distribute the split chunks to the available shards. To avoid this performance cost, you can pre-split the collection, as described in Split Chunks in a Sharded Cluster (page 723). Insert to Multiple mongos To parallelize import processes, send bulk insert or insert operations to more than one mongos instance. For empty collections, first pre-split the collection as described in Split Chunks in a Sharded Cluster (page 723). Avoid Monotonic Throttling If your shard key increases monotonically during an insert, then all inserted data goes to the last chunk in the collection, which will always end up on a single shard. Therefore, the insert capacity of the cluster will never exceed the insert capacity of that single shard. If your insert volume is larger than what a single shard can process, and if you cannot avoid a monotonically increasing shard key, then consider the following modifications to your application: • Reverse the binary bits of the shard key. This preserves the information and avoids correlating insertion order with increasing sequence of values. • Swap the first and last 16-bit words to “shuffle” the inserts. Example The following example, in C++, swaps the leading and trailing 16-bit word of BSON ObjectIds generated so they are no longer monotonically increasing. using namespace mongo; OID make_an_id() { OID x= OID::gen(); const unsigned char *p= x.getData(); swap( (unsigned short&) p[0], (unsigned short&) p[10] ); return x; } void foo() { // create an object BSONObj o= BSON("_id"<< make_an_id()<<"x"<<3<<"name"<<"jane"); // now we may insert o into a sharded collection } See also: Shard Keys (page 674) for information on choosing a sharded key. Also see Shard Key Internals (page 674) (in particular, Choosing a Shard Key (page 694)). Storage New in version 3.0: MongoDB adds support for additional storage engines. MongoDB’s original storage engine, known as mmapv1 remains the default in 3.0, but the new wiredTiger engine is available and can offer additional flexibility and improved throughput for many workloads. 3.2. MongoDB CRUD Concepts 91 MongoDB Documentation, Release 3.0.7 Data Model MongoDB stores data in the form of BSON documents, which are rich mappings of keys, or field names, to values. BSON supports a rich collection of types, and fields in BSON documents may hold arrays of values or embedded documents. All documents in MongoDB must be less than 16MB, which is the BSON document size. All documents are part of a collection, which are a logical groupings of documents in a MongoDB database. The documents in a collection share a set of indexes, and typically these documents share common fields and structure. In MongoDB the database construct is a group of related collections. Each database has a distinct set of data files and can contain a large number of collections. A single MongoDB deployment may have many databases. WiredTiger Storage Engine New in version 3.0. WiredTiger is a storage engine that is optionally available in the 64-bit build of MongoDB 3.0. It excels at read and insert workloads as well as more complex update workloads. Document Level Locking With WiredTiger, all write operations happen within the context of a document level lock. As a result, multiple clients can modify more than one document in a single collection at the same time. With this very granular concurrency control, MongoDB can more effectively support workloads with read, write and updates as well as high-throughput concurrent workloads. Journal WiredTiger uses a write-ahead transaction log in combination with checkpoints to ensure data persistence. With WiredTiger, MongoDB will commit a checkpoint to disk every 60 seconds or when there are 2 gigabytes of data to write. Between and during checkpoints the data files are always valid. The WiredTiger journal persists all data modifications between checkpoints. If MongoDB exits between checkpoints, it uses the journal to replay all data modified since the last checkpoint. By default, the WiredTiger journal is compressed using the snappy compression library. To specify an alternate compression algorithm or no compression, use the storage.wiredTiger.engineConfig.journalCompressor setting. You can disable journaling by setting storage.journal.enabled to false, which can reduce the overhead of maintaining the journal. For standalone instances, not using the journal means that you will lose some data modifica- tions when MongoDB exits unexpectedly between checkpoints. For members of replica sets, the replication process may provide sufficient durability guarantees. Compression With WiredTiger, MongoDB supports compression for all collections and indexes. Compression min- imizes storage use at the expense of additional CPU. By default, WiredTiger uses block compression with the snappy compression library for all collections and prefix compression for all indexes. For collections, block compression with zlib is also available. To specify an alternate compression algorithm or no compression, use the storage.wiredTiger.collectionConfig.blockCompressor setting. For indexes, to disable prefix compression, use the storage.wiredTiger.indexConfig.prefixCompression setting. Compression settings are also configurable on a per-collection and per-index basis during collection and index creation. See create-collection-storage-engine-options and db.collection.createIndex() storageEngine option. For most workloads, the default compression settings balance storage efficiency and processing requirements. The WiredTiger journal is also compressed by default. For information on journal compression, see Journal (page 92). 92 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 See also: http://wiredtiger.com MMAPv1 Storage Engine MMAPv1 is MongoDB’s original storage engine based on memory mapped files. It excels at workloads with high volume inserts, reads, and in-place updates. MMAPv1 is the default storage engine in MongoDB 3.0 and all previous versions. Journal In order to ensure that all modifications to a MongoDB data set are durably written to disk, MongoDB records all modifications to a journal that it writes to disk more frequently than it writes the data files. The journal allows MongoDB to successfully recover data from data files after a mongod instance exits without flushing all changes. See Journaling Mechanics (page 314) for more information about the journal in MongoDB. Record Storage Characteristics All records are contiguously located on disk, and when a document becomes larger than the allocated record, MongoDB must allocate a new record. New allocations require MongoDB to move a document and update all indexes that refer to the document, which takes more time than in-place updates and leads to storage fragmentation. Changed in version 3.0.0. By default, MongoDB uses Power of 2 Sized Allocations (page 93) so that every document in MongoDB is stored in a record which contains the document itself and extra space, or padding. Padding allows the document to grow as the result of updates while minimizing the likelihood of reallocations. Record Allocation Strategies MongoDB supports multiple record allocation strategies that determine how mongod adds padding to a document when creating a record. Because documents in MongoDB may grow after insertion and all records are contiguous on disk, the padding can reduce the need to relocate documents on disk following updates. Relocations are less efficient than in-place updates and can lead to storage fragmentation. As a result, all padding strategies trade additional space for increased efficiency and decreased fragmentation. Different allocation strategies support different kinds of workloads: the power of 2 allocations (page 93) are more efficient for insert/update/delete workloads; while exact fit allocations (page 94) is ideal for collections without update and delete workloads. Power of 2 Sized Allocations Changed in version 3.0.0. MongoDB 3.0 uses the power of 2 sizes allocation as the default record allocation strategy for MMAPv1. With the power of 2 sizes allocation strategy, each record has a size in bytes that is a power of 2 (e.g. 32, 64, 128, 256, 512 ... 2MB). For documents larger than 2MB, the allocation is rounded up to the nearest multiple of 2MB. The power of 2 sizes allocation strategy has the following key properties: • Can efficiently reuse freed records to reduce fragmentation. Quantizing record allocation sizes into a fixed set of sizes increases the probability that an insert will fit into the free space created by an earlier document deletion or relocation. • Can reduce moves. The added padding space gives a document room to grow without requiring a move. In addition to saving the cost of moving, this results in less updates to indexes. Although the power of 2 sizes strategy can minimize moves, it does not eliminate them entirely. 3.2. MongoDB CRUD Concepts 93 MongoDB Documentation, Release 3.0.7 No Padding Allocation Strategy Changed in version 3.0.0. For collections whose workloads do not change the document sizes, such as workloads that consist of insert- only operations or update operations that do not increase document size (such as incrementing a counter), you can disable the power of 2 allocation (page 93) using the collMod command with the noPadding flag or the db.createCollection() method with the noPadding option. Prior to version 3.0.0, MongoDB used an allocation strategy that included a dynamically calculated padding as a factor of the document size. Capped Collections Capped collections are fixed-size collections that support high-throughput operations that store records in insertion order. Capped collections work like circular buffers: once a collection fills its allocated space, it makes room for new documents by overwriting the oldest documents in the collection. See Capped Collections (page 213) for more information. Additional Resources • Blog Post: New Compression Options in MongoDB 3.010 3.3 MongoDB CRUD Tutorials The following tutorials provide instructions for querying and modifying data. For a higher-level overview of these operations, see MongoDB CRUD Operations (page 59). Insert Documents (page 95) Insert new documents into a collection. Query Documents (page 98) Find documents in a collection using search criteria. Modify Documents (page 104) Modify documents in a collection Remove Documents (page 108) Remove documents from a collection. Limit Fields to Return from a Query (page 109) Limit which fields are returned by a query. Limit Number of Elements in an Array after an Update (page 112) Use $push with modifiers to sort and maintain an array of fixed size. Iterate a Cursor in the mongo Shell (page 113) Access documents returned by a find query by iterating the cursor, either manually or using the iterator index. Analyze Query Performance (page 114) Use query introspection (i.e. explain) to analyze the efficiency of queries and determine how a query uses available indexes. Perform Two Phase Commits (page 119) Use two-phase commits when writing data to multiple documents. Update Document if Current (page 125) Update a document only if it has not changed since it was last read. Create Tailable Cursor (page 126) Create tailable cursors for use in capped collections with high numbers of write operations for which an index would be too expensive. Create an Auto-Incrementing Sequence Field (page 129) Describes how to create an incrementing sequence num- ber for the _id field using a Counters Collection or an Optimistic Loop. 10https://www.mongodb.com/blog/post/new-compression-options-mongodb-30?jmp=docs 94 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 3.3.1 Insert Documents In MongoDB, the db.collection.insert() method adds new documents into a collection. Insert a Document Step 1: Insert a document into a collection. Insert a document into a collection named inventory. The operation will create the collection if the collection does not currently exist. db.inventory.insert( { item: "ABC1", details:{ model: "14Q3", manufacturer: "XYZ Company" }, stock: [ { size: "S", qty: 25 }, { size: "M", qty: 50}], category: "clothing" } ) The operation returns a WriteResult object with the status of the operation. A successful insert of the document returns the following object: WriteResult({ "nInserted":1}) The nInserted field specifies the number of documents inserted. If the operation encounters an error, the WriteResult object will contain the error information. Step 2: Review the inserted document. If the insert operation is successful, verify the insertion by querying the collection. db.inventory.find() The document you inserted should return. { "_id": ObjectId("53d98f133bb604791249ca99"), "item": "ABC1", "details":{ "model": "14Q3", "manufacturer": "XYZ Company"}, "stock":[{ "size": "S", "qty": 25},{ "size": "M", "qty": 50}], "category": "clothing"} The returned document shows that MongoDB added an _id field to the document. If a client inserts a document that does not contain the _id field, MongoDB adds the field with the value set to a generated ObjectId11. The ObjectId12 values in your documents will differ from the ones shown. Insert an Array of Documents You can pass an array of documents to the db.collection.insert() method to insert multiple documents. 11https://docs.mongodb.org/manual/reference/object-id 12https://docs.mongodb.org/manual/reference/object-id 3.3. MongoDB CRUD Tutorials 95 MongoDB Documentation, Release 3.0.7 Step 1: Create an array of documents. Define a variable mydocuments that holds an array of documents to insert. var mydocuments= [ { item: "ABC2", details: { model: "14Q3", manufacturer: "M1 Corporation"}, stock: [ { size: "M", qty: 50}], category: "clothing" }, { item: "MNO2", details: { model: "14Q3", manufacturer: "ABC Company"}, stock: [ { size: "S", qty:5 }, { size: "M", qty:5 }, { size: "L", qty:1}], category: "clothing" }, { item: "IJK2", details: { model: "14Q2", manufacturer: "M5 Corporation"}, stock: [ { size: "S", qty:5 }, { size: "L", qty:1}], category: "houseware" } ]; Step 2: Insert the documents. Pass the mydocuments array to the db.collection.insert() to perform a bulk insert. db.inventory.insert( mydocuments ); The method returns a BulkWriteResult object with the status of the operation. A successful insert of the docu- ments returns the following object: BulkWriteResult({ "writeErrors":[], "writeConcernErrors":[], "nInserted":3, "nUpserted":0, "nMatched":0, "nModified":0, "nRemoved":0, "upserted":[] }) The nInserted field specifies the number of documents inserted. If the operation encounters an error, the BulkWriteResult object will contain information regarding the error. The inserted documents will each have an _id field added by MongoDB. Insert Multiple Documents with Bulk New in version 2.6. 96 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 MongoDB provides a Bulk() API that you can use to perform multiple write operations in bulk. The following sequence of operations describes how you would use the Bulk() API to insert a group of documents into a MongoDB collection. Step 1: Initialize a Bulk operations builder. Initialize a Bulk operations builder for the collection inventory. var bulk= db.inventory.initializeUnorderedBulkOp(); The operation returns an unordered operations builder which maintains a list of operations to perform. Unordered operations means that MongoDB can execute in parallel as well as in nondeterministic order. If an error occurs during the processing of one of the write operations, MongoDB will continue to process remaining write operations in the list. You can also initialize an ordered operations builder; see db.collection.initializeOrderedBulkOp() for details. Step 2: Add insert operations to the bulk object. Add two insert operations to the bulk object using the Bulk.insert() method. bulk.insert( { item: "BE10", details: { model: "14Q2", manufacturer: "XYZ Company"}, stock: [ { size: "L", qty:5}], category: "clothing" } ); bulk.insert( { item: "ZYT1", details: { model: "14Q1", manufacturer: "ABC Company"}, stock: [ { size: "S", qty:5 }, { size: "M", qty:5}], category: "houseware" } ); Step 3: Execute the bulk operation. Call the execute() method on the bulk object to execute the operations in its list. bulk.execute(); The method returns a BulkWriteResult object with the status of the operation. A successful insert of the docu- ments returns the following object: BulkWriteResult({ "writeErrors":[], "writeConcernErrors":[], "nInserted":2, "nUpserted":0, "nMatched":0, "nModified":0, 3.3. MongoDB CRUD Tutorials 97 MongoDB Documentation, Release 3.0.7 "nRemoved":0, "upserted":[] }) The nInserted field specifies the number of documents inserted. If the operation encounters an error, the BulkWriteResult object will contain information regarding the error. Additional Examples and Methods For more examples, see db.collection.insert(). The db.collection.update() method, the db.collection.findAndModify(), and the db.collection.save() method can also add new documents. See the individual reference pages for the methods for more information and examples. 3.3.2 Query Documents In MongoDB, the db.collection.find() method retrieves documents from a collection. 13 The db.collection.find() method returns a cursor (page 66) to the retrieved documents. This tutorial provides examples of read operations using the db.collection.find() method in the mongo shell. In these examples, the retrieved documents contain all their fields. To restrict the fields to return in the retrieved documents, see Limit Fields to Return from a Query (page 109). Select All Documents in a Collection An empty query document ({}) selects all documents in the collection: db.inventory.find( {} ) Not specifying a query document to the find() is equivalent to specifying an empty query document. Therefore the following operation is equivalent to the previous operation: db.inventory.find() Specify Equality Condition To specify equality condition, use the query document { : } to select all documents that contain the with the specified . The following example retrieves from the inventory collection all documents where the type field has the value snacks: db.inventory.find( { type: "snacks"}) Specify Conditions Using Query Operators A query document can use the query operators to specify conditions in a MongoDB query. The following example selects all documents in the inventory collection where the value of the type field is either ’food’ or ’snacks’: 13 The db.collection.findOne() method also performs a read operation to return a single document. Internally, the db.collection.findOne() method is the db.collection.find() method with a limit of 1. 98 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 db.inventory.find( { type: { $in:[ 'food', 'snacks']}}) Although you can express this query using the $or operator, use the $in operator rather than the $or operator when performing equality checks on the same field. Refer to the https://docs.mongodb.org/manual/reference/operator/query document for the complete list of query operators. Specify AND Conditions A compound query can specify conditions for more than one field in the collection’s documents. Implicitly, a logical AND conjunction connects the clauses of a compound query so that the query selects the documents in the collection that match all the conditions. In the following example, the query document specifies an equality match on the field type and a less than ($lt) comparison match on the field price: db.inventory.find( { type: 'food', price: { $lt: 9.95}}) This query selects all documents where the type field has the value ’food’ and the value of the price field is less than 9.95. See comparison operators for other comparison operators. Specify OR Conditions Using the $or operator, you can specify a compound query that joins each clause with a logical OR conjunction so that the query selects the documents in the collection that match at least one condition. In the following example, the query document selects all documents in the collection where the field qty has a value greater than ($gt) 100 or the value of the price field is less than ($lt) 9.95: db.inventory.find( { $or: [ { qty: { $gt: 100 } }, { price: { $lt: 9.95}}] } ) Specify AND as well as OR Conditions With additional clauses, you can specify precise conditions for matching documents. In the following example, the compound query document selects all documents in the collection where the value of the type field is ’food’ and either the qty has a value greater than ($gt) 100 or the value of the price field is less than ($lt) 9.95: db.inventory.find( { type: 'food', $or: [ { qty: { $gt: 100 } }, { price: { $lt: 9.95}}] } ) Embedded Documents When the field holds an embedded document, a query can either specify an exact match on the embedded document or specify a match by individual fields in the embedded document using the dot notation. 3.3. MongoDB CRUD Tutorials 99 MongoDB Documentation, Release 3.0.7 Exact Match on the Embedded Document To specify an equality match on the whole embedded document, use the query document { : } where is the document to match. Equality matches on an embedded document require an exact match of the specified , including the field order. In the following example, the query matches all documents where the value of the field producer is an embedded document that contains only the field company with the value ’ABC123’ and the field address with the value ’123 Street’, in the exact order: db.inventory.find( { producer: { company: 'ABC123', address: '123 Street' } } ) Equality Match on Fields within an Embedded Document Use the dot notation to match by specific fields in an embedded document. Equality matches for specific fields in an embedded document will select documents in the collection where the embedded document contains the specified fields with the specified values. The embedded document can contain additional fields. In the following example, the query uses the dot notation to match all documents where the value of the field producer is an embedded document that contains a field company with the value ’ABC123’ and may contain other fields: db.inventory.find( { 'producer.company': 'ABC123'}) Arrays When the field holds an array, you can query for an exact array match or for specific values in the array. If the array holds embedded documents, you can query for specific fields in the embedded documents using dot notation. If you specify multiple conditions using the $elemMatch operator, the array must contain at least one element that satisfies all the conditions. See Single Element Satisfies the Criteria (page 101). If you specify multiple conditions without using the $elemMatch operator, then some combination of the array elements, not necessarily a single element, must satisfy all the conditions; i.e. different elements in the array can satisfy different parts of the conditions. See Combination of Elements Satisfies the Criteria (page 102). Consider an inventory collection that contains the following documents: { _id:5, type: "food", item: "aaa", ratings:[5,8,9]} { _id:6, type: "food", item: "bbb", ratings:[5,9]} { _id:7, type: "food", item: "ccc", ratings:[9,5,8]} Exact Match on an Array To specify equality match on an array, use the query document { : } where is the array to match. Equality matches on the array require that the array field match exactly the specified , including the element order. 100 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 The following example queries for all documents where the field ratings is an array that holds exactly three ele- ments, 5, 8, and 9, in this order: db.inventory.find( { ratings:[5,8,9]}) The operation returns the following document: { "_id":5, "type": "food", "item": "aaa", "ratings":[5,8,9]} Match an Array Element Equality matches can specify a single element in the array to match. These specifications match if the array contains at least one element with the specified value. The following example queries for all documents where ratings is an array that contains 5 as one of its elements: db.inventory.find( { ratings:5}) The operation returns the following documents: { "_id":5, "type": "food", "item": "aaa", "ratings":[5,8,9]} { "_id":6, "type": "food", "item": "bbb", "ratings":[5,9]} { "_id":7, "type": "food", "item": "ccc", "ratings":[9,5,8]} Match a Specific Element of an Array Equality matches can specify equality matches for an element at a particular index or position of the array using the dot notation. In the following example, the query uses the dot notation to match all documents where the ratings array contains 5 as the first element: db.inventory.find( { 'ratings.0':5}) The operation returns the following documents: { "_id":5, "type": "food", "item": "aaa", "ratings":[5,8,9]} { "_id":6, "type": "food", "item": "bbb", "ratings":[5,9]} Specify Multiple Criteria for Array Elements Single Element Satisfies the Criteria Use $elemMatch operator to specify multiple criteria on the elements of an array such that at least one array element satisfies all the specified criteria. The following example queries for documents where the ratings array contains at least one element that is greater than ($gt) 5 and less than ($lt) 9: db.inventory.find( { ratings: { $elemMatch: { $gt:5, $lt:9}}}) The operation returns the following documents, whose ratings array contains the element 8 which meets the crite- ria: { "_id":5, "type": "food", "item": "aaa", "ratings":[5,8,9]} { "_id":7, "type": "food", "item": "ccc", "ratings":[9,5,8]} 3.3. MongoDB CRUD Tutorials 101 MongoDB Documentation, Release 3.0.7 Combination of Elements Satisfies the Criteria The following example queries for documents where the ratings array contains elements that in some combination satisfy the query conditions; e.g., one element can satisfy the greater than 5 condition and another element can satisfy the less than 9 condition, or a single element can satisfy both: db.inventory.find( { ratings: { $gt:5, $lt:9}}) The operation returns the following documents: { "_id":5, "type": "food", "item": "aaa", "ratings":[5,8,9]} { "_id":6, "type": "food", "item": "bbb", "ratings":[5,9]} { "_id":7, "type": "food", "item": "ccc", "ratings":[9,5,8]} The document with the "ratings" : [ 5, 9 ] matches the query since the element 9 is greater than 5 (the first condition) and the element 5 is less than 9 (the second condition). Array of Embedded Documents Consider that the inventory collection includes the following documents: { _id: 100, type: "food", item: "xyz", qty: 25, price: 2.5, ratings:[5,8,9], memos: [ { memo: "on time", by: "shipping" }, { memo: "approved", by: "billing"}] } { _id: 101, type: "fruit", item: "jkl", qty: 10, price: 4.25, ratings:[5,9], memos: [ { memo: "on time", by: "payment" }, { memo: "delayed", by: "shipping"}] } Match a Field in the Embedded Document Using the Array Index If you know the array index of the embedded document, you can specify the document using the embedded document’s position using the dot notation. The following example selects all documents where the memos contains an array whose first element (i.e. index is 0) is a document that contains the field by whose value is ’shipping’: db.inventory.find( { 'memos.0.by': 'shipping'}) The operation returns the following document: { _id: 100, type: "food", item: "xyz", qty: 25, price: 2.5, ratings:[5,8,9], 102 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 memos: [ { memo: "on time", by: "shipping" }, { memo: "approved", by: "billing"}] } Match a Field Without Specifying Array Index If you do not know the index position of the document in the array, concatenate the name of the field that contains the array, with a dot (.) and the name of the field in the embedded document. The following example selects all documents where the memos field contains an array that contains at least one embedded document that contains the field by with the value ’shipping’: db.inventory.find( { 'memos.by': 'shipping'}) The operation returns the following documents: { _id: 100, type: "food", item: "xyz", qty: 25, price: 2.5, ratings:[5,8,9], memos: [ { memo: "on time", by: "shipping" }, { memo: "approved", by: "billing"}] } { _id: 101, type: "fruit", item: "jkl", qty: 10, price: 4.25, ratings:[5,9], memos: [ { memo: "on time", by: "payment" }, { memo: "delayed", by: "shipping"}] } Specify Multiple Criteria for Array of Documents Single Element Satisfies the Criteria Use $elemMatch operator to specify multiple criteria on an array of em- bedded documents such that at least one embedded document satisfies all the specified criteria. The following example queries for documents where the memos array has at least one embedded document that contains both the field memo equal to ’on time’ and the field by equal to ’shipping’: db.inventory.find( { memos: { $elemMatch: { memo: 'on time', by: 'shipping' } } } ) The operation returns the following document: 3.3. MongoDB CRUD Tutorials 103 MongoDB Documentation, Release 3.0.7 { _id: 100, type: "food", item: "xyz", qty: 25, price: 2.5, ratings:[5,8,9], memos: [ { memo: "on time", by: "shipping" }, { memo: "approved", by: "billing"}] } Combination of Elements Satisfies the Criteria The following example queries for documents where the memos array contains elements that in some combination satisfy the query conditions; e.g. one element satisfies the field memo equal to ’on time’ condition and another element satisfies the field by equal to ’shipping’ condition, or a single element can satisfy both criteria: db.inventory.find( { 'memos.memo': 'on time', 'memos.by': 'shipping' } ) The query returns the following documents: { _id: 100, type: "food", item: "xyz", qty: 25, price: 2.5, ratings:[5,8,9], memos: [ { memo: "on time", by: "shipping" }, { memo: "approved", by: "billing"}] } { _id: 101, type: "fruit", item: "jkl", qty: 10, price: 4.25, ratings:[5,9], memos: [ { memo: "on time", by: "payment" }, { memo: "delayed", by: "shipping"}] } See also: Limit Fields to Return from a Query (page 109) 3.3.3 Modify Documents MongoDB provides the update() method to update the documents of a collection. The method accepts as its parameters: • an update conditions document to match the documents to update, • an update operations document to specify the modification to perform, and • an options document. 104 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 To specify the update condition, use the same structure and syntax as the query conditions. By default, update() updates a single document. To update multiple documents, use the multi option. Update Specific Fields in a Document To change a field value, MongoDB provides update operators14, such as $set to modify values. Some update operators, such as $set, will create the field if the field does not exist. See the individual update operator15 reference. Step 1: Use update operators to change field values. For the document with item equal to "MNO2", use the $set operator to update the category field and the details field to the specified values and the $currentDate operator to update the field lastModified with the current date. db.inventory.update( { item: "MNO2"}, { $set:{ category: "apparel", details: { model: "14Q3", manufacturer: "XYZ Company"} }, $currentDate: { lastModified: true } } ) The update operation returns a WriteResult object which contains the status of the operation. A successful update of the document returns the following object: WriteResult({ "nMatched":1, "nUpserted":0, "nModified":1}) The nMatched field specifies the number of existing documents matched for the update, and nModified specifies the number of existing documents modified. Step 2: Update an embedded field. To update a field within an embedded document, use the dot notation. When using the dot notation, enclose the whole dotted field name in quotes. The following updates the model field within the embedded details document. db.inventory.update( { item: "ABC1"}, { $set:{ "details.model": "14Q2"}} ) The update operation returns a WriteResult object which contains the status of the operation. A successful update of the document returns the following object: WriteResult({ "nMatched":1, "nUpserted":0, "nModified":1}) 14https://docs.mongodb.org/manual/reference/operator/update 15https://docs.mongodb.org/manual/reference/operator/update 3.3. MongoDB CRUD Tutorials 105 MongoDB Documentation, Release 3.0.7 Step 3: Update multiple documents. By default, the update() method updates a single document. To update multiple documents, use the multi option in the update() method. Update the category field to "apparel" and update the lastModified field to the current date for all docu- ments that have category field equal to "clothing". db.inventory.update( { category: "clothing"}, { $set: { category: "apparel"}, $currentDate: { lastModified: true } }, { multi: true } ) The update operation returns a WriteResult object which contains the status of the operation. A successful update of the document returns the following object: WriteResult({ "nMatched":3, "nUpserted":0, "nModified":3}) Replace the Document To replace the entire content of a document except for the _id field, pass an entirely new document as the second argument to update(). The replacement document can have different fields from the original document. In the replacement document, you can omit the _id field since the _id field is immutable. If you do include the _id field, it must be the same value as the existing value. Step 1: Replace a document. The following operation replaces the document with item equal to "BE10". The newly replaced document will only contain the the _id field and the fields in the replacement document. db.inventory.update( { item: "BE10"}, { item: "BE05", stock: [ { size: "S", qty: 20 }, { size: "M", qty:5}], category: "apparel" } ) The update operation returns a WriteResult object which contains the status of the operation. A successful update of the document returns the following object: WriteResult({ "nMatched":1, "nUpserted":0, "nModified":1}) upsert Option By default, if no document matches the update query, the update() method does nothing. However, by specifying upsert: true, the update() method either updates matching document or documents, or inserts a new document using the update specification if no matching document exists. 106 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 Step 1: Specify upsert: true for the update replacement operation. When you specify upsert: true for an update operation to replace a document and no matching documents are found, MongoDB creates a new document using the equality conditions in the update conditions document, and replaces this document, except for the _id field if specified, with the update document. The following operation either updates a matching document by replacing it with a new document or adds a new document if no matching document exists. db.inventory.update( { item: "TBD1"}, { item: "TBD1", details:{ "model": "14Q4", "manufacturer": "ABC Company"}, stock:[{ "size": "S", "qty": 25}], category: "houseware" }, { upsert: true } ) The update operation returns a WriteResult object which contains the status of the operation, including whether the db.collection.update() method modified an existing document or added a new document. WriteResult({ "nMatched":0, "nUpserted":1, "nModified":0, "_id": ObjectId("53dbd684babeaec6342ed6c7") }) The nMatched field shows that the operation matched 0 documents. The nUpserted of 1 shows that the update added a document. The nModified of 0 specifies that no existing documents were updated. The _id field shows the generated _id field for the added document. Step 2: Specify upsert: true for the update specific fields operation. When you specify upsert: true for an update operation that modifies specific fields and no matching documents are found, MongoDB creates a new document using the equality conditions in the update conditions document, and applies the modification as specified in the update document. The following update operation either updates specific fields of a matching document or adds a new document if no matching document exists. db.inventory.update( { item: "TBD2"}, { $set:{ details:{ "model": "14Q3", "manufacturer": "IJK Co."}, category: "houseware" } }, { upsert: true } ) 3.3. MongoDB CRUD Tutorials 107 MongoDB Documentation, Release 3.0.7 The update operation returns a WriteResult object which contains the status of the operation, including whether the db.collection.update() method modified an existing document or added a new document. WriteResult({ "nMatched":0, "nUpserted":1, "nModified":0, "_id": ObjectId("53dbd7c8babeaec6342ed6c8") }) The nMatched field shows that the operation matched 0 documents. The nUpserted of 1 shows that the update added a document. The nModified of 0 specifies that no existing documents were updated. The _id field shows the generated _id field for the added document. Additional Examples and Methods For more examples, see Update examples in the db.collection.update() reference page. The db.collection.findAndModify() and the db.collection.save() method can also modify exist- ing documents or insert a new one. See the individual reference pages for the methods for more information and examples. 3.3.4 Remove Documents In MongoDB, the db.collection.remove() method removes documents from a collection. You can remove all documents from a collection, remove all documents that match a condition, or limit the operation to remove just a single document. This tutorial provides examples of remove operations using the db.collection.remove() method in the mongo shell. Remove All Documents To remove all documents from a collection, pass an empty query document {} to the remove() method. The remove() method does not remove the indexes. The following example removes all documents from the inventory collection: db.inventory.remove({}) To remove all documents from a collection, it may be more efficient to use the drop() method to drop the entire collection, including the indexes, and then recreate the collection and rebuild the indexes. Remove Documents that Match a Condition To remove the documents that match a deletion criteria, call the remove() method with the parameter. The following example removes all documents from the inventory collection where the type field equals food: db.inventory.remove( { type: "food"}) For large deletion operations, it may be more efficient to copy the documents that you want to keep to a new collection and then use drop() on the original collection. 108 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 Remove a Single Document that Matches a Condition To remove a single document, call the remove() method with the justOne parameter set to true or 1. The following example removes one document from the inventory collection where the type field equals food: db.inventory.remove( { type: "food"},1) To delete a single document sorted by some specified order, use the findAndModify() method. 3.3.5 Limit Fields to Return from a Query The projection document limits the fields to return for all matching documents. The projection document can specify the inclusion of fields or the exclusion of fields. The specifications have the following forms: Syntax Description : <1 or true> Specify the inclusion of a field. : <0 or false> Specify the suppression of the field. Important: The _id field is, by default, included in the result set. To suppress the _id field from the result set, specify _id: 0 in the projection document. You cannot combine inclusion and exclusion semantics in a single projection with the exception of the _id field. This tutorial offers various query examples that limit the fields to return for all matching documents. The examples in this tutorial use a collection inventory and use the db.collection.find() method in the mongo shell. The db.collection.find() method returns a cursor (page 66) to the retrieved documents. For examples on query selection criteria, see Query Documents (page 98). Return All Fields in Matching Documents If you specify no projection, the find() method returns all fields of all documents that match the query. db.inventory.find( { type: 'food'}) This operation will return all documents in the inventory collection where the value of the type field is ’food’. The returned documents contain all fields. Return the Specified Fields and the _id Field Only A projection can explicitly include several fields. In the following operation, the find() method returns all docu- ments that match the query. In the result set, only the item and qty fields and, by default, the _id field return in the matching documents. db.inventory.find( { type: 'food' }, { item:1, qty:1}) Return Specified Fields Only You can remove the _id field from the results by specifying its exclusion in the projection, as in the following example: db.inventory.find( { type: 'food' }, { item:1, qty:1, _id:0}) 3.3. MongoDB CRUD Tutorials 109 MongoDB Documentation, Release 3.0.7 This operation returns all documents that match the query. In the result set, only the item and qty fields return in the matching documents. Return All But the Excluded Field To exclude a single field or group of fields you can use a projection in the following form: db.inventory.find( { type: 'food' }, { type:0}) This operation returns all documents where the value of the type field is food. In the result set, the type field does not return in the matching documents. With the exception of the _id field you cannot combine inclusion and exclusion statements in projection documents. Return Specific Fields in Embedded Documents Use the dot notation (page 175) to return specific fields inside an embedded document. For example, the inventory collection contains the following document: { "_id":3, "type": "food", "item": "aaa", "classification": { dept: "grocery", category: "chocolate"} } The following operation returns all documents that match the query. The specified projection returns only the category field in the classification document. The returned category field remains inside the classification document. db.inventory.find( { type: 'food', _id:3}, { "classification.category":1, _id:0} ) The operation returns the following document: { "classification":{ "category": "chocolate"}} Suppress Specific Fields in Embedded Documents Use dot notation (page 175) to suppress specific fields inside an embedded document using a 0 instead of 1. For example, the inventory collection contains the following document: { "_id":3, "type": "food", "item": "Super Dark Chocolate", "classification":{ "dept": "grocery", "category": "chocolate"}, "vendor":{ "primary":{ "name": "Marsupial Vending Co", "address": "Wallaby Rd", "delivery":["M","W","F"] }, "secondary":{ 110 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 "name": "Intl. Chocolatiers", "address": "Cocoa Plaza", "delivery":["Sa"] } } } The following operation returns all documents where the value of the type field is food and the _id field is 3. The projection suppresses only the category field in the classification document. The dept field remains inside the classification document. db.inventory.find( { type: 'food', _id:3}, { "classification.category":0} ) The operation returns the following document: { "_id":3, "type": "food", "item": "Super Dark Chocolate", "classification":{ "dept": "grocery"}, "vendor":{ "primary":{ "name": "Bobs Vending", "address": "Wallaby Rd", "delivery":["M","W","F"] }, "secondary":{ "name": "Intl. Chocolatiers", "address": "Cocoa Plaza", "delivery":["Sa"] } } } You can suppress nested subdocuments at any depth using dot notation (page 175). The following specifies a projection to suppress the delivery array only for the secondary document. db.inventory.find( { "type": "food"}, { "vendor.secondary.delivery":0} ) This returns all documents except the delivery array in the secondary document { "_id":3, "type": "food", "item": "Super Dark Chocolate", "classification":{ "dept": "grocery", "category": "chocolate"}, "vendor":{ "primary":{ "name": "Bobs Vending", "address": "Wallaby Rd", "delivery":["M","W","F"] }, "secondary":{ 3.3. MongoDB CRUD Tutorials 111 MongoDB Documentation, Release 3.0.7 "name": "Intl. Chocolatiers", "address": "Cocoa Plaza" } } } Projection for Array Fields For fields that contain arrays, MongoDB provides the following projection operators: $elemMatch, $slice, and $. For example, the inventory collection contains the following document: { "_id":5, "type": "food", "item": "aaa", "ratings":[5,8,9]} Then the following operation uses the $slice projection operator to return just the first two elements in the ratings array. db.inventory.find( { _id:5 }, { ratings: { $slice:2}}) $elemMatch, $slice, and $ are the only way to project portions of an array. For instance, you cannot project a portion of an array using the array index; e.g. { "ratings.0": 1 } projection will not project the array with the first element. See also: Query Documents (page 98) 3.3.6 Limit Number of Elements in an Array after an Update New in version 2.4. Synopsis Consider an application where users may submit many scores (e.g. for a test), but the application only needs to track the top three test scores. This pattern uses the $push operator with the $each, $sort, and $slice modifiers to sort and maintain an array of fixed size. Pattern Consider the following document in the collection students: { _id:1, scores:[ { attempt:1, score: 10}, { attempt:2 , score:8} ] } The following update uses the $push operator with: • the $each modifier to append to the array 2 new elements, 112 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 • the $sort modifier to order the elements by ascending (1) score, and • the $slice modifier to keep the last 3 elements of the ordered array. db.students.update( { _id:1}, { $push:{ scores:{ $each: [ { attempt:3, score:7 }, { attempt:4, score:4}], $sort: { score:1}, $slice:-3 } } } ) Note: When using the $sort modifier on the array element, access the field in the embedded document element directly instead of using the dot notation on the array field. After the operation, the document contains only the top 3 scores in the scores array: { "_id":1, "scores":[ { "attempt":3, "score":7}, { "attempt":2, "score":8}, { "attempt":1, "score": 10} ] } See also: • $push operator, • $each modifier, • $sort modifier, and • $slice modifier. 3.3.7 Iterate a Cursor in the mongo Shell The db.collection.find() method returns a cursor. To access the documents, you need to iterate the cursor. However, in the mongo shell, if the returned cursor is not assigned to a variable using the var keyword, then the cursor is automatically iterated up to 20 times to print up to the first 20 documents in the results. The following describes ways to manually iterate the cursor to access the documents or to use the iterator index. Manually Iterate the Cursor In the mongo shell, when you assign the cursor returned from the find() method to a variable using the var keyword, the cursor does not automatically iterate. You can call the cursor variable in the shell to iterate up to 20 times 16 and print the matching documents, as in the following example: 16 You can use the DBQuery.shellBatchSize to change the number of iteration from the default value 20. See Executing Queries (page 278) for more information. 3.3. MongoDB CRUD Tutorials 113 MongoDB Documentation, Release 3.0.7 var myCursor= db.inventory.find( { type: 'food'}); myCursor You can also use the cursor method next() to access the documents, as in the following example: var myCursor= db.inventory.find( { type: 'food'}); while (myCursor.hasNext()) { print(tojson(myCursor.next())); } As an alternative print operation, consider the printjson() helper method to replace print(tojson()): var myCursor= db.inventory.find( { type: 'food'}); while (myCursor.hasNext()) { printjson(myCursor.next()); } You can use the cursor method forEach() to iterate the cursor and access the documents, as in the following example: var myCursor= db.inventory.find( { type: 'food'}); myCursor.forEach(printjson); See JavaScript cursor methods and your driver documentation for more information on cursor methods. Iterator Index In the mongo shell, you can use the toArray() method to iterate the cursor and return the documents in an array, as in the following: var myCursor= db.inventory.find( { type: 'food'}); var documentArray= myCursor.toArray(); var myDocument= documentArray[3]; The toArray() method loads into RAM all documents returned by the cursor; the toArray() method exhausts the cursor. Additionally, some drivers provide access to the documents by using an index on the cursor (i.e. cursor[index]). This is a shortcut for first calling the toArray() method and then using an index on the resulting array. Consider the following example: var myCursor= db.inventory.find( { type: 'food'}); var myDocument= myCursor[3]; The myCursor[3] is equivalent to the following example: myCursor.toArray() [3]; 3.3.8 Analyze Query Performance The cursor.explain("executionStats") and the db.collection.explain("executionStats") methods provide statistics about the performance of a query. This data output can be useful in measuring if and how a 114 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 query uses an index. db.collection.explain() provides information on the execution of other operations, such as db.collection.update(). See db.collection.explain() for details. Evaluate the Performance of a Query Consider a collection inventory with the following documents: { "_id":1, "item": "f1", type: "food", quantity: 500} { "_id":2, "item": "f2", type: "food", quantity: 100} { "_id":3, "item": "p1", type: "paper", quantity: 200} { "_id":4, "item": "p2", type: "paper", quantity: 150} { "_id":5, "item": "f3", type: "food", quantity: 300} { "_id":6, "item": "t1", type: "toys", quantity: 500} { "_id":7, "item": "a1", type: "apparel", quantity: 250} { "_id":8, "item": "a2", type: "apparel", quantity: 400} { "_id":9, "item": "t2", type: "toys", quantity: 50} { "_id": 10, "item": "f4", type: "food", quantity: 75} Query with No Index The following query retrieves documents where the quantity field has a value between 100 and 200, inclusive: db.inventory.find( { quantity: { $gte: 100, $lte: 200}}) The query returns the following documents: { "_id":2, "item": "f2", "type": "food", "quantity": 100} { "_id":3, "item": "p1", "type": "paper", "quantity": 200} { "_id":4, "item": "p2", "type": "paper", "quantity": 150} To view the query plan selected, use the explain("executionStats") method: db.inventory.find( { quantity: { $gte: 100, $lte: 200}} ).explain("executionStats") explain() returns the following results: { "queryPlanner":{ "plannerVersion":1, ... "winningPlan":{ "stage": "COLLSCAN", ... } }, "executionStats":{ "executionSuccess": true, "nReturned":3, "executionTimeMillis":0, "totalKeysExamined":0, "totalDocsExamined": 10, "executionStages":{ "stage": "COLLSCAN", 3.3. MongoDB CRUD Tutorials 115 MongoDB Documentation, Release 3.0.7 ... }, ... }, ... } • queryPlanner.winningPlan.stage displays COLLSCAN to indicate a collection scan. • executionStats.nReturned displays 3 to indicate that the query matches and returns three documents. • executionStats.totalDocsExamined display 10 to indicate that MongoDB had to scan ten docu- ments (i.e. all documents in the collection) to find the three matching documents. The difference between the number of matching documents and the number of examined documents may suggest that, to improve efficiency, the query might benefit from the use of an index. Query with Index To support the query on the quantity field, add an index on the quantity field: db.inventory.createIndex( { quantity:1}) To view the query plan statistics, use the explain("executionStats") method: db.inventory.find( { quantity: { $gte: 100, $lte: 200}} ).explain("executionStats") The explain() method returns the following results: { "queryPlanner":{ "plannerVersion":1, ... "winningPlan":{ "stage": "FETCH", "inputStage":{ "stage": "IXSCAN", "keyPattern":{ "quantity":1 }, ... } }, "rejectedPlans":[] }, "executionStats":{ "executionSuccess": true, "nReturned":3, "executionTimeMillis":0, "totalKeysExamined":3, "totalDocsExamined":3, "executionStages":{ ... }, ... }, 116 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 ... } • queryPlanner.winningPlan.inputStage.stage displays IXSCAN to indicate index use. • executionStats.nReturned displays 3 to indicate that the query matches and returns three documents. • executionStats.totalKeysExamined display 3 to indicate that MongoDB scanned three index en- tries. • executionStats.totalDocsExamined display 3 to indicate that MongoDB scanned three documents. When run with an index, the query scanned 3 index entries and 3 documents to return 3 matching documents. Without the index, to return the 3 matching documents, the query had to scan the whole collection, scanning 10 documents. Compare Performance of Indexes To manually compare the performance of a query using more than one index, you can use the hint() method in conjunction with the explain() method. Consider the following query: db.inventory.find( { quantity: { $gte: 100, $lte: 300 }, type: "food"}) The query returns the following documents: { "_id":2, "item": "f2", "type": "food", "quantity": 100} { "_id":5, "item": "f3", "type": "food", "quantity": 300} To support the query, add a compound index (page 488). With compound indexes (page 488), the order of the fields matter. For example, add the following two compound indexes. The first index orders by quantity field first, and then the type field. The second index orders by type first, and then the quantity field. db.inventory.createIndex( { quantity:1, type:1}) db.inventory.createIndex( { type:1, quantity:1}) Evaluate the effect of the first index on the query: db.inventory.find( { quantity: { $gte: 100, $lte: 300 }, type: "food"} ).hint({ quantity:1, type:1 }).explain("executionStats") The explain() method returns the following output: { "queryPlanner":{ ... "winningPlan":{ "stage": "FETCH", "inputStage":{ "stage": "IXSCAN", "keyPattern":{ "quantity":1, "type":1 }, ... } } }, 3.3. MongoDB CRUD Tutorials 117 MongoDB Documentation, Release 3.0.7 "rejectedPlans":[] }, "executionStats":{ "executionSuccess": true, "nReturned":2, "executionTimeMillis":0, "totalKeysExamined":5, "totalDocsExamined":2, "executionStages":{ ... } }, ... } MongoDB scanned 5 index keys (executionStats.totalKeysExamined) to return 2 matching documents (executionStats.nReturned). Evaluate the effect of the second index on the query: db.inventory.find( { quantity: { $gte: 100, $lte: 300 }, type: "food"} ).hint({ type:1, quantity:1 }).explain("executionStats") The explain() method returns the following output: { "queryPlanner":{ ... "winningPlan":{ "stage": "FETCH", "inputStage":{ "stage": "IXSCAN", "keyPattern":{ "type":1, "quantity":1 }, ... } }, "rejectedPlans":[] }, "executionStats":{ "executionSuccess": true, "nReturned":2, "executionTimeMillis":0, "totalKeysExamined":2, "totalDocsExamined":2, "executionStages":{ ... } }, ... } MongoDB scanned 2 index keys (executionStats.totalKeysExamined) to return 2 matching documents (executionStats.nReturned). For this example query, the compound index { type: 1, quantity: 1 } is more efficient than the com- pound index { quantity: 1, type: 1 }. 118 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 See also: Query Optimization (page 67), Query Plans (page 70), Optimize Query Performance (page 221), Indexing Strategies (page 547) Additional Resources • MongoDB Performance Evaluation and Tuning Consulting Package17 3.3.9 Perform Two Phase Commits Synopsis This document provides a pattern for doing multi-document updates or “multi-document transactions” using a two- phase commit approach for writing data to multiple documents. Additionally, you can extend this process to provide a rollback-like (page 123) functionality. Background Operations on a single document are always atomic with MongoDB databases; however, operations that involve multi- ple documents, which are often referred to as “multi-document transactions”, are not atomic. Since documents can be fairly complex and contain multiple “nested” documents, single-document atomicity provides the necessary support for many practical use cases. Despite the power of single-document atomic operations, there are cases that require multi-document transactions. When executing a transaction composed of sequential operations, certain issues arise, such as: • Atomicity: if one operation fails, the previous operation within the transaction must “rollback” to the previous state (i.e. the “nothing,” in “all or nothing”). • Consistency: if a major failure (i.e. network, hardware) interrupts the transaction, the database must be able to recover a consistent state. For situations that require multi-document transactions, you can implement two-phase commit in your application to provide support for these kinds of multi-document updates. Using two-phase commit ensures that data is consistent and, in case of an error, the state that preceded the transaction is recoverable (page 123). During the procedure, however, documents can represent pending data and states. Note: Because only single-document operations are atomic with MongoDB, two-phase commits can only offer transaction-like semantics. It is possible for applications to return intermediate data at intermediate points during the two-phase commit or rollback. Pattern Overview Consider a scenario where you want to transfer funds from account A to account B. In a relational database system, you can subtract the funds from A and add the funds to B in a single multi-statement transaction. In MongoDB, you can emulate a two-phase commit to achieve a comparable result. The examples in this tutorial use the following two collections: 17https://www.mongodb.com/products/consulting?jmp=docs#performance_evaluation 3.3. MongoDB CRUD Tutorials 119 MongoDB Documentation, Release 3.0.7 1. A collection named accounts to store account information. 2. A collection named transactions to store information on the fund transfer transactions. Initialize Source and Destination Accounts Insert into the accounts collection a document for account A and a document for account B. db.accounts.insert( [ { _id: "A", balance: 1000, pendingTransactions: [] }, { _id: "B", balance: 1000, pendingTransactions:[]} ] ) The operation returns a BulkWriteResult() object with the status of the operation. Upon successful insert, the BulkWriteResult() has nInserted set to 2 . Initialize Transfer Record For each fund transfer to perform, insert into the transactions collection a document with the transfer information. The document contains the following fields: • source and destination fields, which refer to the _id fields from the accounts collection, • value field, which specifies the amount of transfer affecting the balance of the source and destination accounts, • state field, which reflects the current state of the transfer. The state field can have the value of initial, pending, applied, done, canceling, and canceled. • lastModified field, which reflects last modification date. To initialize the transfer of 100 from account A to account B, insert into the transactions collection a document with the transfer information, the transaction state of "initial", and the lastModified field set to the current date: db.transactions.insert( { _id:1, source: "A", destination: "B", value: 100, state: "initial", lastModified: new Date() } ) The operation returns a WriteResult() object with the status of the operation. Upon successful insert, the WriteResult() object has nInserted set to 1. Transfer Funds Between Accounts Using Two-Phase Commit Step 1: Retrieve the transaction to start. From the transactions collection, find a transaction in the initial state. Currently the transactions collection has only one document, namely the one added in the Initialize Transfer Record (page 120) step. If the collection contains additional documents, the query will return any transaction with an initial state unless you specify additional query conditions. var t= db.transactions.findOne( { state: "initial"}) Type the variable t in the mongo shell to print the contents of the variable. The operation should print a document similar to the following except the lastModified field should reflect date of your insert operation: 120 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 { "_id":1, "source": "A", "destination": "B", "value": 100, "state": "initial", "lastModified": ISODate("2014-07-11T20:39:26.345Z")} Step 2: Update transaction state to pending. Set the transaction state from initial to pending and use the $currentDate operator to set the lastModified field to the current date. db.transactions.update( { _id: t._id, state: "initial"}, { $set: { state: "pending"}, $currentDate: { lastModified: true } } ) The operation returns a WriteResult() object with the status of the operation. Upon successful update, the nMatched and nModified displays 1. In the update statement, the state: "initial" condition ensures that no other process has already updated this record. If nMatched and nModified is 0, go back to the first step to get a different transaction and restart the procedure. Step 3: Apply the transaction to both accounts. Apply the transaction t to both accounts using the update() method if the transaction has not been applied to the accounts. In the update condition, include the condition pendingTransactions: { $ne: t._id } in order to avoid re-applying the transaction if the step is run more than once. To apply the transaction to the account, update both the balance field and the pendingTransactions field. Update the source account, subtracting from its balance the transaction value and adding to its pendingTransactions array the transaction _id. db.accounts.update( { _id: t.source, pendingTransactions: { $ne: t._id } }, { $inc: { balance:-t.value }, $push: { pendingTransactions: t._id } } ) Upon successful update, the method returns a WriteResult() object with nMatched and nModified set to 1. Update the destination account, adding to its balance the transaction value and adding to its pendingTransactions array the transaction _id . db.accounts.update( { _id: t.destination, pendingTransactions: { $ne: t._id } }, { $inc: { balance: t.value }, $push: { pendingTransactions: t._id } } ) Upon successful update, the method returns a WriteResult() object with nMatched and nModified set to 1. Step 4: Update transaction state to applied. Use the following update() operation to set the transaction’s state to applied and update the lastModified field: db.transactions.update( { _id: t._id, state: "pending"}, { $set: { state: "applied"}, $currentDate: { lastModified: true } } ) 3.3. MongoDB CRUD Tutorials 121 MongoDB Documentation, Release 3.0.7 Upon successful update, the method returns a WriteResult() object with nMatched and nModified set to 1. Step 5: Update both accounts’ list of pending transactions. Remove the applied transaction _id from the pendingTransactions array for both accounts. Update the source account. db.accounts.update( { _id: t.source, pendingTransactions: t._id }, { $pull: { pendingTransactions: t._id } } ) Upon successful update, the method returns a WriteResult() object with nMatched and nModified set to 1. Update the destination account. db.accounts.update( { _id: t.destination, pendingTransactions: t._id }, { $pull: { pendingTransactions: t._id } } ) Upon successful update, the method returns a WriteResult() object with nMatched and nModified set to 1. Step 6: Update transaction state to done. Complete the transaction by setting the state of the transaction to done and updating the lastModified field: db.transactions.update( { _id: t._id, state: "applied"}, { $set: { state: "done"}, $currentDate: { lastModified: true } } ) Upon successful update, the method returns a WriteResult() object with nMatched and nModified set to 1. Recovering from Failure Scenarios The most important part of the transaction procedure is not the prototypical example above, but rather the possibility for recovering from the various failure scenarios when transactions do not complete successfully. This section presents an overview of possible failures and provides steps to recover from these kinds of events. Recovery Operations The two-phase commit pattern allows applications running the sequence to resume the transaction and arrive at a consistent state. Run the recovery operations at application startup, and possibly at regular intervals, to catch any unfinished transactions. The time required to reach a consistent state depends on how long the application needs to recover each transaction. The following recovery procedures uses the lastModified date as an indicator of whether the pending transaction requires recovery; specifically, if the pending or applied transaction has not been updated in the last 30 minutes, the procedures determine that these transactions require recovery. You can use different conditions to make this determination. 122 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 Transactions in Pending State To recover from failures that occur after step “Update transaction state to pending. (page ??)” but before “Update transaction state to applied. (page ??)” step, retrieve from the transactions collection a pending transaction for recovery: var dateThreshold= new Date(); dateThreshold.setMinutes(dateThreshold.getMinutes()- 30); var t= db.transactions.findOne( { state: "pending", lastModified: { $lt: dateThreshold } } ); And resume from step “Apply the transaction to both accounts. (page ??)“ Transactions in Applied State To recover from failures that occur after step “Update transaction state to applied. (page ??)” but before “Update transaction state to done. (page ??)” step, retrieve from the transactions collection an applied transaction for recovery: var dateThreshold= new Date(); dateThreshold.setMinutes(dateThreshold.getMinutes()- 30); var t= db.transactions.findOne( { state: "applied", lastModified: { $lt: dateThreshold } } ); And resume from “Update both accounts’ list of pending transactions. (page ??)“ Rollback Operations In some cases, you may need to “roll back” or undo a transaction; e.g., if the application needs to “cancel” the transaction or if one of the accounts does not exist or stops existing during the transaction. Transactions in Applied State After the “Update transaction state to applied. (page ??)” step, you should not roll back the transaction. Instead, complete that transaction and create a new transaction (page 120) to reverse the transaction by switching the values in the source and the destination fields. Transactions in Pending State After the “Update transaction state to pending. (page ??)” step, but before the “Update transaction state to applied. (page ??)” step, you can rollback the transaction using the following procedure: Step 1: Update transaction state to canceling. Update the transaction state from pending to canceling. db.transactions.update( { _id: t._id, state: "pending"}, { $set: { state: "canceling"}, $currentDate: { lastModified: true } } ) Upon successful update, the method returns a WriteResult() object with nMatched and nModified set to 1. Step 2: Undo the transaction on both accounts. To undo the transaction on both accounts, reverse the transaction t if the transaction has been applied. In the update condition, include the condition pendingTransactions: t._id in order to update the account only if the pending transaction has been applied. Update the destination account, subtracting from its balance the transaction value and removing the transaction _id from the pendingTransactions array. 3.3. MongoDB CRUD Tutorials 123 MongoDB Documentation, Release 3.0.7 db.accounts.update( { _id: t.destination, pendingTransactions: t._id }, { $inc: { balance:-t.value }, $pull: { pendingTransactions: t._id } } ) Upon successful update, the method returns a WriteResult() object with nMatched and nModified set to 1. If the pending transaction has not been previously applied to this account, no document will match the update condition and nMatched and nModified will be 0. Update the source account, adding to its balance the transaction value and removing the transaction _id from the pendingTransactions array. db.accounts.update( { _id: t.source, pendingTransactions: t._id }, { $inc: { balance: t.value}, $pull: { pendingTransactions: t._id } } ) Upon successful update, the method returns a WriteResult() object with nMatched and nModified set to 1. If the pending transaction has not been previously applied to this account, no document will match the update condition and nMatched and nModified will be 0. Step 3: Update transaction state to canceled. To finish the rollback, update the transaction state from canceling to cancelled. db.transactions.update( { _id: t._id, state: "canceling"}, { $set: { state: "cancelled"}, $currentDate: { lastModified: true } } ) Upon successful update, the method returns a WriteResult() object with nMatched and nModified set to 1. Multiple Applications Transactions exist, in part, so that multiple applications can create and run operations concurrently without causing data inconsistency or conflicts. In our procedure, to update or retrieve the transaction document, the update conditions include a condition on the state field to prevent reapplication of the transaction by multiple applications. For example, applications App1 and App2 both grab the same transaction, which is in the initial state. App1 applies the whole transaction before App2 starts. When App2 attempts to perform the “Update transaction state to pending. (page ??)” step, the update condition, which includes the state: "initial" criterion, will not match any document, and the nMatched and nModified will be 0. This should signal to App2 to go back to the first step to restart the procedure with a different transaction. When multiple applications are running, it is crucial that only one application can handle a given transaction at any point in time. As such, in addition including the expected state of the transaction in the update condition, you can also create a marker in the transaction document itself to identify the application that is handling the transaction. Use findAndModify() method to modify the transaction and get it back in one step: 124 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 t= db.transactions.findAndModify( { query: { state: "initial", application: { $exists: false } }, update: { $set: { state: "pending", application: "App1"}, $currentDate: { lastModified: true } }, new: true } ) Amend the transaction operations to ensure that only applications that match the identifier in the application field apply the transaction. If the application App1 fails during transaction execution, you can use the recovery procedures (page 122), but appli- cations should ensure that they “own” the transaction before applying the transaction. For example to find and resume the pending job, use a query that resembles the following: var dateThreshold= new Date(); dateThreshold.setMinutes(dateThreshold.getMinutes()- 30); db.transactions.find( { application: "App1", state: "pending", lastModified: { $lt: dateThreshold } } ) Using Two-Phase Commits in Production Applications The example transaction above is intentionally simple. For example, it assumes that it is always possible to roll back operations to an account and that account balances can hold negative values. Production implementations would likely be more complex. Typically, accounts need information about current bal- ance, pending credits, and pending debits. For all transactions, ensure that you use the appropriate level of write concern (page 80) for your deployment. 3.3.10 Update Document if Current Overview The Update if Current pattern is an approach to concurrency control (page 84) when multiple applications have access to the data. Pattern The pattern queries for the document to update. Then, for each field to modify, the pattern includes the field and its value in the returned document in the query predicate for the update operation. This way, the update only modifies the document fields if the fields have not changed since the query. 3.3. MongoDB CRUD Tutorials 125 MongoDB Documentation, Release 3.0.7 Example Consider the following example in the mongo shell. The example updates the quantity and the reordered fields of a document only if the fields have not changed since the query. Changed in version 2.6: The db.collection.update() method now returns a WriteResult() object that contains the status of the operation. Previous versions required an extra db.getLastErrorObj() method call. var myDocument= db.products.findOne( { sku: "abc123"}); if ( myDocument ) { var oldQuantity= myDocument.quantity; var oldReordered= myDocument.reordered; var results= db.products.update( { _id: myDocument._id, quantity: oldQuantity, reordered: oldReordered }, { $inc: { quantity: 50}, $set: { reordered: true } } ) if ( results.hasWriteError() ) { print( "unexpected error updating document: "+ tojson(results) ); } else if ( results.nMatched ===0){ print( "No matching document for "+ "{ _id: "+ myDocument._id.toString()+ ", quantity: "+ oldQuantity+ ", reordered: "+ oldReordered +"}" ); } } Modifications to the Pattern Another approach is to add a version field to the documents. Applications increment this field upon each update operation to the documents. You must be able to ensure that all clients that connect to your database include the version field in the query predicate. To associate increasing numbers with documents in a collection, you can use one of the methods described in Create an Auto-Incrementing Sequence Field (page 129). For more approaches, see Concurrency Control (page 84). 3.3.11 Create Tailable Cursor Overview By default, MongoDB will automatically close a cursor when the client has exhausted all results in the cursor. How- ever, for capped collections (page 213) you may use a Tailable Cursor that remains open after the client exhausts the results in the initial cursor. Tailable cursors are conceptually equivalent to the tail Unix command with the -f 126 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 option (i.e. with “follow” mode). After clients insert new additional documents into a capped collection, the tailable cursor will continue to retrieve documents. Use tailable cursors on capped collections that have high write volumes where indexes aren’t practical. For instance, MongoDB replication (page 559) uses tailable cursors to tail the primary’s oplog. Note: If your query is on an indexed field, do not use tailable cursors, but instead, use a regular cursor. Keep track of the last value of the indexed field returned by the query. To retrieve the newly added documents, query the collection again using the last value of the indexed field in the query criteria, as in the following example: db..find( { indexedField: { $gt:}}) Consider the following behaviors related to tailable cursors: • Tailable cursors do not use indexes and return documents in natural order. • Because tailable cursors do not use indexes, the initial scan for the query may be expensive; but, after initially exhausting the cursor, subsequent retrievals of the newly added documents are inexpensive. • Tailable cursors may become dead, or invalid, if either: – the query returns no match. – the cursor returns the document at the “end” of the collection and then the application deletes that docu- ment. A dead cursor has an id of 0. See your driver documentation for the driver-specific method to specify the tailable cursor. C++ Example The tail function uses a tailable cursor to output the results from a query to a capped collection: • The function handles the case of the dead cursor by having the query be inside a loop. • To periodically check for new data, the cursor->more() statement is also inside a loop. #include "client/dbclient.h" using namespace mongo; /* * Example of a tailable cursor. * The function "tails" the capped collection (ns) and output elements as they are added. * The function also handles the possibility of a dead cursor by tracking the field 'insertDate'. * New documents are added with increasing values of 'insertDate'. */ void tail(DBClientBase& conn, const char *ns) { BSONElement lastValue= minKey.firstElement(); Query query= Query().hint( BSON("$natural"<<1)); while (1){ auto_ptrc= conn.query(ns, query,0,0,0, QueryOption_CursorTailable| QueryOption_AwaitData ); 3.3. MongoDB CRUD Tutorials 127 MongoDB Documentation, Release 3.0.7 while (1){ if (!c->more() ) { if ( c->isDead() ) { break; } continue; } BSONObj o=c->next(); lastValue= o["insertDate"]; cout<< o.toString()<< endl; } query= QUERY("insertDate"<c= conn.query(ns, query,0,0,0, QueryOption_CursorTailable| QueryOption_AwaitData ); * Specify the capped collection using ns as an argument to the function. * Set the QueryOption_CursorTailable option to create a tailable cursor. * Set the QueryOption_AwaitData option so that the returned cursor blocks for a few seconds to wait for data. – In an inner while (1) loop, read the documents from the cursor: * If the cursor has no more documents and is not invalid, loop the inner while loop to recheck for more documents. * If the cursor has no more documents and is dead, break the inner while loop. * If the cursor has documents: · output the document, · update the lastValue value, · and loop the inner while (1) loop to recheck for more documents. – If the logic breaks out of the inner while (1) loop and the cursor is invalid: * Use the lastValue value to create a new query condition that matches documents added after the lastValue. Explicitly ensure $natural order with the hint() method: query= QUERY("insertDate"< Guarantees that write operations have propagated successfully to the specified number of replica set members including the primary. For example, w: 2 indicates acknowledgements from the primary and at least one secondary. If you set w to a number that is greater than the number of set members that hold data, MongoDB waits for the non-existent members to become available, which means MongoDB blocks indefinitely. "majority" Confirms that write operations have propagated to the majority of voting nodes: a majority of the replica set’s voting members must acknowledge the write operation before it succeeds. This allows you to avoid hard coding assumptions about the size of your replica set into your application. Changed in version 3.0: In previous versions, w: "majority" refers to the majority of the replica set’s members. Changed in version 2.6: In Master/Slave (page 596) deployments, MongoDB treats w: "majority" as equivalent to w: 1. In earlier versions of MongoDB, w: "majority" produces an error in master/slave (page 596) deployments. By specifying a tag set (page 635), you can have fine-grained control over which replica set members must acknowledge a write operation to satisfy the required level of write concern. j Option The j option confirms that the mongod instance has written the data to the on-disk journal. This ensures that data is not lost if the mongod instance shuts down unexpectedly. Set to true to enable. Changed in version 2.6: Specifying a write concern that includes j: true to a mongod or mongos running with --nojournal option now errors. Previous versions would ignore the j: true. Note: Requiring journaled write concern in a replica set only requires a journal commit of the write operation to the primary of the set regardless of the level of replica acknowledged write concern. wtimeout This option specifies a time limit, in milliseconds, for the write concern. wtimeout is only applicable for w values greater than 1. wtimeout causes write operations to return with an error after the specified limit, even if the required write concern will eventually succeed. When these write operations return, MongoDB does not undo successful data modifications performed before the write concern exceeded the wtimeout time limit. If you do not specify the wtimeout option and the level of write concern is unachievable, the write operation will block indefinitely. Specifying a wtimeout value of 0 is equivalent to a write concern without the wtimeout option. See also: Write Concern Introduction (page 80) and Write Concern for Replica Sets (page 82). SQL to MongoDB Mapping Chart In addition to the charts that follow, you might want to consider the Frequently Asked Questions (page 743) section for a selection of common questions about MongoDB. 134 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 Terminology and Concepts The following table presents the various SQL terminology and concepts and the corresponding MongoDB terminology and concepts. SQL Terms/Concepts MongoDB Terms/Concepts database database table collection row document or BSON document column field index index table joins embedded documents and linking primary key Specify any unique column or column combination as primary key. primary key In MongoDB, the primary key is automatically set to the _id field. aggregation (e.g. group by) aggregation pipeline See the SQL to Aggregation Mapping Chart (page 476). Executables The following table presents some database executables and the corresponding MongoDB executables. This table is not meant to be exhaustive. MongoDB MySQL Oracle Informix DB2 Database Server mongod mysqld oracle IDS DB2 Server Database Client mongo mysql sqlplus DB-Access DB2 Client Examples The following table presents the various SQL statements and the corresponding MongoDB statements. The examples in the table assume the following conditions: • The SQL examples assume a table named users. • The MongoDB examples assume a collection named users that contain documents of the following prototype: { _id: ObjectId("509a8fb2f3f4948bd2f983a0"), user_id: "abc123", age: 55, status: 'A' } Create and Alter The following table presents the various SQL statements related to table-level actions and the corresponding MongoDB statements. 3.4. MongoDB CRUD Reference 135 MongoDB Documentation, Release 3.0.7 SQL Schema Statements MongoDB Schema Statements CREATE TABLE users ( id MEDIUMINT NOT NULL AUTO_INCREMENT, user_id Varchar(30), age Number, status char(1), PRIMARY KEY (id) ) Implicitly created on first insert() operation. The primary key _id is automatically added if _id field is not specified. db.users.insert( { user_id: "abc123", age: 55, status: "A" }) However, you can also explicitly create a collection: db.createCollection("users") ALTER TABLE users ADD join_date DATETIME Collections do not describe or enforce the structure of its documents; i.e. there is no structural alteration at the collection level. However, at the document level, update() operations can add fields to existing documents using the $set op- erator. db.users.update( { }, { $set: { join_date: new Date() } }, { multi: true } ) ALTER TABLE users DROP COLUMN join_date Collections do not describe or enforce the structure of its documents; i.e. there is no structural alteration at the collection level. However, at the document level, update() operations can remove fields from documents using the $unset operator. db.users.update( { }, { $unset: { join_date:""}}, { multi: true } ) CREATE INDEX idx_user_id_asc ON users(user_id) db.users.createIndex( { user_id:1}) CREATE INDEX idx_user_id_asc_age_desc ON users(user_id, age DESC) db.users.createIndex( { user_id:1, age:-1}) DROP TABLE users db.users.drop() For more information, see db.collection.insert(), db.createCollection(), db.collection.update(), $set, $unset, db.collection.createIndex(), indexes (page 485), db.collection.drop(), and Data Modeling Concepts (page 149). Insert The following table presents the various SQL statements related to inserting records into tables and the cor- responding MongoDB statements. 136 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 SQL INSERT Statements MongoDB insert() Statements INSERT INTO users(user_id, age, status) VALUES ("bcd001", 45, "A") db.users.insert( { user_id: "bcd001", age: 45, status: "A"} ) For more information, see db.collection.insert(). Select The following table presents the various SQL statements related to reading records from tables and the corre- sponding MongoDB statements. 3.4. MongoDB CRUD Reference 137 MongoDB Documentation, Release 3.0.7 SQL SELECT Statements MongoDB find() Statements SELECT * FROM users db.users.find() SELECT id, user_id, status FROM users db.users.find( { }, { user_id:1, status:1} ) SELECT user_id, status FROM users db.users.find( { }, { user_id:1, status:1, _id:0} ) SELECT * FROM users WHERE status= "A" db.users.find( { status: "A"} ) SELECT user_id, status FROM users WHERE status= "A" db.users.find( { status: "A"}, { user_id:1, status:1, _id:0} ) SELECT * FROM users WHERE status!= "A" db.users.find( { status: { $ne: "A"}} ) SELECT * FROM users WHERE status= "A" AND age= 50 db.users.find( { status: "A", age: 50} ) SELECT * FROM users WHERE status= "A" OR age= 50 db.users.find( { $or: [ { status: "A"}, { age: 50}]} ) SELECT * FROM users WHERE age> 25 db.users.find( { age: { $gt: 25}} ) SELECT * FROM users WHERE age< 25 db.users.find( { age: { $lt: 25}} ) SELECT * FROM users WHERE age> 25 AND age<= 50 db.users.find( { age: { $gt: 25, $lte: 50}} ) SELECT * FROM users WHERE user_id like "%bc%" db.users.find( { user_id: /bc/}) SELECT * FROM users WHERE user_id like "bc%" db.users.find( { user_id: /^bc/}) SELECT * FROM users WHERE status= "A" ORDERBY user_id ASC db.users.find( { status: "A" } ).sort( { user_id:1}) SELECT * FROM users WHERE status= "A" ORDERBY user_id DESC db.users.find( { status: "A" } ).sort( { user_id:-1}) SELECT COUNT(*) FROM users db.users.count() or db.users.find().count() SELECT COUNT(user_id) FROM users db.users.count( { user_id: { $exists: true }}) or db.users.find( { user_id: { $exists: true } } ).count() SELECT COUNT(*) FROM users WHERE age> 30 db.users.count( { age: { $gt: 30}}) or db.users.find( { age: { $gt: 30 } } ).count() SELECT DISTINCT(status) FROM users db.users.distinct( "status") SELECT * FROM users LIMIT 1 db.users.findOne() or db.users.find().limit(1) SELECT * FROM users LIMIT 5 SKIP 10 db.users.find().limit(5).skip(10) EXPLAIN SELECT * FROM users WHERE status= "A" db.users.find( { status: "A" } ).explain() 138 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 For more information, see db.collection.find(), db.collection.distinct(), db.collection.findOne(), $ne $and, $or, $gt, $lt, $exists, $lte, $regex, limit(), skip(), explain(), sort(), and count(). Update Records The following table presents the various SQL statements related to updating existing records in tables and the corresponding MongoDB statements. SQL Update Statements MongoDB update() Statements UPDATE users SET status= "C" WHERE age> 25 db.users.update( { age: { $gt: 25}}, { $set: { status: "C"}}, { multi: true } ) UPDATE users SET age= age+3 WHERE status= "A" db.users.update( { status: "A"}, { $inc: { age:3}}, { multi: true } ) For more information, see db.collection.update(), $set, $inc, and $gt. Delete Records The following table presents the various SQL statements related to deleting records from tables and the corresponding MongoDB statements. SQL Delete Statements MongoDB remove() Statements DELETE FROM users WHERE status= "D" db.users.remove( { status: "D"}) DELETE FROM users db.users.remove({}) For more information, see db.collection.remove(). Additional Resources • Transitioning from SQL to MongoDB (Presentation)19 • Best Practices for Migrating from RDBMS to MongoDB (Webinar)20 • SQL vs. MongoDB Day 1-221 • SQL vs. MongoDB Day 3-522 • MongoDB vs. SQL Day 1423 • MongoDB and MySQL Compared24 19http://www.mongodb.com/presentations/webinar-transitioning-sql-mongodb?jmp=docs 20http://www.mongodb.com/webinar/best-practices-migration?jmp=docs 21http://www.mongodb.com/blog/post/mongodb-vs-sql-day-1-2?jmp=docs 22http://www.mongodb.com/blog/post/mongodb-vs-sql-day-3-5?jmp=docs 23http://www.mongodb.com/blog/post/mongodb-vs-sql-day-14?jmp=docs 24http://www.mongodb.com/mongodb-and-mysql-compared?jmp=docs 3.4. MongoDB CRUD Reference 139 MongoDB Documentation, Release 3.0.7 • Quick Reference Cards25 • MongoDB Database Modernization Consulting Package26 The bios Example Collection The bios collection provides example data for experimenting with MongoDB. Many of this guide’s examples on insert, update and read operations create or query data from the bios collection. The following documents comprise the bios collection. In the examples, the data might be different, as the examples themselves make changes to the data. { "_id":1, "name":{ "first": "John", "last": "Backus" }, "birth": ISODate("1924-12-03T05:00:00Z"), "death": ISODate("2007-03-17T04:00:00Z"), "contribs":[ "Fortran", "ALGOL", "Backus-Naur Form", "FP" ], "awards":[ { "award": "W.W. McDowell Award", "year": 1967, "by": "IEEE Computer Society" }, { "award": "National Medal of Science", "year": 1975, "by": "National Science Foundation" }, { "award": "Turing Award", "year": 1977, "by": "ACM" }, { "award": "Draper Prize", "year": 1993, "by": "National Academy of Engineering" } ] } { "_id": ObjectId("51df07b094c6acd67e492f41"), "name":{ "first": "John", "last": "McCarthy" }, 25https://www.mongodb.com/lp/misc/quick-reference-cards?jmp=docs 26https://www.mongodb.com/products/consulting?jmp=docs#database_modernization 140 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 "birth": ISODate("1927-09-04T04:00:00Z"), "death": ISODate("2011-12-24T05:00:00Z"), "contribs":[ "Lisp", "Artificial Intelligence", "ALGOL" ], "awards":[ { "award": "Turing Award", "year": 1971, "by": "ACM" }, { "award": "Kyoto Prize", "year": 1988, "by": "Inamori Foundation" }, { "award": "National Medal of Science", "year": 1990, "by": "National Science Foundation" } ] } { "_id":3, "name":{ "first": "Grace", "last": "Hopper" }, "title": "Rear Admiral", "birth": ISODate("1906-12-09T05:00:00Z"), "death": ISODate("1992-01-01T05:00:00Z"), "contribs":[ "UNIVAC", "compiler", "FLOW-MATIC", "COBOL" ], "awards":[ { "award": "Computer Sciences Man of the Year", "year": 1969, "by": "Data Processing Management Association" }, { "award": "Distinguished Fellow", "year": 1973, "by": " British Computer Society" }, { "award": "W. W. McDowell Award", "year": 1976, "by": "IEEE Computer Society" }, { 3.4. MongoDB CRUD Reference 141 MongoDB Documentation, Release 3.0.7 "award": "National Medal of Technology", "year": 1991, "by": "United States" } ] } { "_id":4, "name":{ "first": "Kristen", "last": "Nygaard" }, "birth": ISODate("1926-08-27T04:00:00Z"), "death": ISODate("2002-08-10T04:00:00Z"), "contribs":[ "OOP", "Simula" ], "awards":[ { "award": "Rosing Prize", "year": 1999, "by": "Norwegian Data Association" }, { "award": "Turing Award", "year": 2001, "by": "ACM" }, { "award": "IEEE John von Neumann Medal", "year": 2001, "by": "IEEE" } ] } { "_id":5, "name":{ "first": "Ole-Johan", "last": "Dahl" }, "birth": ISODate("1931-10-12T04:00:00Z"), "death": ISODate("2002-06-29T04:00:00Z"), "contribs":[ "OOP", "Simula" ], "awards":[ { "award": "Rosing Prize", "year": 1999, "by": "Norwegian Data Association" }, { "award": "Turing Award", 142 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 "year": 2001, "by": "ACM" }, { "award": "IEEE John von Neumann Medal", "year": 2001, "by": "IEEE" } ] } { "_id":6, "name":{ "first": "Guido", "last": "van Rossum" }, "birth": ISODate("1956-01-31T05:00:00Z"), "contribs":[ "Python" ], "awards":[ { "award": "Award for the Advancement of Free Software", "year": 2001, "by": "Free Software Foundation" }, { "award": "NLUUG Award", "year": 2003, "by": "NLUUG" } ] } { "_id": ObjectId("51e062189c6ae665454e301d"), "name":{ "first": "Dennis", "last": "Ritchie" }, "birth": ISODate("1941-09-09T04:00:00Z"), "death": ISODate("2011-10-12T04:00:00Z"), "contribs":[ "UNIX", "C" ], "awards":[ { "award": "Turing Award", "year": 1983, "by": "ACM" }, { "award": "National Medal of Technology", "year": 1998, "by": "United States" }, 3.4. MongoDB CRUD Reference 143 MongoDB Documentation, Release 3.0.7 { "award": "Japan Prize", "year": 2011, "by": "The Japan Prize Foundation" } ] } { "_id":8, "name":{ "first": "Yukihiro", "aka": "Matz", "last": "Matsumoto" }, "birth": ISODate("1965-04-14T04:00:00Z"), "contribs":[ "Ruby" ], "awards":[ { "award": "Award for the Advancement of Free Software", "year": "2011", "by": "Free Software Foundation" } ] } { "_id":9, "name":{ "first": "James", "last": "Gosling" }, "birth": ISODate("1955-05-19T04:00:00Z"), "contribs":[ "Java" ], "awards":[ { "award": "The Economist Innovation Award", "year": 2002, "by": "The Economist" }, { "award": "Officer of the Order of Canada", "year": 2007, "by": "Canada" } ] } { "_id": 10, "name":{ "first": "Martin", "last": "Odersky" }, 144 Chapter 3. MongoDB CRUD Operations MongoDB Documentation, Release 3.0.7 "contribs":[ "Scala" ] } 3.4. MongoDB CRUD Reference 145 MongoDB Documentation, Release 3.0.7 146 Chapter 3. MongoDB CRUD Operations CHAPTER 4 Data Models Data in MongoDB has a flexible schema. Collections do not enforce document structure. This flexibility gives you data-modeling choices to match your application and its performance requirements. Data Modeling Introduction (page 147) An introduction to data modeling in MongoDB. Data Modeling Concepts (page 149) The core documentation detailing the decisions you must make when determin- ing a data model, and discussing considerations that should be taken into account. Data Model Examples and Patterns (page 155) Examples of possible data models that you can use to structure your MongoDB documents. Data Model Reference (page 172) Reference material for data modeling for developers of MongoDB applications. 4.1 Data Modeling Introduction Data in MongoDB has a flexible schema. Unlike SQL databases, where you must determine and declare a table’s schema before inserting data, MongoDB’s collections do not enforce document structure. This flexibility facilitates the mapping of documents to an entity or an object. Each document can match the data fields of the represented entity, even if the data has substantial variation. In practice, however, the documents in a collection share a similar structure. The key challenge in data modeling is balancing the needs of the application, the performance characteristics of the database engine, and the data retrieval patterns. When designing data models, always consider the application usage of the data (i.e. queries, updates, and processing of the data) as well as the inherent structure of the data itself. 4.1.1 Document Structure The key decision in designing data models for MongoDB applications revolves around the structure of documents and how the application represents relationships between data. There are two tools that allow applications to represent these relationships: references and embedded documents. References References store the relationships between data by including links or references from one document to another. Appli- cations can resolve these references (page 175) to access the related data. Broadly, these are normalized data models. See Normalized Data Models (page 151) for the strengths and weaknesses of using references. 147 MongoDB Documentation, Release 3.0.7 Embedded Data Embedded documents capture relationships between data by storing related data in a single document structure. Mon- goDB documents make it possible to embed document structures in a field or array within a document. These denor- malized data models allow applications to retrieve and manipulate related data in a single database operation. See Embedded Data Models (page 150) for the strengths and weaknesses of embedding documents. 4.1.2 Atomicity of Write Operations In MongoDB, write operations are atomic at the document level, and no single write operation can atomically affect more than one document or more than one collection. A denormalized data model with embedded data combines all related data for a represented entity in a single document. This facilitates atomic write operations since a single write operation can insert or update the data for an entity. Normalizing the data would split the data across multiple collections and would require multiple write operations that are not atomic collectively. However, schemas that facilitate atomic writes may limit ways that applications can use the data or may limit ways to modify applications. The Atomicity Considerations (page 152) documentation describes the challenge of designing a schema that balances flexibility and atomicity. 4.1.3 Document Growth Some updates, such as pushing elements to an array or adding new fields, increase a document’s size. For the MMAPv1 storage engine, if the document size exceeds the allocated space for that document, MongoDB relocates the document on disk. When using the MMAPv1 storage engine, growth consideration can affect the decision to normalize or denormalize data. See Document Growth Considerations (page 152) for more about planning for and managing document growth for MMAPv1. 148 Chapter 4. Data Models MongoDB Documentation, Release 3.0.7 4.1.4 Data Use and Performance When designing a data model, consider how applications will use your database. For instance, if your application only uses recently inserted documents, consider using Capped Collections (page 213). Or if your application needs are mainly read operations to a collection, adding indexes to support common queries can improve performance. See Operational Factors and Data Models (page 152) for more information on these and other operational considera- tions that affect data model designs. 4.1.5 Additional Resources • Thinking in Documents Part 1 (Blog Post)1 4.2 Data Modeling Concepts Consider the following aspects of data modeling in MongoDB: Data Model Design (page 150) Presents the different strategies that you can choose from when determining your data model, their strengths and their weaknesses. Operational Factors and Data Models (page 152) Details features you should keep in mind when designing your data model, such as lifecycle management, indexing, horizontal scalability, and document growth. GridFS (page 154) GridFS is a specification for storing documents that exceeds the BSON-document size limit of 16MB. For a general introduction to data modeling in MongoDB, see the Data Modeling Introduction (page 147). For example data models, see Data Modeling Examples and Patterns (page 155). 1https://www.mongodb.com/blog/post/thinking-documents-part-1?jmp=docs 4.2. Data Modeling Concepts 149 MongoDB Documentation, Release 3.0.7 4.2.1 Data Model Design Effective data models support your application needs. The key consideration for the structure of your documents is the decision to embed (page 150) or to use references (page 151). Embedded Data Models With MongoDB, you may embed related data in a single structure or document. These schema are generally known as “denormalized” models, and take advantage of MongoDB’s rich documents. Consider the following diagram: Embedded data models allow applications to store related pieces of information in the same database record. As a result, applications may need to issue fewer queries and updates to complete common operations. In general, use embedded data models when: • you have “contains” relationships between entities. See Model One-to-One Relationships with Embedded Doc- uments (page 156). • you have one-to-many relationships between entities. In these relationships the “many” or child documents always appear with or are viewed in the context of the “one” or parent documents. See Model One-to-Many Relationships with Embedded Documents (page 157). In general, embedding provides better performance for read operations, as well as the ability to request and retrieve related data in a single database operation. Embedded data models make it possible to update related data in a single atomic write operation. However, embedding related data in documents may lead to situations where documents grow after creation. With the MMAPv1 storage engine, document growth can impact write performance and lead to data fragmentation. In version 3.0.0, MongoDB uses Power of 2 Sized Allocations (page 93) as the default allocation strategy for MMAPv1 in order to account for document growth, minimizing the likelihood of data fragmentation. See Power of 2 Sized Allocations (page 93) for details. Furthermore, documents in MongoDB must be smaller than the maximum BSON document size. For bulk binary data, consider GridFS (page 154). 150 Chapter 4. Data Models MongoDB Documentation, Release 3.0.7 To interact with embedded documents, use dot notation to “reach into” embedded documents. See query for data in arrays (page 100) and query data in embedded documents (page 99) for more examples on accessing data in arrays and embedded documents. Normalized Data Models Normalized data models describe relationships using references (page 175) between documents. In general, use normalized data models: • when embedding would result in duplication of data but would not provide sufficient read performance advan- tages to outweigh the implications of the duplication. • to represent more complex many-to-many relationships. • to model large hierarchical data sets. References provides more flexibility than embedding. However, client-side applications must issue follow-up queries to resolve the references. In other words, normalized data models can require more round trips to the server. See Model One-to-Many Relationships with Document References (page 158) for an example of referencing. For examples of various tree models using references, see Model Tree Structures (page 160). Additional Resources • Thinking in Documents Part 1 (Blog Post)2 • Thinking in Documents (Presentation)3 2https://www.mongodb.com/blog/post/thinking-documents-part-1?jmp=docs 3http://www.mongodb.com/presentations/webinar-back-basics-1-thinking-documents?jmp=docs 4.2. Data Modeling Concepts 151 MongoDB Documentation, Release 3.0.7 • Schema Design for Time Series Data (Presentation)4 • Socialite, the Open Source Status Feed - Storing a Social Graph (Presentation)5 • MongoDB Rapid Start Consultation Services6 4.2.2 Operational Factors and Data Models Modeling application data for MongoDB depends on both the data itself, as well as the characteristics of MongoDB itself. For example, different data models may allow applications to use more efficient queries, increase the throughput of insert and update operations, or distribute activity to a sharded cluster more effectively. These factors are operational or address requirements that arise outside of the application but impact the performance of MongoDB based applications. When developing a data model, analyze all of your application’s read operations (page 62) and write operations (page 75) in conjunction with the following considerations. Document Growth Changed in version 3.0.0. Some updates to documents can increase the size of documents. These updates include pushing elements to an array (i.e. $push) and adding new fields to a document. When using the MMAPv1 storage engine, document growth can be a consideration for your data model. For MMAPv1, if the document size exceeds the allocated space for that document, MongoDB will relocate the docu- ment on disk. With MongoDB 3.0.0, however, the default use of the Power of 2 Sized Allocations (page 93) minimizes the occurrences of such re-allocations as well as allows for the effective reuse of the freed record space. When using MMAPv1, if your applications require updates that will frequently cause document growth to exceeds the current power of 2 allocation, you may want to refactor your data model to use references between data in distinct documents rather than a denormalized data model. You may also use a pre-allocation strategy to explicitly avoid document growth. Refer to the Pre-Aggregated Reports Use Case7 for an example of the pre-allocation approach to handling document growth. See Storage (page 91) for more information on MongoDB’s storage model and record allocation strategies. Atomicity In MongoDB, operations are atomic at the document level. No single write operation can change more than one document. Operations that modify more than a single document in a collection still operate on one document at a time. 8 Ensure that your application stores all fields with atomic dependency requirements in the same document. If the application can tolerate non-atomic updates for two pieces of data, you can store these data in separate documents. A data model that embeds related data in a single document facilitates these kinds of atomic operations. For data mod- els that store references between related pieces of data, the application must issue separate read and write operations to retrieve and modify these related pieces of data. See Model Data for Atomic Operations (page 168) for an example data model that provides atomic updates for a single document. 4http://www.mongodb.com/presentations/webinar-time-series-data-mongodb?jmp=docs 5http://www.mongodb.com/presentations/socialite-open-source-status-feed-part-2-managing-social-graph?jmp=docs 6https://www.mongodb.com/products/consulting?jmp=docs#rapid_start 7https://docs.mongodb.org/ecosystem/use-cases/pre-aggregated-reports 8 Document-level atomic operations include all operations within a single MongoDB document record: operations that affect multiple embedded documents within that single record are still atomic. 152 Chapter 4. Data Models MongoDB Documentation, Release 3.0.7 Sharding MongoDB uses sharding to provide horizontal scaling. These clusters support deployments with large data sets and high-throughput operations. Sharding allows users to partition a collection within a database to distribute the collec- tion’s documents across a number of mongod instances or shards. To distribute data and application traffic in a sharded collection, MongoDB uses the shard key (page 674). Selecting the proper shard key (page 674) has significant implications for performance, and can enable or prevent query isolation and increased write capacity. It is important to consider carefully the field or fields to use as the shard key. See Sharding Introduction (page 661) and Shard Keys (page 674) for more information. Indexes Use indexes to improve performance for common queries. Build indexes on fields that appear often in queries and for all operations that return sorted results. MongoDB automatically creates a unique index on the _id field. As you create indexes, consider the following behaviors of indexes: • Each index requires at least 8KB of data space. • Adding an index has some negative performance impact for write operations. For collections with high write- to-read ratio, indexes are expensive since each insert must also update any indexes. • Collections with high read-to-write ratio often benefit from additional indexes. Indexes do not affect un-indexed read operations. • When active, each index consumes disk space and memory. This usage can be significant and should be tracked for capacity planning, especially for concerns over working set size. See Indexing Strategies (page 547) for more information on indexes as well as Analyze Query Performance (page 114). Additionally, the MongoDB database profiler (page 232) may help identify inefficient queries. Large Number of Collections In certain situations, you might choose to store related information in several collections rather than in a single collec- tion. Consider a sample collection logs that stores log documents for various environment and applications. The logs collection contains documents of the following form: { log: "dev", ts: ..., info: ... } { log: "debug", ts: ..., info: ...} If the total number of documents is low, you may group documents into collection by type. For logs, consider main- taining distinct log collections, such as logs_dev and logs_debug. The logs_dev collection would contain only the documents related to the dev environment. Generally, having a large number of collections has no significant performance penalty and results in very good performance. Distinct collections are very important for high-throughput batch processing. When using models that have a large number of collections, consider the following behaviors: • Each collection has a certain minimum overhead of a few kilobytes. • Each index, including the index on _id, requires at least 8KB of data space. • For each database, a single namespace file (i.e. .ns) stores all meta-data for that database, and each index and collection has its own entry in the namespace file. MongoDB places limits on the size of namespace files. 4.2. Data Modeling Concepts 153 MongoDB Documentation, Release 3.0.7 • MongoDB using the mmapv1 storage engine has limits on the number of namespaces. You may wish to know the current number of namespaces in order to determine how many additional namespaces the database can support. To get the current number of namespaces, run the following in the mongo shell: db.system.namespaces.count() The limit on the number of namespaces depend on the .ns size. The namespace file defaults to 16 MB. To change the size of the new namespace file, start the server with the option --nssize . For existing databases, after starting up the server with --nssize, run the db.repairDatabase() com- mand from the mongo shell. For impacts and considerations on running db.repairDatabase(), see repairDatabase. Data Lifecycle Management Data modeling decisions should take data lifecycle management into consideration. The Time to Live or TTL feature (page 215) of collections expires documents after a period of time. Consider using the TTL feature if your application requires some data to persist in the database for a limited period of time. Additionally, if your application only uses recently inserted documents, consider Capped Collections (page 213). Capped collections provide first-in-first-out (FIFO) management of inserted documents and efficiently support opera- tions that insert and read documents based on insertion order. 4.2.3 GridFS GridFS is a specification for storing and retrieving files that exceed the BSON-document size limit of 16MB. Instead of storing a file in a single document, GridFS divides a file into parts, or chunks, 9 and stores each of those chunks as a separate document. By default GridFS limits chunk size to 255k. GridFS uses two collections to store files. One collection stores the file chunks, and the other stores file metadata. When you query a GridFS store for a file, the driver or client will reassemble the chunks as needed. You can perform range queries on files stored through GridFS. You also can access information from arbitrary sections of files, which allows you to “skip” into the middle of a video or audio file. GridFS is useful not only for storing files that exceed 16MB but also for storing any files for which you want access without having to load the entire file into memory. For more information on the indications of GridFS, see When should I use GridFS? (page 749). Changed in version 2.4.10: The default chunk size changed from 256k to 255k. Implement GridFS To store and retrieve files using GridFS, use either of the following: • A MongoDB driver. See the drivers documentation for information on using GridFS with your driver. • The mongofiles command-line tool in the mongo shell. See the mongofiles reference for complete documentation. 9 The use of the term chunks in the context of GridFS is not related to the use of the term chunks in the context of sharding. 154 Chapter 4. Data Models MongoDB Documentation, Release 3.0.7 GridFS Collections GridFS stores files in two collections: • chunks stores the binary chunks. For details, see The chunks Collection (page 179). • files stores the file’s metadata. For details, see The files Collection (page 179). GridFS places the collections in a common bucket by prefixing each with the bucket name. By default, GridFS uses two collections with names prefixed by fs bucket: • fs.files • fs.chunks You can choose a different bucket name than fs, and create multiple buckets in a single database. Each document in the chunks collection represents a distinct chunk of a file as represented in the GridFS store. Each chunk is identified by its unique ObjectId stored in its _id field. For descriptions of all fields in the chunks and files collections, see GridFS Reference (page 178). GridFS Index GridFS uses a unique, compound index on the chunks collection for the files_id and n fields. The files_id field contains the _id of the chunk’s “parent” document. The n field contains the sequence number of the chunk. GridFS numbers all chunks, starting with 0. For descriptions of the documents and fields in the chunks collection, see GridFS Reference (page 178). The GridFS index allows efficient retrieval of chunks using the files_id and n values, as shown in the following example: cursor= db.fs.chunks.find({files_id: myFileID}).sort({n:1}); See the relevant driver documentation for the specific behavior of your GridFS application. If your driver does not create this index, issue the following operation using the mongo shell: db.fs.chunks.createIndex( { files_id:1, n:1 }, { unique: true } ); Additional Resources • Building MongoDB Applications with Binary Files Using GridFS: Part 110 • Building MongoDB Applications with Binary Files Using GridFS: Part 211 4.3 Data Model Examples and Patterns The following documents provide overviews of various data modeling patterns and common schema design consider- ations: Model Relationships Between Documents (page 156) Examples for modeling relationships between documents. Model One-to-One Relationships with Embedded Documents (page 156) Presents a data model that uses em- bedded documents (page 150) to describe one-to-one relationships between connected data. 10http://www.mongodb.com/blog/post/building-mongodb-applications-binary-files-using-gridfs-part-1?jmp=docs 11http://www.mongodb.com/blog/post/building-mongodb-applications-binary-files-using-gridfs-part-2?jmp=docs 4.3. Data Model Examples and Patterns 155 MongoDB Documentation, Release 3.0.7 Model One-to-Many Relationships with Embedded Documents (page 157) Presents a data model that uses embedded documents (page 150) to describe one-to-many relationships between connected data. Model One-to-Many Relationships with Document References (page 158) Presents a data model that uses references (page 151) to describe one-to-many relationships between documents. Model Tree Structures (page 160) Examples for modeling tree structures. Model Tree Structures with Parent References (page 161) Presents a data model that organizes documents in a tree-like structure by storing references (page 151) to “parent” nodes in “child” nodes. Model Tree Structures with Child References (page 162) Presents a data model that organizes documents in a tree-like structure by storing references (page 151) to “child” nodes in “parent” nodes. See Model Tree Structures (page 160) for additional examples of data models for tree structures. Model Specific Application Contexts (page 168) Examples for models for specific application contexts. Model Data for Atomic Operations (page 168) Illustrates how embedding fields related to an atomic update within the same document ensures that the fields are in sync. Model Data to Support Keyword Search (page 169) Describes one method for supporting keyword search by storing keywords in an array in the same document as the text field. Combined with a multi-key index, this pattern can support application’s keyword search operations. 4.3.1 Model Relationships Between Documents Model One-to-One Relationships with Embedded Documents (page 156) Presents a data model that uses embedded documents (page 150) to describe one-to-one relationships between connected data. Model One-to-Many Relationships with Embedded Documents (page 157) Presents a data model that uses embed- ded documents (page 150) to describe one-to-many relationships between connected data. Model One-to-Many Relationships with Document References (page 158) Presents a data model that uses refer- ences (page 151) to describe one-to-many relationships between documents. Model One-to-One Relationships with Embedded Documents Overview Data in MongoDB has a flexible schema. Collections do not enforce document structure. Decisions that affect how you model data can affect application performance and database capacity. See Data Modeling Concepts (page 149) for a full high level overview of data modeling in MongoDB. This document describes a data model that uses embedded (page 150) documents to describe relationships between connected data. Pattern Consider the following example that maps patron and address relationships. The example illustrates the advantage of embedding over referencing if you need to view one data entity in context of the other. In this one-to-one relationship between patron and address data, the address belongs to the patron. In the normalized data model, the address document contains a reference to the patron document. 156 Chapter 4. Data Models MongoDB Documentation, Release 3.0.7 { _id: "joe", name: "Joe Bookreader" } { patron_id: "joe", street: "123 Fake Street", city: "Faketon", state: "MA", zip: "12345" } If the address data is frequently retrieved with the name information, then with referencing, your application needs to issue multiple queries to resolve the reference. The better data model would be to embed the address data in the patron data, as in the following document: { _id: "joe", name: "Joe Bookreader", address:{ street: "123 Fake Street", city: "Faketon", state: "MA", zip: "12345" } } With the embedded data model, your application can retrieve the complete patron information with one query. Model One-to-Many Relationships with Embedded Documents Overview Data in MongoDB has a flexible schema. Collections do not enforce document structure. Decisions that affect how you model data can affect application performance and database capacity. See Data Modeling Concepts (page 149) for a full high level overview of data modeling in MongoDB. This document describes a data model that uses embedded (page 150) documents to describe relationships between connected data. Pattern Consider the following example that maps patron and multiple address relationships. The example illustrates the advantage of embedding over referencing if you need to view many data entities in context of another. In this one-to- many relationship between patron and address data, the patron has multiple address entities. In the normalized data model, the address documents contain a reference to the patron document. { _id: "joe", name: "Joe Bookreader" } { patron_id: "joe", 4.3. Data Model Examples and Patterns 157 MongoDB Documentation, Release 3.0.7 street: "123 Fake Street", city: "Faketon", state: "MA", zip: "12345" } { patron_id: "joe", street: "1 Some Other Street", city: "Boston", state: "MA", zip: "12345" } If your application frequently retrieves the address data with the name information, then your application needs to issue multiple queries to resolve the references. A more optimal schema would be to embed the address data entities in the patron data, as in the following document: { _id: "joe", name: "Joe Bookreader", addresses:[ { street: "123 Fake Street", city: "Faketon", state: "MA", zip: "12345" }, { street: "1 Some Other Street", city: "Boston", state: "MA", zip: "12345" } ] } With the embedded data model, your application can retrieve the complete patron information with one query. Model One-to-Many Relationships with Document References Overview Data in MongoDB has a flexible schema. Collections do not enforce document structure. Decisions that affect how you model data can affect application performance and database capacity. See Data Modeling Concepts (page 149) for a full high level overview of data modeling in MongoDB. This document describes a data model that uses references (page 151) between documents to describe relationships between connected data. Pattern Consider the following example that maps publisher and book relationships. The example illustrates the advantage of referencing over embedding to avoid repetition of the publisher information. 158 Chapter 4. Data Models MongoDB Documentation, Release 3.0.7 Embedding the publisher document inside the book document would lead to repetition of the publisher data, as the following documents show: { title: "MongoDB: The Definitive Guide", author:[ "Kristina Chodorow", "Mike Dirolf"], published_date: ISODate("2010-09-24"), pages: 216, language: "English", publisher:{ name: "O'Reilly Media", founded: 1980, location: "CA" } } { title: "50 Tips and Tricks for MongoDB Developer", author: "Kristina Chodorow", published_date: ISODate("2011-05-06"), pages: 68, language: "English", publisher:{ name: "O'Reilly Media", founded: 1980, location: "CA" } } To avoid repetition of the publisher data, use references and keep the publisher information in a separate collection from the book collection. When using references, the growth of the relationships determine where to store the reference. If the number of books per publisher is small with limited growth, storing the book reference inside the publisher document may sometimes be useful. Otherwise, if the number of books per publisher is unbounded, this data model would lead to mutable, growing arrays, as in the following example: { name: "O'Reilly Media", founded: 1980, location: "CA", books:[12346789, 234567890, ...] } { _id: 123456789, title: "MongoDB: The Definitive Guide", author:[ "Kristina Chodorow", "Mike Dirolf"], published_date: ISODate("2010-09-24"), pages: 216, language: "English" } { _id: 234567890, title: "50 Tips and Tricks for MongoDB Developer", author: "Kristina Chodorow", published_date: ISODate("2011-05-06"), pages: 68, 4.3. Data Model Examples and Patterns 159 MongoDB Documentation, Release 3.0.7 language: "English" } To avoid mutable, growing arrays, store the publisher reference inside the book document: { _id: "oreilly", name: "O'Reilly Media", founded: 1980, location: "CA" } { _id: 123456789, title: "MongoDB: The Definitive Guide", author:[ "Kristina Chodorow", "Mike Dirolf"], published_date: ISODate("2010-09-24"), pages: 216, language: "English", publisher_id: "oreilly" } { _id: 234567890, title: "50 Tips and Tricks for MongoDB Developer", author: "Kristina Chodorow", published_date: ISODate("2011-05-06"), pages: 68, language: "English", publisher_id: "oreilly" } 4.3.2 Model Tree Structures MongoDB allows various ways to use tree data structures to model large hierarchical or nested data relationships. Model Tree Structures with Parent References (page 161) Presents a data model that organizes documents in a tree- like structure by storing references (page 151) to “parent” nodes in “child” nodes. Model Tree Structures with Child References (page 162) Presents a data model that organizes documents in a tree- like structure by storing references (page 151) to “child” nodes in “parent” nodes. Model Tree Structures with an Array of Ancestors (page 164) Presents a data model that organizes documents in a tree-like structure by storing references (page 151) to “parent” nodes and an array that stores all ancestors. Model Tree Structures with Materialized Paths (page 165) Presents a data model that organizes documents in a tree- like structure by storing full relationship paths between documents. In addition to the tree node, each document stores the _id of the nodes ancestors or path as a string. Model Tree Structures with Nested Sets (page 167) Presents a data model that organizes documents in a tree-like structure using the Nested Sets pattern. This optimizes discovering subtrees at the expense of tree mutability. 160 Chapter 4. Data Models MongoDB Documentation, Release 3.0.7 Model Tree Structures with Parent References Overview Data in MongoDB has a flexible schema. Collections do not enforce document structure. Decisions that affect how you model data can affect application performance and database capacity. See Data Modeling Concepts (page 149) for a full high level overview of data modeling in MongoDB. This document describes a data model that describes a tree-like structure in MongoDB documents by storing references (page 151) to “parent” nodes in children nodes. Pattern The Parent References pattern stores each tree node in a document; in addition to the tree node, the document stores the id of the node’s parent. Consider the following hierarchy of categories: The following example models the tree using Parent References, storing the reference to the parent category in the field parent: db.categories.insert( { _id: "MongoDB", parent: "Databases"}) db.categories.insert( { _id: "dbm", parent: "Databases"}) db.categories.insert( { _id: "Databases", parent: "Programming"}) db.categories.insert( { _id: "Languages", parent: "Programming"}) 4.3. Data Model Examples and Patterns 161 MongoDB Documentation, Release 3.0.7 db.categories.insert( { _id: "Programming", parent: "Books"}) db.categories.insert( { _id: "Books", parent: null }) • The query to retrieve the parent of a node is fast and straightforward: db.categories.findOne( { _id: "MongoDB" } ).parent • You can create an index on the field parent to enable fast search by the parent node: db.categories.createIndex( { parent:1}) • You can query by the parent field to find its immediate children nodes: db.categories.find( { parent: "Databases"}) The Parent Links pattern provides a simple solution to tree storage but requires multiple queries to retrieve subtrees. Model Tree Structures with Child References Overview Data in MongoDB has a flexible schema. Collections do not enforce document structure. Decisions that affect how you model data can affect application performance and database capacity. See Data Modeling Concepts (page 149) for a full high level overview of data modeling in MongoDB. This document describes a data model that describes a tree-like structure in MongoDB documents by storing references (page 151) in the parent-nodes to children nodes. 162 Chapter 4. Data Models MongoDB Documentation, Release 3.0.7 Pattern The Child References pattern stores each tree node in a document; in addition to the tree node, document stores in an array the id(s) of the node’s children. Consider the following hierarchy of categories: The following example models the tree using Child References, storing the reference to the node’s children in the field children: db.categories.insert( { _id: "MongoDB", children:[]}) db.categories.insert( { _id: "dbm", children:[]}) db.categories.insert( { _id: "Databases", children:[ "MongoDB", "dbm"]}) db.categories.insert( { _id: "Languages", children:[]}) db.categories.insert( { _id: "Programming", children:[ "Databases", "Languages"]}) db.categories.insert( { _id: "Books", children:[ "Programming"]}) • The query to retrieve the immediate children of a node is fast and straightforward: db.categories.findOne( { _id: "Databases" } ).children • You can create an index on the field children to enable fast search by the child nodes: db.categories.createIndex( { children:1}) • You can query for a node in the children field to find its parent node as well as its siblings: 4.3. Data Model Examples and Patterns 163 MongoDB Documentation, Release 3.0.7 db.categories.find( { children: "MongoDB"}) The Child References pattern provides a suitable solution to tree storage as long as no operations on subtrees are necessary. This pattern may also provide a suitable solution for storing graphs where a node may have multiple parents. Model Tree Structures with an Array of Ancestors Overview Data in MongoDB has a flexible schema. Collections do not enforce document structure. Decisions that affect how you model data can affect application performance and database capacity. See Data Modeling Concepts (page 149) for a full high level overview of data modeling in MongoDB. This document describes a data model that describes a tree-like structure in MongoDB documents using references (page 151) to parent nodes and an array that stores all ancestors. Pattern The Array of Ancestors pattern stores each tree node in a document; in addition to the tree node, document stores in an array the id(s) of the node’s ancestors or path. Consider the following hierarchy of categories: 164 Chapter 4. Data Models MongoDB Documentation, Release 3.0.7 The following example models the tree using Array of Ancestors. In addition to the ancestors field, these docu- ments also store the reference to the immediate parent category in the parent field: db.categories.insert( { _id: "MongoDB", ancestors:[ "Books", "Programming", "Databases" ], parent: "Databases"}) db.categories.insert( { _id: "dbm", ancestors:[ "Books", "Programming", "Databases" ], parent: "Databases"}) db.categories.insert( { _id: "Databases", ancestors:[ "Books", "Programming" ], parent: "Programming"}) db.categories.insert( { _id: "Languages", ancestors:[ "Books", "Programming" ], parent: "Programming"}) db.categories.insert( { _id: "Programming", ancestors:[ "Books" ], parent: "Books"}) db.categories.insert( { _id: "Books", ancestors: [ ], parent: null }) • The query to retrieve the ancestors or path of a node is fast and straightforward: db.categories.findOne( { _id: "MongoDB" } ).ancestors • You can create an index on the field ancestors to enable fast search by the ancestors nodes: db.categories.createIndex( { ancestors:1}) • You can query by the field ancestors to find all its descendants: db.categories.find( { ancestors: "Programming"}) The Array of Ancestors pattern provides a fast and efficient solution to find the descendants and the ancestors of a node by creating an index on the elements of the ancestors field. This makes Array of Ancestors a good choice for working with subtrees. The Array of Ancestors pattern is slightly slower than the Materialized Paths (page 165) pattern but is more straight- forward to use. Model Tree Structures with Materialized Paths Overview Data in MongoDB has a flexible schema. Collections do not enforce document structure. Decisions that affect how you model data can affect application performance and database capacity. See Data Modeling Concepts (page 149) for a full high level overview of data modeling in MongoDB. This document describes a data model that describes a tree-like structure in MongoDB documents by storing full relationship paths between documents. Pattern The Materialized Paths pattern stores each tree node in a document; in addition to the tree node, document stores as a string the id(s) of the node’s ancestors or path. Although the Materialized Paths pattern requires additional steps of working with strings and regular expressions, the pattern also provides more flexibility in working with the path, such as finding nodes by partial paths. Consider the following hierarchy of categories: The following example models the tree using Materialized Paths, storing the path in the field path; the path string uses the comma , as a delimiter: db.categories.insert( { _id: "Books", path: null }) db.categories.insert( { _id: "Programming", path: ",Books,"}) db.categories.insert( { _id: "Databases", path: ",Books,Programming,"}) db.categories.insert( { _id: "Languages", path: ",Books,Programming,"}) db.categories.insert( { _id: "MongoDB", path: ",Books,Programming,Databases,"}) db.categories.insert( { _id: "dbm", path: ",Books,Programming,Databases,"}) 4.3. Data Model Examples and Patterns 165 MongoDB Documentation, Release 3.0.7 • You can query to retrieve the whole tree, sorting by the field path: db.categories.find().sort( { path:1}) • You can use regular expressions on the path field to find the descendants of Programming: db.categories.find( { path: /,Programming,/}) • You can also retrieve the descendants of Books where the Books is also at the topmost level of the hierarchy: db.categories.find( { path: /^,Books,/}) • To create an index on the field path use the following invocation: db.categories.createIndex( { path:1}) This index may improve performance depending on the query: – For queries from the root Books sub-tree (e.g. https://docs.mongodb.org/manual/^,Books,/ or https://docs.mongodb.org/manual/^,Books,Programming,/), an index on the path field improves the query performance significantly. – For queries of sub-trees where the path from the root is not provided in the query (e.g. https://docs.mongodb.org/manual/,Databases,/), or similar queries of sub-trees, where the node might be in the middle of the indexed string, the query must inspect the entire index. For these queries an index may provide some performance improvement if the index is significantly smaller than the entire collection. 166 Chapter 4. Data Models MongoDB Documentation, Release 3.0.7 Model Tree Structures with Nested Sets Overview Data in MongoDB has a flexible schema. Collections do not enforce document structure. Decisions that affect how you model data can affect application performance and database capacity. See Data Modeling Concepts (page 149) for a full high level overview of data modeling in MongoDB. This document describes a data model that describes a tree like structure that optimizes discovering subtrees at the expense of tree mutability. Pattern The Nested Sets pattern identifies each node in the tree as stops in a round-trip traversal of the tree. The application visits each node in the tree twice; first during the initial trip, and second during the return trip. The Nested Sets pattern stores each tree node in a document; in addition to the tree node, document stores the id of node’s parent, the node’s initial stop in the left field, and its return stop in the right field. Consider the following hierarchy of categories: The following example models the tree using Nested Sets: db.categories.insert( { _id: "Books", parent:0, left:1, right: 12}) db.categories.insert( { _id: "Programming", parent: "Books", left:2, right: 11}) db.categories.insert( { _id: "Languages", parent: "Programming", left:3, right:4}) db.categories.insert( { _id: "Databases", parent: "Programming", left:5, right: 10}) db.categories.insert( { _id: "MongoDB", parent: "Databases", left:6, right:7}) db.categories.insert( { _id: "dbm", parent: "Databases", left:8, right:9}) You can query to retrieve the descendants of a node: 4.3. Data Model Examples and Patterns 167 MongoDB Documentation, Release 3.0.7 var databaseCategory= db.categories.findOne( { _id: "Databases"}); db.categories.find( { left: { $gt: databaseCategory.left }, right: { $lt: databaseCategory.right } } ); The Nested Sets pattern provides a fast and efficient solution for finding subtrees but is inefficient for modifying the tree structure. As such, this pattern is best for static trees that do not change. 4.3.3 Model Specific Application Contexts Model Data for Atomic Operations (page 168) Illustrates how embedding fields related to an atomic update within the same document ensures that the fields are in sync. Model Data to Support Keyword Search (page 169) Describes one method for supporting keyword search by storing keywords in an array in the same document as the text field. Combined with a multi-key index, this pattern can support application’s keyword search operations. Model Monetary Data (page 170) Describes two methods to model monetary data in MongoDB. Model Time Data (page 172) Describes how to deal with local time in MongoDB. Model Data for Atomic Operations Pattern In MongoDB, write operations, e.g. db.collection.update(), db.collection.findAndModify(), db.collection.remove(), are atomic on the level of a single document. For fields that must be updated to- gether, embedding the fields within the same document ensures that the fields can be updated atomically. For example, consider a situation where you need to maintain information on books, including the number of copies available for checkout as well as the current checkout information. The available copies of the book and the checkout information should be in sync. As such, embedding the available field and the checkout field within the same document ensures that you can update the two fields atomically. { _id: 123456789, title: "MongoDB: The Definitive Guide", author:[ "Kristina Chodorow", "Mike Dirolf"], published_date: ISODate("2010-09-24"), pages: 216, language: "English", publisher_id: "oreilly", available:3, checkout: [ { by: "joe", date: ISODate("2012-10-15")}] } Then to update with new checkout information, you can use the db.collection.update() method to atomically update both the available field and the checkout field: db.books.update ( { _id: 123456789, available: { $gt:0}}, { $inc: { available:-1}, $push: { checkout: { by: "abc", date: new Date() } } } ) 168 Chapter 4. Data Models MongoDB Documentation, Release 3.0.7 The operation returns a WriteResult() object that contains information on the status of the operation: WriteResult({ "nMatched":1, "nUpserted":0, "nModified":1}) The nMatched field shows that 1 document matched the update condition, and nModified shows that the operation updated 1 document. If no document matched the update condition, then nMatched and nModified would be 0 and would indicate that you could not check out the book. Model Data to Support Keyword Search Note: Keyword search is not the same as text search or full text search, and does not provide stemming or other text-processing features. See the Limitations of Keyword Indexes (page 170) section for more information. In 2.4, MongoDB provides a text search feature. See Text Indexes (page 500) for more information. If your application needs to perform queries on the content of a field that holds text you can perform exact matches on the text or use $regex to use regular expression pattern matches. However, for many operations on text, these methods do not satisfy application requirements. This pattern describes one method for supporting keyword search using MongoDB to support application search functionality, that uses keywords stored in an array in the same document as the text field. Combined with a multi-key index (page 491), this pattern can support application’s keyword search operations. Pattern To add structures to your document to support keyword-based queries, create an array field in your documents and add the keywords as strings in the array. You can then create a multi-key index (page 491) on the array and create queries that select values from the array. Example Given a collection of library volumes that you want to provide topic-based search. For each volume, you add the array topics, and you add as many keywords as needed for a given volume. For the Moby-Dick volume you might have the following document: { title: "Moby-Dick", author: "Herman Melville", published: 1851, ISBN: 0451526996, topics:[ "whaling", "allegory", "revenge", "American", "novel", "nautical", "voyage", "Cape Cod"] } You then create a multi-key index on the topics array: db.volumes.createIndex( { topics:1}) The multi-key index creates separate index entries for each keyword in the topics array. For example the index contains one entry for whaling and another for allegory. You then query based on the keywords. For example: db.volumes.findOne( { topics: "voyage" }, { title:1}) 4.3. Data Model Examples and Patterns 169 MongoDB Documentation, Release 3.0.7 Note: An array with a large number of elements, such as one with several hundreds or thousands of keywords will incur greater indexing costs on insertion. Limitations of Keyword Indexes MongoDB can support keyword searches using specific data models and multi-key indexes (page 491); however, these keyword indexes are not sufficient or comparable to full-text products in the following respects: • Stemming. Keyword queries in MongoDB can not parse keywords for root or related words. • Synonyms. Keyword-based search features must provide support for synonym or related queries in the applica- tion layer. • Ranking. The keyword look ups described in this document do not provide a way to weight results. • Asynchronous Indexing. MongoDB builds indexes synchronously, which means that the indexes used for key- word indexes are always current and can operate in real-time. However, asynchronous bulk indexes may be more efficient for some kinds of content and workloads. Model Monetary Data Overview MongoDB stores numeric data as either IEEE 754 standard 64-bit floating point numbers or as 32-bit or 64-bit signed integers. Applications that handle monetary data often require capturing fractional units of currency. However, arith- metic on floating point numbers, as implemented in modern hardware, often does not conform to requirements for monetary arithmetic. In addition, some fractional numeric quantities, such as one third and one tenth, have no exact representation in binary floating point numbers. Note: Arithmetic mentioned on this page refers to server-side arithmetic performed by mongod or mongos, and not to client-side arithmetic. This document describes two ways to model monetary data in MongoDB: • Exact Precision (page 171) which multiplies the monetary value by a power of 10. • Arbitrary Precision (page 171) which uses two fields for the value: one field to store the exact monetary value as a non-numeric and another field to store a floating point approximation of the value. Use Cases for Exact Precision Model If you regularly need to perform server-side arithmetic on monetary data, the exact precision model may be appropriate. For instance: • If you need to query the database for exact, mathematically valid matches, use Exact Precision (page 171). • If you need to be able to do server-side arithmetic, e.g., $inc, $mul, and aggregation framework arithmetic, use Exact Precision (page 171). 170 Chapter 4. Data Models MongoDB Documentation, Release 3.0.7 Use Cases for Arbitrary Precision Model If there is no need to perform server-side arithmetic on monetary data, modeling monetary data using the arbitrary precision model may be suitable. For instance: • If you need to handle arbitrary or unforeseen number of precision, see Arbitrary Precision (page 171). • If server-side approximations are sufficient, possibly with client-side post-processing, see Arbitrary Precision (page 171). Exact Precision To model monetary data using the exact precision model: 1. Determine the maximum precision needed for the monetary value. For example, your application may require precision down to the tenth of one cent for monetary values in USD currency. 2. Convert the monetary value into an integer by multiplying the value by a power of 10 that ensures the maximum precision needed becomes the least significant digit of the integer. For example, if the required maximum precision is the tenth of one cent, multiply the monetary value by 1000. 3. Store the converted monetary value. For example, the following scales 9.99 USD by 1000 to preserve precision up to one tenth of a cent. { price: 9990, currency: "USD"} The model assumes that for a given currency value: • The scale factor is consistent for a currency; i.e. same scaling factor for a given currency. • The scale factor is a constant and known property of the currency; i.e applications can determine the scale factor from the currency. When using this model, applications must be consistent in performing the appropriate scaling of the values. For use cases of this model, see Use Cases for Exact Precision Model (page 170). Arbitrary Precision To model monetary data using the arbitrary precision model, store the value in two fields: 1. In one field, encode the exact monetary value as a non-numeric data type; e.g., BinData or a string. 2. In the second field, store a double-precision floating point approximation of the exact value. The following example uses the arbitrary precision model to store 9.99 USD for the price and 0.25 USD for the fee: { price:{ display: "9.99", approx: 9.9900000000000002, currency: "USD"}, fee:{ display: "0.25", approx: 0.2499999999999999, currency: "USD"} } With some care, applications can perform range and sort queries on the field with the numeric approximation. How- ever, the use of the approximation field for the query and sort operations requires that applications perform client-side post-processing to decode the non-numeric representation of the exact value and then filter out the returned documents based on the exact monetary value. For use cases of this model, see Use Cases for Arbitrary Precision Model (page 171). 4.3. Data Model Examples and Patterns 171 MongoDB Documentation, Release 3.0.7 Model Time Data Overview MongoDB stores times in UTC (page 184) by default, and will convert any local time representations into this form. Applications that must operate or report on some unmodified local time value may store the time zone alongside the UTC timestamp, and compute the original local time in their application logic. Example In the MongoDB shell, you can store both the current date and the current client’s offset from UTC. var now= new Date(); db.data.save( { date: now, offset: now.getTimezoneOffset() } ); You can reconstruct the original local time by applying the saved offset: var record= db.data.findOne(); var localNow= new Date( record.date.getTime()- ( record.offset * 60000)); 4.4 Data Model Reference Documents (page 172) MongoDB stores all data in documents, which are JSON-style data structures composed of field-and-value pairs. Database References (page 175) Discusses manual references and DBRefs, which MongoDB can use to represent relationships between documents. GridFS Reference (page 178) Convention for storing large files in a MongoDB Database. ObjectId (page 180) A 12-byte BSON type that MongoDB uses as the default value for its documents’ _id field if the _id field is not specified. BSON Types (page 182) Outlines the unique BSON types used by MongoDB. See BSONspec.org12 for the complete BSON specification. 4.4.1 Documents MongoDB stores all data in documents, which are JSON-style data structures composed of field-and-value pairs: { "item": "pencil", "qty": 500, "type": "no.2"} Most user-accessible data structures in MongoDB are documents, including: • All database records. • Query selectors (page 62), which define what records to select for read, update, and delete operations. • Update definitions (page 75), which define what fields to modify during an update. • Index specifications (page 485), which define what fields to index. • Data output by MongoDB for reporting and configuration, such as the output of the serverStatus and the replica set configuration document (page 652). 12http://bsonspec.org/ 172 Chapter 4. Data Models MongoDB Documentation, Release 3.0.7 Document Format MongoDB stores documents on disk in the BSON serialization format. BSON is a binary representation of JSON documents, though it contains more data types than JSON. For the BSON spec, see bsonspec.org13. See also BSON Types (page 182). The mongo JavaScript shell and the MongoDB language drivers translate between BSON and the language- specific document representation. Document Structure MongoDB documents are composed of field-and-value pairs and have the following structure: { field1: value1, field2: value2, field3: value3, ... fieldN: valueN } The value of a field can be any of the BSON data types (page 182), including other documents, arrays, and arrays of documents. The following document contains values of varying types: var mydoc={ _id: ObjectId("5099803df3f4948bd2f98391"), name: { first: "Alan", last: "Turing"}, birth: new Date('Jun 23, 1912'), death: new Date('Jun 07, 1954'), contribs:[ "Turing machine", "Turing test", "Turingery"], views: NumberLong(1250000) } The above fields have the following data types: •_id holds an ObjectId. • name holds an embedded document that contains the fields first and last. • birth and death hold values of the Date type. • contribs holds an array of strings. • views holds a value of the NumberLong type. Field Names Field names are strings. Documents (page 172) have the following restrictions on field names: • The field name _id is reserved for use as a primary key; its value must be unique in the collection, is immutable, and may be of any type other than an array. • The field names cannot start with the dollar sign ($) character. • The field names cannot contain the dot (.) character. • The field names cannot contain the null character. 13http://bsonspec.org/ 4.4. Data Model Reference 173 MongoDB Documentation, Release 3.0.7 BSON documents may have more than one field with the same name. Most MongoDB interfaces, however, represent MongoDB with a structure (e.g. a hash table) that does not support duplicate field names. If you need to manipulate documents that have more than one field with the same name, see the driver documentation for your driver. Some documents created by internal MongoDB processes may have duplicate fields, but no MongoDB process will ever add duplicate fields to an existing user document. Field Value Limit For indexed collections (page 481), the values for the indexed fields have a Maximum Index Key Length limit. See Maximum Index Key Length for details. Document Limitations Documents have the following attributes: Document Size Limit The maximum BSON document size is 16 megabytes. The maximum document size helps ensure that a single document cannot use excessive amount of RAM or, during transmission, excessive amount of bandwidth. To store documents larger than the maximum size, MongoDB provides the GridFS API. See mongofiles and the documentation for your driver for more information about GridFS. Document Field Order MongoDB preserves the order of the document fields following write operations except for the following cases: • The _id field is always the first field in the document. • Updates that include renaming of field names may result in the reordering of fields in the document. Changed in version 2.6: Starting in version 2.6, MongoDB actively attempts to preserve the field order in a document. Before version 2.6, MongoDB did not actively preserve the order of the fields in a document. The _id Field The _id field has the following behavior and constraints: • By default, MongoDB creates a unique index on the _id field during the creation of a collection. • The _id field is always the first field in the documents. If the server receives a document that does not have the _id field first, then the server will move the field to the beginning. • The _id field may contain values of any BSON data type (page 182), other than an array. Warning: To ensure functioning replication, do not store values that are of the BSON regular expression type in the _id field. The following are common options for storing values for _id: • Use an ObjectId (page 180). • Use a natural unique identifier, if available. This saves space and avoids an additional index. 174 Chapter 4. Data Models MongoDB Documentation, Release 3.0.7 • Generate an auto-incrementing number. See Create an Auto-Incrementing Sequence Field (page 129). • Generate a UUID in your application code. For a more efficient storage of the UUID values in the collection and in the _id index, store the UUID as a value of the BSON BinData type. Index keys that are of the BinData type are more efficiently stored in the index if: – the binary subtype value is in the range of 0-7 or 128-135, and – the length of the byte array is: 0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 12, 14, 16, 20, 24, or 32. • Use your driver’s BSON UUID facility to generate UUIDs. Be aware that driver implementations may imple- ment UUID serialization and deserialization logic differently, which may not be fully compatible with other drivers. See your driver documentation14 for information concerning UUID interoperability. Note: Most MongoDB driver clients will include the _id field and generate an ObjectId before sending the insert operation to MongoDB; however, if the client sends a document without an _id field, the mongod will add the _id field and generate the ObjectId. Dot Notation MongoDB uses the dot notation to access the elements of an array and to access the fields of an embedded document. To access an element of an array by the zero-based index position, concatenate the array name with the dot (.) and zero-based index position, and enclose in quotes: '.' See also $ positional operator for update operations and $ projection operator when array index position is unknown. To access a field of an embedded document with dot-notation, concatenate the embedded document name with the dot (.) and the field name, and enclose in quotes: '.' See also: • Embedded Documents (page 99) for dot notation examples with embedded documents. • Arrays (page 100) for dot notation examples with arrays. Additional Resources • Thinking in Documents Part 1 (Blog Post)15 4.4.2 Database References MongoDB does not support joins. In MongoDB some data is denormalized, or stored with related data in documents to remove the need for joins. However, in some cases it makes sense to store related information in separate documents, typically in different collections or databases. MongoDB applications use one of two methods for relating documents: • Manual references (page 176) where you save the _id field of one document in another document as a reference. Then your application can run a second query to return the related data. These references are simple and sufficient for most use cases. 14https://api.mongodb.org/ 15https://www.mongodb.com/blog/post/thinking-documents-part-1?jmp=docs 4.4. Data Model Reference 175 MongoDB Documentation, Release 3.0.7 • DBRefs (page 177) are references from one document to another using the value of the first document’s _id field, collection name, and, optionally, its database name. By including these names, DBRefs allow documents located in multiple collections to be more easily linked with documents from a single collection. To resolve DBRefs, your application must perform additional queries to return the referenced documents. Many drivers have helper methods that form the query for the DBRef automatically. The drivers 16 do not auto- matically resolve DBRefs into documents. DBRefs provide a common format and type to represent relationships among documents. The DBRef format also provides common semantics for representing links between documents if your database must interact with multiple frameworks and tools. Unless you have a compelling reason to use DBRefs, use manual references instead. Manual References Background Using manual references is the practice of including one document’s _id field in another document. The application can then issue a second query to resolve the referenced fields as needed. Process Consider the following operation to insert two documents, using the _id field of the first document as a reference in the second document: original_id= ObjectId() db.places.insert({ "_id": original_id, "name": "Broadway Center", "url": "bc.example.net" }) db.people.insert({ "name": "Erin", "places_id": original_id, "url": "bc.example.net/Erin" }) Then, when a query returns the document from the people collection you can, if needed, make a second query for the document referenced by the places_id field in the places collection. Use For nearly every case where you want to store a relationship between two documents, use manual references (page 176). The references are simple to create and your application can resolve references as needed. The only limitation of manual linking is that these references do not convey the database and collection names. If you have documents in a single collection that relate to documents in more than one collection, you may need to consider using DBRefs. 16 Some community supported drivers may have alternate behavior and may resolve a DBRef into a document automatically. 176 Chapter 4. Data Models MongoDB Documentation, Release 3.0.7 DBRefs Background DBRefs are a convention for representing a document, rather than a specific reference type. They include the name of the collection, and in some cases the database name, in addition to the value from the _id field. Format DBRefs have the following fields: $ref The $ref field holds the name of the collection where the referenced document resides. $id The $id field contains the value of the _id field in the referenced document. $db Optional. Contains the name of the database where the referenced document resides. Only some drivers support $db references. Example DBRef documents resemble the following document: { "$ref":, "$id":, "$db":} Consider a document from a collection that stored a DBRef in a creator field: { "_id": ObjectId("5126bbf64aed4daf9e2ab771"), // .. application fields "creator":{ "$ref": "creators", "$id": ObjectId("5126bc054aed4daf9e2ab772"), "$db": "users" } } The DBRef in this example points to a document in the creators collection of the users database that has ObjectId("5126bc054aed4daf9e2ab772") in its _id field. Note: The order of fields in the DBRef matters, and you must use the above sequence when using a DBRef. 4.4. Data Model Reference 177 MongoDB Documentation, Release 3.0.7 Driver Support for DBRefs C The C driver contains no support for DBRefs. You can traverse references manually. C++ The C++ driver contains no support for DBRefs. You can traverse references manually. C# The C# driver supports DBRefs using the MongoDBRef17 class and FetchDBRef and FetchDBRefAs methods. Haskell The Haskell driver contains no support for DBRefs. You can traverse references manually. Java The DBRef18 class provides support for DBRefs from Java. JavaScriptThe mongo shell’s JavaScript interface provides a DBRef. Node.js The Node.js driver supports DBRefs using the DBRef19 class and the dereference20 method. Perl The Perl driver supports DBRefs using the MongoDB::DBRef21 class. You can traverse references manually. PHP The PHP driver supports DBRefs, including the optional $db reference, using the MongoDBRef22 class. Python The Python driver supports DBRefs using the DBRef23 class and the dereference24 method. Ruby The Ruby driver supports DBRefs using the DBRef25 class and the dereference26 method. Scala The Scala driver contains no support for DBRefs. You can traverse references manually. Use In most cases you should use the manual reference (page 176) method for connecting two or more related documents. However, if you need to reference documents from multiple collections, consider using DBRefs. 4.4.3 GridFS Reference GridFS stores files in two collections: • chunks stores the binary chunks. For details, see The chunks Collection (page 179). • files stores the file’s metadata. For details, see The files Collection (page 179). GridFS places the collections in a common bucket by prefixing each with the bucket name. By default, GridFS uses two collections with names prefixed by fs bucket: • fs.files • fs.chunks You can choose a different bucket name than fs, and create multiple buckets in a single database. See also: GridFS (page 154) for more information about GridFS. 17https://api.mongodb.org/csharp/current/html/T_MongoDB_Driver_MongoDBRef.htm 18https://api.mongodb.org/java/current/com/mongodb/DBRef.html 19http://mongodb.github.io/node-mongodb-native/api-bson-generated/db_ref.html 20http://mongodb.github.io/node-mongodb-native/api-generated/db.html#dereference 21https://metacpan.org/pod/MongoDB::DBRef 22http://www.php.net/manual/en/class.mongodbref.php/ 23https://api.mongodb.org/python/current/api/bson/dbref.html 24https://api.mongodb.org/python/current/api/pymongo/database.html#pymongo.database.Database.deref eren ce 25https://api.mongodb.org/ruby/current/BSON/DBRef.html 26https://api.mongodb.org/ruby/current/Mongo/DB.html#dereference-instance_method 178 Chapter 4. Data Models MongoDB Documentation, Release 3.0.7 The chunks Collection Each document in the chunks collection represents a distinct chunk of a file as represented in the GridFS store. The following is a prototype document from the chunks collection.: { "_id":, "files_id":, "n":, "data": } A document from the chunks collection contains the following fields: chunks._id The unique ObjectId of the chunk. chunks.files_id The _id of the “parent” document, as specified in the files collection. chunks.n The sequence number of the chunk. GridFS numbers all chunks, starting with 0. chunks.data The chunk’s payload as a BSON binary type. The chunks collection uses a compound index on files_id and n, as described in GridFS Index (page 155). The files Collection Each document in the files collection represents a file in the GridFS store. Consider the following prototype of a document in the files collection: { "_id":, "length":, "chunkSize":, "uploadDate":, "md5":, "filename":, "contentType":, "aliases":, "metadata":, } Documents in the files collection contain some or all of the following fields. Applications may create additional arbitrary fields: files._id The unique ID for this document. The _id is of the data type you chose for the original document. The default type for MongoDB documents is BSON ObjectId. files.length The size of the document in bytes. files.chunkSize The size of each chunk. GridFS divides the document into chunks of the size specified here. The default size is 255 kilobytes. 4.4. Data Model Reference 179 MongoDB Documentation, Release 3.0.7 Changed in version 2.4.10: The default chunk size changed from 256k to 255k. files.uploadDate The date the document was first stored by GridFS. This value has the Date type. files.md5 An MD5 hash returned by the filemd5 command. This value has the String type. files.filename Optional. A human-readable name for the document. files.contentType Optional. A valid MIME type for the document. files.aliases Optional. An array of alias strings. files.metadata Optional. Any additional information you want to store. 4.4.4 ObjectId Overview ObjectId is a 12-byte BSON type, constructed using: • a 4-byte value representing the seconds since the Unix epoch, • a 3-byte machine identifier, • a 2-byte process id, and • a 3-byte counter, starting with a random value. In MongoDB, documents stored in a collection require a unique _id field that acts as a primary key. MongoDB uses ObjectIds as the default value for the _id field if the _id field is not specified; i.e. if a document does not contain a top-level _id field, the MongoDB driver adds the _id field that holds an ObjectId. In addition, if the mongod receives a document to insert that does not contain an _id field, mongod will add the _id field that holds an ObjectId. MongoDB clients should add an _id field with a unique ObjectId. Using ObjectIds for the _id field provides the following additional benefits: • in the mongo shell, you can access the creation time of the ObjectId, using the getTimestamp() method. • sorting on an _id field that stores ObjectId values is roughly equivalent to sorting by creation time. Important: The relationship between the order of ObjectId values and generation time is not strict within a single second. If multiple systems, or multiple processes or threads on a single system generate values, within a single second; ObjectId values do not represent a strict insertion order. Clock skew between clients can also result in non-strict ordering even for values because client drivers generate ObjectId values. Also consider the Documents (page 172) section for related information on MongoDB’s document orientation. ObjectId() The mongo shell provides the ObjectId() wrapper class to generate a new ObjectId, and to provide the following helper attribute and methods: 180 Chapter 4. Data Models MongoDB Documentation, Release 3.0.7 • str The hexadecimal string representation of the object. • getTimestamp() Returns the timestamp portion of the object as a Date. • toString() Returns the JavaScript representation in the form of a string literal “ObjectId(...)”. Changed in version 2.2: In previous versions toString() returns the hexadecimal string representation, which as of version 2.2 can be retrieved by the str property. • valueOf() Returns the representation of the object as a hexadecimal string. The returned string is the str attribute. Changed in version 2.2: In previous versions, valueOf() returns the object. Examples Consider the following uses ObjectId() class in the mongo shell: Generate a new ObjectId To generate a new ObjectId, use the ObjectId() constructor with no argument: x= ObjectId() In this example, the value of x would be: ObjectId("507f1f77bcf86cd799439011") To generate a new ObjectId using the ObjectId() constructor with a unique hexadecimal string: y= ObjectId("507f191e810c19729de860ea") In this example, the value of y would be: ObjectId("507f191e810c19729de860ea") • To return the timestamp of an ObjectId() object, use the getTimestamp() method as follows: Convert an ObjectId into a Timestamp To return the timestamp of an ObjectId() object, use the getTimestamp() method as follows: ObjectId("507f191e810c19729de860ea").getTimestamp() This operation will return the following Date object: ISODate("2012-10-17T20:46:22Z") 4.4. Data Model Reference 181 MongoDB Documentation, Release 3.0.7 Convert ObjectIds into Strings Access the str attribute of an ObjectId() object, as follows: ObjectId("507f191e810c19729de860ea").str This operation will return the following hexadecimal string: 507f191e810c19729de860ea To return the hexadecimal string representation of an ObjectId(), use the valueOf() method as follows: ObjectId("507f191e810c19729de860ea").valueOf() This operation returns the following output: 507f191e810c19729de860ea To return the string representation of an ObjectId() object (in the form of a string literal ObjectId(...)), use the toString() method as follows: ObjectId("507f191e810c19729de860ea").toString() This operation will return the following string output: ObjectId("507f191e810c19729de860ea") 4.4.5 BSON Types BSON is a binary serialization format used to store documents and make remote procedure calls in MongoDB. The BSON specification is located at bsonspec.org27. BSON supports the following data types as values in documents. Each data type has a corresponding number that can be used with the $type operator to query documents by BSON type. Type Number Notes Double 1 String 2 Object 3 Array 4 Binary data 5 Undefined 6 Deprecated. Object id 7 Boolean 8 Date 9 Null 10 Regular Expression 11 JavaScript 13 Symbol 14 JavaScript (with scope) 15 32-bit integer 16 Timestamp 17 64-bit integer 18 Min key 255 Query with -1. Max key 127 27http://bsonspec.org/ 182 Chapter 4. Data Models MongoDB Documentation, Release 3.0.7 To determine a field’s type, see Check Types in the mongo Shell (page 275). If you convert BSON to JSON, see the Extended JSON reference. Comparison/Sort Order When comparing values of different BSON types, MongoDB uses the following comparison order, from lowest to highest: 1. MinKey (internal type) 2. Null 3. Numbers (ints, longs, doubles) 4. Symbol, String 5. Object 6. Array 7. BinData 8. ObjectId 9. Boolean 10. Date 11. Timestamp 12. Regular Expression 13. MaxKey (internal type) MongoDB treats some types as equivalent for comparison purposes. For instance, numeric types undergo conversion before comparison. Changed in version 3.0.0: Date objects sort before Timestamp objects. Previously Date and Timestamp objects sorted together. The comparison treats a non-existent field as it would an empty BSON Object. As such, a sort on the a field in documents {} and { a: null } would treat the documents as equivalent in sort order. With arrays, a less-than comparison or an ascending sort compares the smallest element of arrays, and a greater-than comparison or a descending sort compares the largest element of the arrays. As such, when comparing a field whose value is a single-element array (e.g. [ 1 ]) with non-array fields (e.g. 2), the comparison is between 1 and 2.A comparison of an empty array (e.g. []) treats the empty array as less than null or a missing field. MongoDB sorts BinData in the following order: 1. First, the length or size of the data. 2. Then, by the BSON one-byte subtype. 3. Finally, by the data, performing a byte-by-byte comparison. The following sections describe special considerations for particular BSON types. ObjectId ObjectIds are: small, likely unique, fast to generate, and ordered. These values consists of 12-bytes, where the first four bytes are a timestamp that reflect the ObjectId’s creation. Refer to the ObjectId (page 180) documentation for more information. 4.4. Data Model Reference 183 MongoDB Documentation, Release 3.0.7 String BSON strings are UTF-8. In general, drivers for each programming language convert from the language’s string format to UTF-8 when serializing and deserializing BSON. This makes it possible to store most international characters in BSON strings with ease. 28 In addition, MongoDB $regex queries support UTF-8 in the regex string. Timestamps BSON has a special timestamp type for internal MongoDB use and is not associated with the regular Date (page 184) type. Timestamp values are a 64 bit value where: • the first 32 bits are a time_t value (seconds since the Unix epoch) • the second 32 bits are an incrementing ordinal for operations within a given second. Within a single mongod instance, timestamp values are always unique. In replication, the oplog has a ts field. The values in this field reflect the operation time, which uses a BSON timestamp value. Note: The BSON timestamp type is for internal MongoDB use. For most cases, in application development, you will want to use the BSON date type. See Date (page 184) for more information. If you insert a document containing an empty BSON timestamp in a top-level field, the MongoDB server will replace that empty timestamp with the current timestamp value. For example, if you create an insert a document with a timestamp value, as in the following operation: var a= new Timestamp(); db.test.insert( { ts: a } ); Then, the db.test.find() operation will return a document that resembles the following: { "_id": ObjectId("542c2b97bac0595474108b48"), "ts": Timestamp(1412180887,1)} If ts were a field in an embedded document, the server would have left it as an empty timestamp value. Changed in version 2.6: Previously, the server would only replace empty timestamp values in the first two fields, including _id, of an inserted document. Now MongoDB will replace any top-level field. Date BSON Date is a 64-bit integer that represents the number of milliseconds since the Unix epoch (Jan 1, 1970). This results in a representable date range of about 290 million years into the past and future. The official BSON specification29 refers to the BSON Date type as the UTC datetime. Changed in version 2.0: BSON Date type is signed. 30 Negative values represent dates before 1970. Example Construct a Date using the new Date() constructor in the mongo shell: 28 Given strings using UTF-8 character sets, using sort() on strings will be reasonably correct. However, because internally sort() uses the C++ strcmp api, the sort order may handle some characters incorrectly. 29http://bsonspec.org/#/specification 30 Prior to version 2.0, Date values were incorrectly interpreted as unsigned integers, which affected sorts, range queries, and indexes on Date fields. Because indexes are not recreated when upgrading, please re-index if you created an index on Date values with an earlier version, and dates before 1970 are relevant to your application. 184 Chapter 4. Data Models MongoDB Documentation, Release 3.0.7 var mydate1= new Date() Example Construct a Date using the ISODate() constructor in the mongo shell: var mydate2= ISODate() Example Return the Date value as string: mydate1.toString() Example Return the month portion of the Date value; months are zero-indexed, so that January is month 0: mydate1.getMonth() 4.4. Data Model Reference 185 MongoDB Documentation, Release 3.0.7 186 Chapter 4. Data Models CHAPTER 5 Administration The administration documentation addresses the ongoing operation and maintenance of MongoDB instances and de- ployments. This documentation includes both high level overviews of these concerns as well as tutorials that cover specific procedures and processes for operating MongoDB. Administration Concepts (page 187) Core conceptual documentation of operational practices for managing Mon- goDB deployments and systems. MongoDB Backup Methods (page 188) Describes approaches and considerations for backing up a MongoDB database. Monitoring for MongoDB (page 191) An overview of monitoring tools, diagnostic strategies, and approaches to monitoring replica sets and sharded clusters. Production Notes (page 201) A collection of notes that describe best practices and considerations for the oper- ations of MongoDB instances and deployments. Continue reading from Administration Concepts (page 187) for additional documentation of MongoDB admin- istration. Administration Tutorials (page 224) Tutorials that describe common administrative procedures and practices for op- erations for MongoDB instances and deployments. Configuration, Maintenance, and Analysis (page 225) Describes routine management operations, including configuration and performance analysis. Backup and Recovery (page 248) Outlines procedures for data backup and restoration with mongod instances and deployments. Continue reading from Administration Tutorials (page 224) for more tutorials of common MongoDB mainte- nance operations. Administration Reference (page 292) Reference and documentation of internal mechanics of administrative features, systems and functions and operations. See also: The MongoDB Manual contains administrative documentation and tutorials though out several sections. See Replica Set Tutorials (page 602) and Sharded Cluster Tutorials (page 690) for additional tutorials and information. 5.1 Administration Concepts The core administration documents address strategies and practices used in the operation of MongoDB systems and deployments. 187 MongoDB Documentation, Release 3.0.7 Operational Strategies (page 188) Higher level documentation of key concepts for the operation and maintenance of MongoDB deployments. MongoDB Backup Methods (page 188) Describes approaches and considerations for backing up a MongoDB database. Monitoring for MongoDB (page 191) An overview of monitoring tools, diagnostic strategies, and approaches to monitoring replica sets and sharded clusters. Run-time Database Configuration (page 196) Outlines common MongoDB configurations and examples of best-practice configurations for common use cases. Continue reading from Operational Strategies (page 188) for additional documentation. Data Management (page 211) Core documentation that addresses issues in data management, organization, mainte- nance, and lifecycle management. Data Center Awareness (page 211) Presents the MongoDB features that allow application developers and database administrators to configure their deployments to be more data center aware or allow operational and location-based separation. Capped Collections (page 213) Capped collections provide a special type of size-constrained collections that preserve insertion order and can support high volume inserts. Expire Data from Collections by Setting TTL (page 215) TTL collections make it possible to automatically remove data from a collection based on the value of a timestamp and are useful for managing data like machine generated event data that are only useful for a limited period of time. Optimization Strategies for MongoDB (page 217) Techniques for optimizing application performance with Mon- goDB. Continue reading from Optimization Strategies for MongoDB (page 217) for additional documentation. 5.1.1 Operational Strategies These documents address higher level strategies for common administrative tasks and requirements with respect to MongoDB deployments. MongoDB Backup Methods (page 188) Describes approaches and considerations for backing up a MongoDB database. Monitoring for MongoDB (page 191) An overview of monitoring tools, diagnostic strategies, and approaches to monitoring replica sets and sharded clusters. Run-time Database Configuration (page 196) Outlines common MongoDB configurations and examples of best- practice configurations for common use cases. Production Notes (page 201) A collection of notes that describe best practices and considerations for the operations of MongoDB instances and deployments. MongoDB Backup Methods When deploying MongoDB in production, you should have a strategy for capturing and restoring backups in the case of data loss events. There are several ways to back up MongoDB clusters: • Backup by Copying Underlying Data Files (page 189) • Backup a Database with mongodump (page 255) • MongoDB Cloud Manager Backup (page 190) 188 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 • Ops Manager Backup Software (page 190) Backup by Copying Underlying Data Files You can create a backup by copying MongoDB’s underlying data files. If the volume where MongoDB stores data files supports point in time snapshots, you can use these snapshots to create backups of a MongoDB system at an exact moment in time. File systems snapshots are an operating system volume manager feature, and are not specific to MongoDB. The mechanics of snapshots depend on the underlying storage system. For example, if you use Amazon’s EBS storage system for EC2 supports snapshots. On Linux the LVM manager can create a snapshot. To get a correct snapshot of a running mongod process, you must have journaling enabled and the journal must reside on the same logical volume as the other MongoDB data files. Without journaling enabled, there is no guarantee that the snapshot will be consistent or valid. To get a consistent snapshot of a sharded system, you must disable the balancer and capture a snapshot from every shard and a config server at approximately the same moment in time. If your storage system does not support snapshots, you can copy the files directly using cp, rsync, or a similar tool. Since copying multiple files is not an atomic operation, you must stop all writes to the mongod before copying the files. Otherwise, you will copy the files in an invalid state. Backups produced by copying the underlying data do not support point in time recovery for replica sets and are difficult to manage for larger sharded clusters. Additionally, these backups are larger because they include the indexes and duplicate underlying storage padding and fragmentation. mongodump, by contrast, creates smaller backups. For more information, see the Backup and Restore with Filesystem Snapshots (page 249) and Backup a Sharded Cluster with Filesystem Snapshots (page 261) for complete instructions on using LVM to create snapshots. Also see Back up and Restore Processes for MongoDB on Amazon EC21. Backup with mongodump The mongodump tool reads data from a MongoDB database and creates high fidelity BSON files. The mongorestore tool can populate a MongoDB database with the data from these BSON files. These tools are simple and efficient for backing up small MongoDB deployments, but are not ideal for capturing backups of larger systems. mongodump and mongorestore can operate against a running mongod process, and can manipulate the underly- ing data files directly. By default, mongodump does not capture the contents of the local database (page 652). mongodump only captures the documents in the database. The resulting backup is space efficient, but mongorestore or mongod must rebuild the indexes after restoring data. When connected to a MongoDB instance, mongodump can adversely affect mongod performance. If your data is larger than system memory, the queries will push the working set out of memory. To mitigate the impact of mongodump on the performance of the replica set, use mongodump to capture back- ups from a secondary (page 567) member of a replica set. Alternatively, you can shut down a secondary and use mongodump with the data files directly. If you shut down a secondary to capture data with mongodump ensure that the operation can complete before its oplog becomes too stale to continue replicating. For replica sets, mongodump also supports a point in time feature with the --oplog option. Applications may continue modifying data while mongodump captures the output. To restore a point in time backup created with --oplog, use mongorestore with the --oplogReplay option. 1https://docs.mongodb.org/ecosystem/tutorial/backup-and-restore-mongodb-on-amazon-ec2 5.1. Administration Concepts 189 MongoDB Documentation, Release 3.0.7 If applications modify data while mongodump is creating a backup, mongodump will compete for resources with those applications. See Back Up and Restore with MongoDB Tools (page 254), Backup a Small Sharded Cluster with mongodump (page 260), and Backup a Sharded Cluster with Database Dumps (page 263) for more information. MongoDB Cloud Manager Backup The MongoDB Cloud Manager2 supports the backing up and restoring of MongoDB deployments. MongoDB Cloud Manager continually backs up MongoDB replica sets and sharded clusters by reading the oplog data from your MongoDB deployment. MongoDB Cloud Manager Backup offers point in time recovery of MongoDB replica sets and a consistent snapshot of sharded clusters. MongoDB Cloud Manager achieves point in time recovery by storing oplog data so that it can create a restore for any moment in time in the last 24 hours for a particular replica set or sharded cluster. Sharded cluster snapshots are difficult to achieve with other MongoDB backup methods. To restore a MongoDB deployment from an MongoDB Cloud Manager Backup snapshot, you download a compressed archive of your MongoDB data files and distribute those files before restarting the mongod processes. To get started with MongoDB Cloud Manager Backup, sign up for MongoDB Cloud Manager3. For documentation on MongoDB Cloud Manager, see the MongoDB Cloud Manager documentation4. Ops Manager Backup Software MongoDB Subscribers can install and run the same core software that powers MongoDB Cloud Manager Backup (page 190) on their own infrastructure. Ops Manager, an on-premise solution, has similar functionality to the cloud version and is available with Enterprise Advanced subscriptions. For more information about Ops Manager, see the MongoDB Enterprise Advanced5 page and the Ops Manager Man- ual6. Further Reading Backup and Restore with Filesystem Snapshots (page 249) An outline of procedures for creating MongoDB data set backups using system-level file snapshot tool, such as LVM or native storage appliance tools. Restore a Replica Set from MongoDB Backups (page 252) Describes procedure for restoring a replica set from an archived backup such as a mongodump or MongoDB Cloud Manager7 Backup file. Back Up and Restore with MongoDB Tools (page 254) Describes a procedure for exporting the contents of a database to either a binary dump or a textual exchange format, and for importing these files into a database. Backup and Restore Sharded Clusters (page 259) Detailed procedures and considerations for backing up sharded clusters and single shards. Recover Data after an Unexpected Shutdown (page 268) Recover data from MongoDB data files that were not prop- erly closed or have an invalid state. 2https://cloud.mongodb.com/?jmp=docs 3https://cloud.mongodb.com/?jmp=docs 4https://docs.cloud.mongodb.com/ 5https://www.mongodb.com/products/mongodb-enterprise-advanced?jmp=docs 6https://docs.opsmanager.mongodb.com/current/ 7https://cloud.mongodb.com/?jmp=docs 190 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 Additional Resources • Backup and it’s Role in Disaster Recovery White Paper8 • Backup vs. Replication: Why Do You Need Both?9 • MongoDB Production Readiness Consulting Package10 Monitoring for MongoDB Monitoring is a critical component of all database administration. A firm grasp of MongoDB’s reporting will allow you to assess the state of your database and maintain your deployment without crisis. Additionally, a sense of MongoDB’s normal operational parameters will allow you to diagnose problems before they escalate to failures. This document presents an overview of the available monitoring utilities and the reporting statistics available in Mon- goDB. It also introduces diagnostic strategies and suggestions for monitoring replica sets and sharded clusters. Note: MongoDB Cloud Manager11, a hosted service, and Ops Manager12, an on-premise solution, provide monitor- ing, backup, and automation of MongoDB instances. See the MongoDB Cloud Manager documentation13 and Ops Manager documentation14 for more information. Monitoring Strategies There are three methods for collecting data about the state of a running MongoDB instance: • First, there is a set of utilities distributed with MongoDB that provides real-time reporting of database activities. • Second, database commands return statistics regarding the current database state with greater fidelity. • Third, MongoDB Cloud Manager15, a hosted service, and Ops Manager, an on-premise solution available in MongoDB Enterprise Advanced16, provide monitoring to collect data from running MongoDB deployments as well as providing visualization and alerts based on that data. Each strategy can help answer different questions and is useful in different contexts. These methods are complemen- tary. MongoDB Reporting Tools This section provides an overview of the reporting methods distributed with MongoDB. It also offers examples of the kinds of questions that each method is best suited to help you address. Utilities The MongoDB distribution includes a number of utilities that quickly return statistics about instances’ performance and activity. Typically, these are most useful for diagnosing issues and assessing normal operation. 8https://www.mongodb.com/lp/white-paper/backup-disaster-recovery?jmp=docs 9http://www.mongodb.com/blog/post/backup-vs-replication-why-do-you-need-both?jmp=docs 10https://www.mongodb.com/products/consulting?jmp=docs#s_product_readiness 11https://cloud.mongodb.com/?jmp=docs 12https://www.mongodb.com/products/mongodb-enterprise-advanced?jmp=docs 13https://docs.cloud.mongodb.com/ 14https://docs.opsmanager.mongodb.com?jmp=docs 15https://cloud.mongodb.com/?jmp=docs 16https://www.mongodb.com/products/mongodb-enterprise-advanced?jmp=docs 5.1. Administration Concepts 191 MongoDB Documentation, Release 3.0.7 mongostat mongostat captures and returns the counts of database operations by type (e.g. insert, query, update, delete, etc.). These counts report on the load distribution on the server. Use mongostat to understand the distribution of operation types and to inform capacity planning. See the mongostat manual for details. mongotop mongotop tracks and reports the current read and write activity of a MongoDB instance, and reports these statistics on a per collection basis. Use mongotop to check if your database activity and use match your expectations. See the mongotop manual for details. HTTP Console MongoDB provides a web interface that exposes diagnostic and monitoring information in a simple web page. The web interface is accessible at localhost:, where the number is 1000 more than the mongod port . For example, if a locally running mongod is using the default port 27017, access the HTTP console at http://localhost:28017. Commands MongoDB includes a number of commands that report on the state of the database. These data may provide a finer level of granularity than the utilities discussed above. Consider using their output in scripts and programs to develop custom alerts, or to modify the behavior of your application in response to the activity of your instance. The db.currentOp method is another useful tool for identifying the database instance’s in-progress operations. serverStatus The serverStatus command, or db.serverStatus() from the shell, returns a general overview of the status of the database, detailing disk usage, memory use, connection, journaling, and index access. The command returns quickly and does not impact MongoDB performance. serverStatus outputs an account of the state of a MongoDB instance. This command is rarely run directly. In most cases, the data is more meaningful when aggregated, as one would see with monitoring tools including MongoDB Cloud Manager17 and Ops Manager18. Nevertheless, all administrators should be familiar with the data provided by serverStatus. dbStats The dbStats command, or db.stats() from the shell, returns a document that addresses storage use and data volumes. The dbStats reflect the amount of storage used, the quantity of data contained in the database, and object, collection, and index counters. Use this data to monitor the state and storage capacity of a specific database. This output also allows you to compare use between databases and to determine the average document size in a database. collStats The collStats or db.collection.stats() from the shell that provides statistics that resem- ble dbStats on the collection level, including a count of the objects in the collection, the size of the collection, the amount of disk space used by the collection, and information about its indexes. 17https://cloud.mongodb.com/?jmp=docs 18https://www.mongodb.com/products/mongodb-enterprise-advanced?jmp=docs 192 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 replSetGetStatus The replSetGetStatus command (rs.status() from the shell) returns an overview of your replica set’s status. The replSetGetStatus document details the state and configuration of the replica set and statistics about its members. Use this data to ensure that replication is properly configured, and to check the connections between the current host and the other members of the replica set. Third Party Tools A number of third party monitoring tools have support for MongoDB, either directly, or through their own plugins. Self Hosted Monitoring Tools These are monitoring tools that you must install, configure and maintain on your own servers. Most are open source. Tool Plugin Description Ganglia19 mongodb-ganglia20 Python script to report operations per second, memory usage, btree statistics, master/slave status and current connections. Ganglia gmond_python_modules21 Parses output from the serverStatus and replSetGetStatus commands. Motop22 None Realtime monitoring tool for MongoDB servers. Shows current operations ordered by durations every second. mtop23 None A top like tool. Munin24 mongo-munin25 Retrieves server statistics. Munin mongomon26 Retrieves collection statistics (sizes, index sizes, and each (configured) collection count for one DB). Munin munin-plugins Ubuntu PPA27 Some additional munin plugins not in the main distribution. Nagios28 nagios-plugin-mongodb29 A simple Nagios check script, written in Python. Also consider dex30, an index and query analyzing tool for MongoDB that compares MongoDB log files and indexes to make indexing recommendations. See also: Ops Manager, an on-premise solution available in MongoDB Enterprise Advanced31. Hosted (SaaS) Monitoring Tools These are monitoring tools provided as a hosted service, usually through a paid subscription. 19http://sourceforge.net/apps/trac/ganglia/wiki 20https://github.com/quiiver/mongodb-ganglia 21https://github.com/ganglia/gmond_python_modules 22https://github.com/tart/motop 23https://github.com/beaufour/mtop 24http://munin-monitoring.org/ 25https://github.com/erh/mongo-munin 26https://github.com/pcdummy/mongomon 27https://launchpad.net/ chris-lea/+archive/munin-plugins 28http://www.nagios.org/ 29https://github.com/mzupan/nagios-plugin-mongodb 30https://github.com/mongolab/dex 31https://www.mongodb.com/products/mongodb-enterprise-advanced?jmp=docs 5.1. Administration Concepts 193 MongoDB Documentation, Release 3.0.7 Name Notes MongoDB Cloud Manager32 MongoDB Cloud Manager is a cloud-based suite of services for managing MongoDB deployments. MongoDB Cloud Manager provides monitoring, backup, and automation functionality. For an on-premise solution, see also Ops Manager, available in MongoDB Enterprise Advanced33. Scout34 Several plugins, including MongoDB Monitoring35, MongoDB Slow Queries36, and MongoDB Replica Set Monitoring37. Server Density38 Dashboard for MongoDB39, MongoDB specific alerts, replication failover timeline and iPhone, iPad and Android mobile apps. Application Performance Management40 IBM has an Application Performance Management SaaS offering that includes monitor for MongoDB and other applications and middleware. Process Logging During normal operation, mongod and mongos instances report a live account of all server activity and operations to either standard output or a log file. The following runtime settings control these options. • quiet. Limits the amount of information written to the log or output. • verbosity. Increases the amount of information written to the log or output. You can also modify the logging verbosity during runtime with the logLevel parameter or the db.setLogLevel() method in the shell. • path. Enables logging to a file, rather than the standard output. You must specify the full path to the log file when adjusting this setting. • logAppend. Adds information to a log file instead of overwriting the file. Note: You can specify these configuration operations as the command line arguments to mongod or mongos For example: mongod -v --logpath /var/log/mongodb/server1.log --logappend Starts a mongod instance in verbose mode, appending data to the log file at /var/log/mongodb/server1.log/. The following database commands also affect logging: • getLog. Displays recent messages from the mongod process log. • logRotate. Rotates the log files for mongod processes only. See Rotate Log Files (page 236). Diagnosing Performance Issues As you develop and operate applications with MongoDB, you may want to analyze the performance of the database as the application. Analyzing MongoDB Performance (page 217) discusses some of the operational factors that can influence performance. 32https://cloud.mongodb.com/?jmp=docs 33https://www.mongodb.com/products/mongodb-enterprise-advanced?jmp=docs 34http://scoutapp.com 35https://scoutapp.com/plugin_urls/391-mongodb-monitoring 36http://scoutapp.com/plugin_urls/291-mongodb-slow-queries 37http://scoutapp.com/plugin_urls/2251-mongodb-replica-set-monitoring 38http://www.serverdensity.com 39http://www.serverdensity.com/mongodb-monitoring/ 40http://ibmserviceengage.com 194 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 Replication and Monitoring Beyond the basic monitoring requirements for any MongoDB instance, for replica sets, administrators must monitor replication lag. “Replication lag” refers to the amount of time that it takes to copy (i.e. replicate) a write operation on the primary to a secondary. Some small delay period may be acceptable, but two significant problems emerge as replication lag grows: • First, operations that occurred during the period of lag are not replicated to one or more secondaries. If you’re using replication to ensure data persistence, exceptionally long delays may impact the integrity of your data set. • Second, if the replication lag exceeds the length of the operation log (oplog) then MongoDB will have to perform an initial sync on the secondary, copying all data from the primary and rebuilding all indexes. This is uncommon under normal circumstances, but if you configure the oplog to be smaller than the default, the issue can arise. Note: The size of the oplog is only configurable during the first run using the --oplogSize argument to the mongod command, or preferably, the oplogSizeMB setting in the MongoDB configuration file. If you do not specify this on the command line before running with the --replSet option, mongod will create a default sized oplog. By default, the oplog is 5 percent of total available disk space on 64-bit systems. For more information about changing the oplog size, see the Change the Size of the Oplog (page 628) For causes of replication lag, see Replication Lag (page 647). Replication issues are most often the result of network connectivity issues between members, or the result of a primary that does not have the resources to support application and replication traffic. To check the status of a replica, use the replSetGetStatus or the following helper in the shell: rs.status() The replSetGetStatus reference provides a more in-depth overview view of this output. In general, watch the value of optimeDate, and pay particular attention to the time difference between the primary and the secondary members. Sharding and Monitoring In most cases, the components of sharded clusters benefit from the same monitoring and analysis as all other MongoDB instances. In addition, clusters require further monitoring to ensure that data is effectively distributed among nodes and that sharding operations are functioning appropriately. See also: See the Sharding Concepts (page 667) documentation for more information. Config Servers The config database maintains a map identifying which documents are on which shards. The cluster updates this map as chunks move between shards. When a configuration server becomes inaccessible, certain sharding operations become unavailable, such as moving chunks and starting mongos instances. However, clusters remain accessible from already-running mongos instances. Because inaccessible configuration servers can seriously impact the availability of a sharded cluster, you should mon- itor your configuration servers to ensure that the cluster remains well balanced and that mongos instances can restart. MongoDB Cloud Manager41 and Ops Manager42 monitor config servers and can create notifications if a config server 41https://cloud.mongodb.com/?jmp=docs 42https://www.mongodb.com/products/mongodb-enterprise-advanced?jmp=docs 5.1. Administration Concepts 195 MongoDB Documentation, Release 3.0.7 becomes inaccessible. See the MongoDB Cloud Manager documentation43 and Ops Manager documentation44 for more information. Balancing and Chunk Distribution The most effective sharded cluster deployments evenly balance chunks among the shards. To facilitate this, MongoDB has a background balancer process that distributes data to ensure that chunks are always optimally distributed among the shards. Issue the db.printShardingStatus() or sh.status() command to the mongos by way of the mongo shell. This returns an overview of the entire cluster including the database name, and a list of the chunks. Stale Locks In nearly every case, all locks used by the balancer are automatically released when they become stale. However, because any long lasting lock can block future balancing, it’s important to ensure that all locks are legitimate. To check the lock status of the database, connect to a mongos instance using the mongo shell. Issue the following command sequence to switch to the config database and display all outstanding locks on the shard database: use config db.locks.find() For active deployments, the above query can provide insights. The balancing process, which originates on a randomly selected mongos, takes a special “balancer” lock that prevents other balancing activity from transpiring. Use the following command, also to the config database, to check the status of the “balancer” lock. db.locks.find( { _id: "balancer"}) If this lock exists, make sure that the balancer process is actively using this lock. Additional Resources • MongoDB Production Readiness Consulting Package45 Run-time Database Configuration The command line and configuration file interfaces provide MongoDB administrators with a large num- ber of options and settings for controlling the operation of the database system. This document provides an overview of common configurations and examples of best-practice configurations for common use cases. While both interfaces provide access to the same collection of options and settings, this document primarily uses the configuration file interface. If you run MongoDB using a init script or if you installed from a package for your operating system, you likely already have a configuration file located at /etc/mongod.conf. Confirm this by checking the contents of the /etc/init.d/mongod or /etc/rc.d/mongod script to ensure that the init scripts start the mongod with the appropriate configuration file. To start a MongoDB instance using this configuration file, issue a command in the following form: mongod --config /etc/mongod.conf mongod -f /etc/mongod.conf Modify the values in the /etc/mongod.conf file on your system to control the configuration of your database instance. 43https://docs.cloud.mongodb.com/ 44https://docs.opsmanager.mongodb.com/current/application 45https://www.mongodb.com/products/consulting?jmp=docs#s_product_readiness 196 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 Configure the Database Consider the following basic configuration which uses the YAML format: processManagement: fork: true net: bindIp: 127.0.0.1 port: 27017 storage: dbPath: /srv/mongodb systemLog: destination: file path:"/var/log/mongodb/mongod.log" logAppend: true storage: journal: enabled: true Or, if using the older .ini configuration file format: fork= true bind_ip= 127.0.0.1 port= 27017 quiet= true dbpath= /srv/mongodb logpath= /var/log/mongodb/mongod.log logappend= true journal= true For most standalone servers, this is a sufficient base configuration. It makes several assumptions, but consider the following explanation: • fork is true, which enables a daemon mode for mongod, which detaches (i.e. “forks”) the MongoDB from the current session and allows you to run the database as a conventional server. • bindIp is 127.0.0.1, which forces the server to only listen for requests on the localhost IP. Only bind to secure interfaces that the application-level systems can access with access control provided by system network filtering (i.e. “firewall”). New in version 2.6: mongod installed from official .deb (page 20) and .rpm (page 7) packages have the bind_ip configuration set to 127.0.0.1 by default. • port is 27017, which is the default MongoDB port for database instances. MongoDB can bind to any port. You can also filter access based on port using network filtering tools. Note: UNIX-like systems require superuser privileges to attach processes to ports lower than 1024. • quiet is true. This disables all but the most critical entries in output/log file, and is not recommended for production systems. If you do set this option, you can use setParameter to modify this setting during run time. • dbPath is /srv/mongodb, which specifies where MongoDB will store its data files. /srv/mongodb and /var/lib/mongodb are popular locations. The user account that mongod runs under will need read and write access to this directory. • systemLog.path is /var/log/mongodb/mongod.log which is where mongod will write its output. If you do not set this value, mongod writes all output to standard output (e.g. stdout.) 5.1. Administration Concepts 197 MongoDB Documentation, Release 3.0.7 • logAppend is true, which ensures that mongod does not overwrite an existing log file following the server start operation. • storage.journal.enabled is true, which enables journaling. Journaling ensures single instance write- durability. 64-bit builds of mongod enable journaling by default. Thus, this setting may be redundant. Given the default configuration, some of these values may be redundant. However, in many situations explicitly stating the configuration increases overall system intelligibility. Security Considerations The following collection of configuration options are useful for limiting access to a mongod instance. Consider the following settings, shown in both YAML and older configuration file format: In YAML format security: authorization: enabled net: bindIp: 127.0.0.1,10.8.0.10,192.168.4.24 Or, if using the older older configuration file format46: bind_ip= 127.0.0.1,10.8.0.10,192.168.4.24 auth= true Consider the following explanation for these configuration decisions: •“ bindIp” has three values: 127.0.0.1, the localhost interface; 10.8.0.10, a private IP address typically used for local networks and VPN interfaces; and 192.168.4.24, a private network interface typically used for local networks. Because production MongoDB instances need to be accessible from multiple database servers, it is important to bind MongoDB to multiple interfaces that are accessible from your application servers. At the same time it’s important to limit these interfaces to interfaces controlled and protected at the network layer. •“ authorization” is true enables the authorization system within MongoDB. If enabled you will need to log in by connecting over the localhost interface for the first time to create user credentials. See also: Security Concepts (page 325) Replication and Sharding Configuration Replication Configuration Replica set configuration is straightforward, and only requires that the replSetName have a value that is consistent among all members of the set. Consider the following: In YAML format replication: replSetName: set0 Or, if using the older configuration file format47: replSet= set0 46https://docs.mongodb.org/v2.4/reference/configuration-options 47https://docs.mongodb.org/v2.4/reference/configuration-options 198 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 Use descriptive names for sets. Once configured, use the mongo shell to add hosts to the replica set. See also: Replica set reconfiguration. To enable authentication for the replica set, add the following keyFile option: In YAML format security: keyFile: /srv/mongodb/keyfile Or, if using the older configuration file format48: keyFile= /srv/mongodb/keyfile Setting keyFile enables authentication and specifies a key file for the replica set member use to when authenticating to each other. The content of the key file is arbitrary, but must be the same on all members of the replica set and mongos instances that connect to the set. The keyfile must be less than one kilobyte in size and may only contain characters in the base64 set and the file must not have group or “world” permissions on UNIX systems. See also: The Replica Set Security (page 329) section for information on configuring authentication with replica sets. The Replication (page 559) document for more information on replication in MongoDB and replica set configuration in general. Sharding Configuration Sharding requires a number of mongod instances with different configurations. The con- fig servers store the cluster’s metadata, while the cluster distributes data among one or more shard servers. Note: Config servers are not replica sets. To set up one or three “config server” instances as normal (page 197) mongod instances, and then add the following configuration option: In YAML format sharding: clusterRole: configsvr net: bindIp: 10.8.0.12 port: 27001 Or, if using the older configuration file format49: configsvr= true bind_ip= 10.8.0.12 port= 27001 This creates a config server running on the private IP address 10.8.0.12 on port 27001. Make sure that there are no port conflicts, and that your config server is accessible from all of your mongos and mongod instances. To set up shards, configure two or more mongod instance using your base configuration (page 197), with the shardsvr value for the sharding.clusterRole setting: 48https://docs.mongodb.org/v2.4/reference/configuration-options 49https://docs.mongodb.org/v2.4/reference/configuration-options 5.1. Administration Concepts 199 MongoDB Documentation, Release 3.0.7 sharding: clusterRole: shardsvr Or, if using the older configuration file format50: shardsvr= true Finally, to establish the cluster, configure at least one mongos process with the following settings: In YAML format: sharding: configDB: 10.8.0.12:27001 chunkSize: 64 Or, if using the older configuration file format51: configdb= 10.8.0.12:27001 chunkSize= 64 Important: Always use 3 config servers in production environments. You can specify multiple configDB instances by specifying hostnames and ports in the form of a comma separated list. In general, avoid modifying the chunkSize from the default value of 64, 52 and ensure this setting is consistent among all mongos instances. See also: The Sharding (page 661) section of the manual for more information on sharding and cluster configuration. Run Multiple Database Instances on the Same System In many cases running multiple instances of mongod on a single system is not recommended. On some types of deployments 53 and for testing purposes you may need to run more than one mongod on a single system. In these cases, use a base configuration (page 197) for each instance, but consider the following configuration values: In YAML format: storage: dbPath: /srv/mongodb/db0/ processManagement: pidFilePath: /srv/mongodb/db0.pid Or, if using the older configuration file format54: dbpath= /srv/mongodb/db0/ pidfilepath= /srv/mongodb/db0.pid The dbPath value controls the location of the mongod instance’s data directory. Ensure that each database has a distinct and well labeled data directory. The pidFilePath controls where mongod process places it’s process id 50https://docs.mongodb.org/v2.4/reference/configuration-options 51https://docs.mongodb.org/v2.4/reference/configuration-options 52 Chunk size is 64 megabytes by default, which provides the ideal balance between the most even distribution of data, for which smaller chunk sizes are best, and minimizing chunk migration, for which larger chunk sizes are optimal. 53 Single-tenant systems with SSD or other high performance disks may provide acceptable performance levels for multiple mongod instances. Additionally, you may find that multiple databases with small working sets may function acceptably on a single system. 54https://docs.mongodb.org/v2.4/reference/configuration-options 200 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 file. As this tracks the specific mongod file, it is crucial that file be unique and well labeled to make it easy to start and stop these processes. Create additional init scripts and/or adjust your existing MongoDB configuration and init script as needed to control these processes. Diagnostic Configurations The following configuration options control various mongod behaviors for diagnostic purposes: • operationProfiling.mode sets the database profiler (page 219) level. The profiler is not active by default because of the possible impact on the profiler itself on performance. Unless this setting is on, queries are not profiled. • operationProfiling.slowOpThresholdMs configures the threshold which determines whether a query is “slow” for the purpose of the logging system and the profiler (page 219). The default value is 100 milliseconds. Set a lower value if the database profiler does not return useful results or a higher value to only log the longest running queries. • systemLog.verbosity controls the amount of logging output that mongod write to the log. Only use this option if you are experiencing an issue that is not reflected in the normal logging level. Changed in version 3.0: You can also specify verbosity level for specific components using the systemLog.component..verbosity setting. For the available components, see component verbosity settings. For more information, see also Database Profiling (page 219) and Analyzing MongoDB Performance (page 217). Production Notes This page details system configurations that affect MongoDB, especially in production. Note: MongoDB Cloud Manager55, a hosted service, and Ops Manager56, an on-premise solution, provide monitor- ing, backup, and automation of MongoDB instances. See the MongoDB Cloud Manager documentation57 and Ops Manager documentation58 for more information. MongoDB Storage Engines Changed in version 3.0: MongoDB includes support for two storage engines: MMAPv1 (page 93), the storage engine available in previous versions of MongoDB, and WiredTiger (page 92). MongoDB uses the MMAPv1 engine by default. The files in the dbPath directory must correspond to the configured storage engine. mongod will not start if dbPath contains data files created by a storage engine other than the one specified by --storageEngine. Supported Platforms MongoDB distributions are currently available for Mac OS X, Linux, Windows Server 2012, Windows Server 2008 R2 64bit, Windows 7 (64 bit), Windows Vista, and Solaris. The MongoDB distribution for Solaris does not include support for the WiredTiger storage engine (page 92). 55https://cloud.mongodb.com/?jmp=docs 56https://www.mongodb.com/products/mongodb-enterprise-advanced?jmp=docs 57https://docs.cloud.mongodb.com/ 58https://docs.opsmanager.mongodb.com?jmp=docs 5.1. Administration Concepts 201 MongoDB Documentation, Release 3.0.7 For a full list of the recommended operating systems for production deployments, see: Recommended Operating Systems for Production Deployments (page 5). See also: Platform Specific Considerations (page 206) Use the Latest Stable Packages Be sure you have the latest stable release. All releases are available on the Downloads59 page. The Downloads60 page is a good place to verify the current stable release, even if you are installing via a package manager. Use 64-bit Builds Always use 64-bit builds for production. Although the 32-bit builds exist, they are unsuitable for production deployments. 32-bit builds also do not support the WiredTiger storage engine. For more information, see the 32-bit limitations page (page 746) Concurrency MMAPv1 Changed in version 3.0: Beginning with MongoDB 3.0, MMAPv1 (page 93) provides collection-level locking: All collections have a unique readers-writer lock that allows multiple clients to modify documents in different collections at the same time. For MongoDB versions 2.2 through 2.6 series, each database has a readers-writer lock that allows concurrent read ac- cess to a database, but gives exclusive access to a single write operation per database. See the Concurrency (page 758) page for more information. In earlier versions of MongoDB, all write operations contended for a single readers-writer lock for the entire mongod instance. WiredTiger WiredTiger (page 92) supports concurrent access by readers and writers to the documents in a collec- tion. Clients can read documents while write operations are in progress, and multiple threads can modify different documents in a collection at the same time. See also: Allocate Sufficient RAM and CPU (page 204) Data Consistency Journaling MongoDB uses write ahead logging to an on-disk journal. Journaling guarantees that MongoDB can quickly recover write operations (page 75) that were not written to data files in cases where mongod terminated as a result of a crash or other serious failure. Leave journaling enabled in order to ensure that mongod will be able to recover its data files and keep the data files in a valid state following a crash. See Journaling (page 314) for more information. Write Concern Write concern describes the guarantee that MongoDB provides when reporting on the success of a write operation. The strength of the write concerns determine the level of guarantee. When inserts, updates and deletes have a weak write concern, write operations return quickly. In some failure cases, write operations issued with weak write concerns may not persist. With stronger write concerns, clients wait after sending a write operation for MongoDB to confirm the write operations. 59http://www.mongodb.org/downloads 60http://www.mongodb.org/downloads 202 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 MongoDB provides different levels of write concern to better address the specific needs of applications. Clients may adjust write concern to ensure that the most important operations persist successfully to an entire MongoDB deployment. For other less critical operations, clients can adjust the write concern to ensure faster performance rather than ensure persistence to the entire deployment. See the Write Concern (page 80) document for more information about choosing an appropriate write concern level for your deployment. Networking Use Trusted Networking Environments Always run MongoDB in a trusted environment, with network rules that prevent access from all unknown machines, systems, and networks. As with any sensitive system that is dependent on network access, your MongoDB deployment should only be accessible to specific systems that require access, such as application servers, monitoring services, and other MongoDB components. Note: By default, authorization (page 334) is not enabled, and mongod assumes a trusted environment. Enable authorization mode as needed. For more information on authentication mechanisms supported in MongoDB as well as authorization in MongoDB, see Authentication (page 326) and Authorization (page 334). For additional information and considerations on security, refer to the documents in the Security Section (page 323), specifically: • Security Checklist (page 432) • Configuration Options (page 330) • Firewalls (page 331) • Network Security Tutorials (page 340) For Windows users, consider the Windows Server Technet Article on TCP Configuration61 when deploying MongoDB on Windows. Disable HTTP Interfaces MongoDB provides interfaces to check the status of the server and, optionally, run queries on it, over HTTP. In production environments, disable the HTTP interfaces. See HTTP Status Interface (page 338). Manage Connection Pool Sizes To avoid overloading the connection resources of a single mongod or mongos instance, ensure that clients maintain reasonable connection pool sizes. Adjust the connection pool size to suit your use case, beginning at 110-115% of the typical number of concurrent database requests. The connPoolStats command returns information regarding the number of open connections to the current database for mongos and mongod instances in sharded clusters. See also Allocate Sufficient RAM and CPU (page 204). Hardware Considerations MongoDB is designed specifically with commodity hardware in mind and has few hardware requirements or limita- tions. MongoDB’s core components run on little-endian hardware, primarily x86/x86_64 processors. Client libraries (i.e. drivers) can run on big or little endian systems. 61http://technet.microsoft.com/en-us/library/dd349797.aspx 5.1. Administration Concepts 203 MongoDB Documentation, Release 3.0.7 Allocate Sufficient RAM and CPU MMAPv1 Due to its concurrency model, the MMAPv1 storage engine does not require many CPU cores . As such, increasing the number of cores can help but does not provide significant return. Increasing the amount of RAM accessible to MongoDB may help reduce the frequency of page faults. WiredTiger The WiredTiger storage engine is multithreaded and can take advantage of many CPU cores. Specif- ically, the total number of active threads (i.e. concurrent operations) relative to the number of CPUs can impact performance: • Throughput increases as the number of concurrent active operations increases up to the number of CPUs. • Throughput decreases as the number of concurrent active operations exceeds the number of CPUs by some threshold amount. The threshold amount depends on your application. You can determine the optimum number of concurrent active operations for your application by experimenting and measuring throughput. The output from mongostat provides statistics on the number of active reads/writes in the (ar|aw) column. WiredTiger’s default configuration will use either 1GB or half of the installed physical RAM for cache, whichever is larger. This size is tunable through the storage.wiredTiger.engineConfig.cacheSizeGB setting, and should be large enough to hold your entire working set. The default storage.wiredTiger.engineConfig.cacheSizeGB setting assumes that there is a sin- gle mongod instance per node. If a single node contains multiple instances, then you should adjust the storage.wiredTiger.engineConfig.cacheSizeGB setting to accommodate the working set as well as the other mongod instances. If you run mongod in a container (e.g. lxc, cgroups, Docker, etc.) that does not have access to all of the RAM available in a system, you must set the storage.wiredTiger.engineConfig.cacheSizeGB to a value less than the amount of RAM available in the container. The exact amount depends on the other processes running in the container. See also: Concurrency (page 202) Use Solid State Disks (SSDs) MongoDB has good results and a good price-performance ratio with SATA SSD (Solid State Disk). Use SSD if available and economical. Spinning disks can be performant, but SSDs’ capacity for random I/O operations works well with the update model of MMAPv1. Commodity (SATA) spinning drives are often a good option, as the random I/O performance increase with more expensive spinning drives is not that dramatic (only on the order of 2x). Using SSDs or increasing RAM may be more effective in increasing I/O throughput. MongoDB and NUMA Hardware Running MongoDB on a system with Non-Uniform Access Memory (NUMA) can cause a number of operational problems, including slow performance for periods of time and high system process usage. When running MongoDB servers and clients on NUMA hardware, you should configure a memory interleave policy so that the host behaves in a non-NUMA fashion. MongoDB checks NUMA settings on start up when deployed on Linux (since version 2.0) and Windows (since version 2.6) machines. If the NUMA configuration may degrade performance, MongoDB prints a warning. See also: 204 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 • The MySQL “swap insanity” problem and the effects of NUMA62 post, which describes the effects of NUMA on databases. The post introduces NUMA and its goals, and illustrates how these goals are not compatible with production databases. Although the blog post addresses the impact of NUMA for MySQL, the issues for MongoDB are similar. • NUMA: An Overview63. Configuring NUMA on Windows On Windows, memory interleaving must be enabled through the machine’s BIOS. Please consult your system documentation for details. Configuring NUMA on Linux When running MongoDB on Linux, you may instead use the numactl command and start the MongoDB programs (mongod, including the config servers (page 670); mongos; or clients) in the following manner: numactl --interleave=all where is the path to the program you are starting. Then, disable zone reclaim in the proc settings using the following command: echo0 > /proc/sys/vm/zone_reclaim_mode To fully disable NUMA behavior, you must perform both operations. For more information, see the Documentation for /proc/sys/vm/*64. Disk and Storage Systems Swap Assign swap space for your systems. Allocating swap space can avoid issues with memory contention and can prevent the OOM Killer on Linux systems from killing mongod. For the MMAPv1 storage engine, the method mongod uses to map files to memory ensures that the operating system will never store MongoDB data in swap space. On Windows systems, using MMAPv1 requires extra swap space due to commitment limits. For details, see MongoDB on Windows (page 208). For the WiredTiger storage engine, given sufficient memory pressure, WiredTiger may store data in swap space . RAID Most MongoDB deployments should use disks backed by RAID-10. RAID-5 and RAID-6 do not typically provide sufficient performance to support a MongoDB deployment. Avoid RAID-0 with MongoDB deployments. While RAID-0 provides good write performance, it also provides limited availability and can lead to reduced performance on read operations, particularly when using Amazon’s EBS volumes. Remote Filesystems With the MMAPv1 storage engine, the Network File System protocol (NFS) is not recom- mended as you may see performance problems when both the data files and the journal files are hosted on NFS. You may experience better performance if you place the journal on local or iscsi volumes. With the WiredTiger storage engine, WiredTiger objects may be stored on remote file systems if the remote file system conforms to ISO/IEC 9945-1:1996 (POSIX.1). Because remote file systems are often slower than local file systems, using a remote file system for storage may degrade performance. If you decide to use NFS, add the following NFS options to your /etc/fstab file: bg, nolock, and noatime. 62http://jcole.us/blog/archives/2010/09/28/mysql-swap-insanity-and-the-numa-architecture/ 63https://queue.acm.org/detail.cfm?id=2513149 64http://www.kernel.org/doc/Documentation/sysctl/vm.txt 5.1. Administration Concepts 205 MongoDB Documentation, Release 3.0.7 Separate Components onto Different Storage Devices For improved performance, consider separating your database’s data, journal, and logs onto different storage devices, based on your application’s access and write pat- tern. For the WiredTiger storage engine, you can also store the indexes on a different storage device. See storage.wiredTiger.engineConfig.directoryForIndexes. Note: Using different storage devices will affect your ability to create snapshot-style backups of your data, since the files will be on different devices and volumes. Scheduling for Virtual Devices Local block devices attached to virtual machine instances via the hypervisor should use a noop scheduler for best performance. The noop scheduler allows the operating system to defer I/O scheduling to the underlying hypervisor. Architecture Replica Sets See the Replica Set Architectures (page 572) document for an overview of architectural considerations for replica set deployments. Sharded Clusters See the Sharded Cluster Production Architecture (page 672) document for an overview of rec- ommended sharded cluster architectures for production deployments. See also: Design Notes (page 222) Compression WiredTiger can compress collection data using either snappy or zlib compression library. snappy provides a lower compression rate but has little performance cost, whereas zlib provides better compression rate but has a higher performance cost. By default, WiredTiger uses snappy compression library. To change the compression setting, see storage.wiredTiger.collectionConfig.blockCompressor. WiredTiger uses prefix compression on all indexes by default. Platform Specific Considerations Note: MongoDB uses the GNU C Library65 (glibc) if available on a system. MongoDB requires version at least glibc-2.12-1.2.el6 to avoid a known bug with earlier versions. For best results use at least version 2.13. MongoDB on Linux 65http://www.gnu.org/software/libc/ 206 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 Kernel and File Systems When running MongoDB in production on Linux, it is recommended that you use Linux kernel version 2.6.36 or later. With the MMAPv1 storage engine, MongoDB preallocates its database files before using them and often creates large files. As such, you should use the XFS and EXT4 file systems. If possible, use XFS as it generally performs better with MongoDB. With the WiredTiger storage engine, use of XFS is strongly recommended to avoid performance issues that have been observed when using EXT4 with WiredTiger. • In general, if you use the XFS file system, use at least version 2.6.25 of the Linux Kernel. • In general, if you use the EXT4 file system, use at least version 2.6.23 of the Linux Kernel. • Some Linux distributions require different versions of the kernel to support using XFS and/or EXT4: Linux Distribution Filesystem Kernel Version CentOS 5.5 ext4, xfs 2.6.18-194.el5 CentOS 5.6 ext4, xfs 2.6.18-3.0.el5 CentOS 5.8 ext4, xfs 2.6.18-308.8.2.el5 CentOS 6.1 ext4, xfs 2.6.32-131.0.15.el6.x86_64 RHEL 5.6 ext4 2.6.18-3.0 RHEL 6.0 xfs 2.6.32-71 Ubuntu 10.04.4 LTS ext4, xfs 2.6.32-38-server Amazon Linux AMI release 2012.03 ext4 3.2.12-3.2.4.amzn1.x86_64 fsync() on Directories Important: MongoDB requires a filesystem that supports fsync() on directories. For example, HGFS and Virtual Box’s shared folders do not support this operation. Recommended Configuration For the MMAPv1 storage engine and the WiredTiger storage engines, consider the following recommendations: • Turn off atime for the storage volume containing the database files. • Set the file descriptor limit, -n, and the user process limit (ulimit), -u, above 20,000, according to the sug- gestions in the ulimit (page 293) document. A low ulimit will affect MongoDB when under heavy use and can produce errors and lead to failed connections to MongoDB processes and loss of service. • Disable Transparent Huge Pages, as MongoDB performs better with normal (4096 bytes) virtual memory pages. See Transparent Huge Pages Settings (page 225). • Disable NUMA in your BIOS. If that is not possible, see MongoDB on NUMA Hardware (page 204). • Configure SELinux on Red Hat. For more information, see Configure SELinux for MongoDB (page 9) and Configure SELinux for MongoDB Enterprise (page 36). For the MMAPv1 storage engine: • Ensure that readahead settings for the block devices that store the database files are appropriate. For random access use patterns, set low readahead values. A readahead of 32 (16kb) often works well. For a standard block device, you can run sudo blockdev --report to get the readahead settings and sudo blockdev --setra to change the readahead settings. Refer to your spe- cific operating system manual for more information. For all MongoDB deployments: • Use the Network Time Protocol (NTP) to synchronize time among your hosts. This is especially important in sharded clusters. 5.1. Administration Concepts 207 MongoDB Documentation, Release 3.0.7 MongoDB and TLS/SSL Libraries On Linux platforms, you may observe one of the following statements in the MongoDB log: /libssl.so.: no version information available (required by /usr/bin/mongod) /libcrypto.so.: no version information available (required by /usr/bin/mongod) These warnings indicate that the system’s TLS/SSL libraries are different from the TLS/SSL libraries that the mongod was compiled against. Typically these messages do not require intervention; however, you can use the following operations to determine the symbol versions that mongod expects: objdump -T /mongod | grep " SSL_" objdump -T /mongod | grep " CRYPTO_" These operations will return output that resembles one the of the following lines: 0000000000000000 DF *UND* 0000000000000000 libssl.so.10 SSL_write 0000000000000000 DF *UND* 0000000000000000 OPENSSL_1.0.0 SSL_write The last two strings in this output are the symbol version and symbol name. Compare these values with the values returned by the following operations to detect symbol version mismatches: objdump -T /libssl.so.1* objdump -T /libcrypto.so.1* This procedure is neither exact nor exhaustive: many symbols used by mongod from the libcrypto library do not begin with CRYPTO_. MongoDB on Windows MongoDB Using MMAPv1 Install Hotfix for MongoDB 2.6.6 and Later Microsoft has released a hotfix for Windows 7 and Windows Server 2008 R2, KB273128466, that repairs a bug in these operating systems’ use of memory-mapped files that adversely affects the performance of MongoDB using the MMAPv1 storage engine. Install this hotfix to obtain significant performance improvements on MongoDB 2.6.6 and later releases in the 2.6 series, which use MMAPv1 exclusively, and on 3.0 and later when using MMAPv1 as the storage engine. Configure Windows Page File For MMAPv1 Configure the page file such that the minimum and maximum page file size are equal and at least 32 GB. Use a multiple of this size if, during peak usage, you expect concurrent writes to many databases or collections. However, the page file size does not need to exceed the maximum size of the database. A large page file is needed as Windows requires enough space to accommodate all regions of memory mapped files made writable during peak usage, regardless of whether writes actually occur. The page file is not used for database storage and will not receive writes during normal MongoDB operation. As such, the page file will not affect performance, but it must exist and be large enough to accommodate Windows’ commitment rules during peak database use. Note: Dynamic page file sizing is too slow to accommodate the rapidly fluctuating commit charge of an active MongoDB deployment. This can result in transient overcommitment situations that may lead to abrupt server shutdown with a VirtualProtect error 1455. 66http://support.microsoft.com/kb/2731284 208 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 MongoDB 3.0 Using WiredTiger For MongoDB instances using the WiredTiger storage engine, performance on Windows is comparable to performance on Linux. MongoDB on Virtual Environments This section describes considerations when running MongoDB in some of the more common virtual environments. For all platforms, consider Scheduling for Virtual Devices (page 206). EC2 MongoDB is compatible with EC2. MongoDB Cloud Manager67 provides integration with Amazon Web Services (AWS) and lets you deploy new EC2 instances directly from MongoDB Cloud Manager. See Configure AWS Integration68 for more details. Azure For all MongoDB deployments using Azure, you must mount the volume that hosts the mongod instance’s dbPath with the Host Cache Preference READ/WRITE. This applies to all Azure deployments, using any guest operating system. If your volumes have inappropriate cache settings, MongoDB may eventually shut down with the following error: [DataFileSync] FlushViewOfFile for failed with error 1 ... [DataFileSync] Fatal Assertion 16387 These shut downs do not produce data loss when storage.journal.enabled is set to true. You can safely restart mongod at any time following this event. The performance characteristics of MongoDB may change with READ/WRITE caching enabled. The TCP keepalive on the Azure load balancer is 240 seconds by default, which can cause it to silently drop connec- tions if the TCP keepalive on your Azure systems is greater than this value. You should set tcp_keepalive_time to 120 to ameliorate this problem. On Linux systems: • To view the keep alive setting, you can use one of the following commands: sysctl net.ipv4.tcp_keepalive_time Or: cat /proc/sys/net/ipv4/tcp_keepalive_time The value is measured in seconds. • To change the tcp_keepalive_time value, you can use one of the following command: sudo sysctl -w net.ipv4.tcp_keepalive_time= Or: echo | sudo tee /proc/sys/net/ipv4/tcp_keepalive_time These operations do not persist across system reboots. To persist the setting, add the following line to /etc/sysctl.conf: net.ipv4.tcp_keepalive_time= 67https://cloud.mongodb.com/?jmp=docs 68https://docs.cloud.mongodb.com/tutorial/configure-aws-settings/ 5.1. Administration Concepts 209 MongoDB Documentation, Release 3.0.7 On Linux, mongod and mongos processes limit the keepalive to a maximum of 300 seconds (5 minutes) on their own sockets by overriding keepalive values greater than 5 minutes. For Windows systems: • To view the keep alive setting, issue the following command: reg query HKLM\SYSTEM\CurrentControlSet\Services\Tcpip\Parameters /v KeepAliveTime The registry value is not present by default. The system default, used if the value is absent, is 7200000 millisec- onds or 0x6ddd00 in hexadecimal. • To change the KeepAliveTime value, use the following command in an Administrator Command Prompt, where is expressed in hexadecimal (e.g. 0x0124c0 is 120000): reg add HKLM\SYSTEM\CurrentControlSet\Services\Tcpip\Parameters\ /v KeepAliveTime /d Windows users should consider the Windows Server Technet Article on KeepAliveTime69 for more information on setting keep alive for MongoDB deployments on Windows systems. VMWare MongoDB is compatible with VMWare. As some users have run into issues with VMWare’s memory overcommit feature, you should disable the feature. Further, MongoDB is known to run poorly with VMWare’s balloon driver (vmmemctl), so you should disable this as well. VMWare uses the balloon driver to reduce physical memory usage on the host hardware by allowing the hypervisor to swap to disk while hiding this fact from the guest, which continues to see the same amount of (virtual) physical memory. This interferes with MongoDB’s memory management, and you are likely to experience significant performance degradation. It is possible to clone a virtual machine running MongoDB. You might use this function to spin up a new virtual host to add as a member of a replica set. If you clone a VM with journaling enabled, the clone snapshot will be valid. If not using journaling, first stop mongod, then clone the VM, and finally, restart mongod. MongoDB on Solaris The MongoDB distribution for Solaris does not include support for the WiredTiger storage engine (page 92). Performance Monitoring iostat On Linux, use the iostat command to check if disk I/O is a bottleneck for your database. Specify a number of seconds when running iostat to avoid displaying stats covering the time since server boot. For example, the following command will display extended statistics and the time for each displayed report, with traffic in MB/s, at one second intervals: iostat -xmt 1 Key fields from iostat: •%util: this is the most useful field for a quick check, it indicates what percent of the time the device/drive is in use. • avgrq-sz: average request size. Smaller number for this value reflect more random IO operations. bwm-ng bwm-ng70 is a command-line tool for monitoring network use. If you suspect a network-based bottleneck, you may use bwm-ng to begin your diagnostic process. 69https://technet.microsoft.com/en-us/library/cc957549.aspx 70http://www.gropp.org/?id=projects&sub=bwm-ng 210 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 Backups To make backups of your MongoDB database, please refer to MongoDB Backup Methods Overview (page 188). Additional Resources • Blog Post: Capacity Planning and Hardware Provisioning for MongoDB In Ten Minutes71 • Whitepaper: MongoDB Multi-Data Center Deployments72 • Whitepaper: Security Architecture73 • Whitepaper: MongoDB Architecture Guide74 • Presentation: MongoDB Administration 10175 • MongoDB Production Readiness Consulting Package76 5.1.2 Data Management These document introduce data management practices and strategies for MongoDB deployments, including strategies for managing multi-data center deployments, managing larger file stores, and data lifecycle tools. Data Center Awareness (page 211) Presents the MongoDB features that allow application developers and database administrators to configure their deployments to be more data center aware or allow operational and location- based separation. Capped Collections (page 213) Capped collections provide a special type of size-constrained collections that preserve insertion order and can support high volume inserts. Expire Data from Collections by Setting TTL (page 215) TTL collections make it possible to automatically remove data from a collection based on the value of a timestamp and are useful for managing data like machine generated event data that are only useful for a limited period of time. Data Center Awareness MongoDB provides a number of features that allow application developers and database administrators to customize the behavior of a sharded cluster or replica set deployment so that MongoDB may be more “data center aware,” or allow operational and location-based separation. MongoDB also supports segregation based on functional parameters, to ensure that certain mongod instances are only used for reporting workloads or that certain high-frequency portions of a sharded collection only exist on specific shards. The following documents, found either in this section or other sections of this manual, provide information on cus- tomizing a deployment for operation- and location-based separation: Operational Segregation in MongoDB Deployments (page 212) MongoDB lets you specify that certain application operations use certain mongod instances. Tag Aware Sharding (page 682) Tags associate specific ranges of shard key values with specific shards for use in managing deployment patterns. 71https://www.mongodb.com/blog/post/capacity-planning-and-hardware-provisioning-mongodb-ten-minutes?jmp=docs 72http://www.mongodb.com/lp/white-paper/multi-dc?jmp=docs 73https://www.mongodb.com/lp/white-paper/mongodb-security-architecture?jmp=docs 74https://www.mongodb.com/lp/whitepaper/architecture-guide?jmp=docs 75http://www.mongodb.com/presentations/webinar-mongodb-administration-101?jmp=docs 76https://www.mongodb.com/products/consulting?jmp=docs#s_product_readiness 5.1. Administration Concepts 211 MongoDB Documentation, Release 3.0.7 Manage Shard Tags (page 730) Use tags to associate specific ranges of shard key values with specific shards. Operational Segregation in MongoDB Deployments Operational Overview MongoDB includes a number of features that allow database administrators and developers to segregate application operations to MongoDB deployments by functional or geographical groupings. This capability provides “data center awareness,” which allows applications to target MongoDB deployments with consideration of the physical location of the mongod instances. MongoDB supports segmentation of operations across different dimensions, which may include multiple data centers and geographical regions in multi-data center deployments, racks, networks, or power circuits in single data center deployments. MongoDB also supports segregation of database operations based on functional or operational parameters, to ensure that certain mongod instances are only used for reporting workloads or that certain high-frequency portions of a sharded collection only exist on specific shards. Specifically, with MongoDB, you can: • ensure write operations propagate to specific members of a replica set, or to specific members of replica sets. • ensure that specific members of a replica set respond to queries. • ensure that specific ranges of your shard key balance onto and reside on specific shards. • combine the above features in a single distributed deployment, on a per-operation (for read and write operations) and collection (for chunk distribution in sharded clusters distribution) basis. For full documentation of these features, see the following documentation in the MongoDB Manual: • Read Preferences (page 588), which controls how drivers help applications target read operations to members of a replica set. • Write Concerns (page 80), which controls how MongoDB ensures that write operations propagate to members of a replica set. • Replica Set Tags (page 635), which control how applications create and interact with custom groupings of replica set members to create custom application-specific read preferences and write concerns. • Tag Aware Sharding (page 682), which allows MongoDB administrators to define an application-specific bal- ancing policy, to control how documents belonging to specific ranges of a shard key distribute to shards in the sharded cluster. See also: Before adding operational segregation features to your application and MongoDB deployment, become familiar with all documentation of replication (page 559), and sharding (page 661). Additional Resource • Whitepaper: MongoDB Multi-Data Center Deployments77 • Webinar: Multi-Data Center Deployment78 Further Reading • The Write Concern (page 80) and Read Preference (page 588) documents, which address capabilities related to data center awareness. 77http://www.mongodb.com/lp/white-paper/multi-dc?jmp=docs 78https://www.mongodb.com/presentations/webinar-multi-data-center-deployment?jmp=docs 212 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 • Deploy a Geographically Redundant Replica Set (page 608). Additional Resource • Whitepaper: MongoDB Multi-Data Center Deployments79 • Webinar: Multi-Data Center Deployment80 Capped Collections Capped collections are fixed-size collections that support high-throughput operations that insert and retrieve docu- ments based on insertion order. Capped collections work in a way similar to circular buffers: once a collection fills its allocated space, it makes room for new documents by overwriting the oldest documents in the collection. See createCollection() or create for more information on creating capped collections. Capped collections have the following behaviors: • Capped collections guarantee preservation of the insertion order. As a result, queries do not need an index to return documents in insertion order. Without this indexing overhead, they can support higher insertion through- put. • Capped collections guarantee that insertion order is identical to the order on disk (natural order) and do so by prohibiting updates that increase document size. Capped collections only allow updates that fit the original document size, which ensures a document does not change its location on disk. • Capped collections automatically remove the oldest documents in the collection without requiring scripts or explicit remove operations. For example, the oplog.rs collection that stores a log of the operations in a replica set uses a capped collection. Consider the following potential use cases for capped collections: • Store log information generated by high-volume systems. Inserting documents in a capped collection without an index is close to the speed of writing log information directly to a file system. Furthermore, the built-in first-in-first-out property maintains the order of events, while managing storage use. • Cache small amounts of data in a capped collections. Since caches are read rather than write heavy, you would either need to ensure that this collection always remains in the working set (i.e. in RAM) or accept some write penalty for the required index or indexes. Recommendations and Restrictions • You can only make in-place updates of documents. If the update operation causes the document to grow beyond their original size, the update operation will fail. If you plan to update documents in a capped collection, create an index so that these update operations do not require a table scan. • If you update a document in a capped collection to a size smaller than its original size, and then a secondary resyncs from the primary, the secondary will replicate and allocate space based on the current smaller document size. If the primary then receives an update which increases the document back to its original size, the primary will accept the update but the secondary will fail with a failing update: objects in a capped ns cannot grow error message. 79http://www.mongodb.com/lp/white-paper/multi-dc?jmp=docs 80https://www.mongodb.com/presentations/webinar-multi-data-center-deployment?jmp=docs 5.1. Administration Concepts 213 MongoDB Documentation, Release 3.0.7 To prevent this error, create your secondary from a snapshot of one of the other up-to-date members of the replica set. Follow our tutorial on filesystem snapshots (page 249) to seed your new secondary. Seeding the secondary with a filesystem snapshot is the only way to guarantee the primary and secondary binary files are compatible. MongoDB Cloud Manager Backup snapshots are insufficient in this situation since you need more than the content of the secondary to match the primary. • You cannot delete documents from a capped collection. To remove all documents from a collection, use the drop() method to drop the collection. • You cannot shard a capped collection. • Capped collections created after 2.2 have an _id field and an index on the _id field by default. Capped collections created before 2.2 do not have an index on the _id field by default. If you are using capped collections with replication prior to 2.2, you should explicitly create an index on the _id field. Warning: If you have a capped collection in a replica set outside of the local database, before 2.2, you should create a unique index on _id. Ensure uniqueness using the unique: true option to the createIndex() method or by using an ObjectId for the _id field. Alternately, you can use the autoIndexId option to create when creating the capped collection, as in the Query a Capped Collec- tion (page 214) procedure. • Use natural ordering to retrieve the most recently inserted elements from the collection efficiently. This is (somewhat) analogous to tail on a log file. • The aggregation pipeline operator $out cannot write results to a capped collection. Procedures Create a Capped Collection You must create capped collections explicitly using the createCollection() method, which is a helper in the mongo shell for the create command. When creating a capped collection you must specify the maximum size of the collection in bytes, which MongoDB will pre-allocate for the collection. The size of the capped collection includes a small amount of space for internal overhead. db.createCollection( "log", { capped: true, size: 100000}) If the size field is less than or equal to 4096, then the collection will have a cap of 4096 bytes. Otherwise, MongoDB will raise the provided size to make it an integer multiple of 256. Additionally, you may also specify a maximum number of documents for the collection using the max field as in the following document: db.createCollection("log", { capped: true, size: 5242880, max: 5000}) Important: The size argument is always required, even when you specify max number of documents. MongoDB will remove older documents if a collection reaches the maximum size limit before it reaches the maximum document count. See createCollection() and create. Query a Capped Collection If you perform a find() on a capped collection with no ordering specified, MongoDB guarantees that the ordering of results is the same as the insertion order. 214 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 To retrieve documents in reverse insertion order, issue find() along with the sort() method with the $natural parameter set to -1, as shown in the following example: db.cappedCollection.find().sort( { $natural:-1}) Check if a Collection is Capped Use the isCapped() method to determine if a collection is capped, as follows: db.collection.isCapped() Convert a Collection to Capped You can convert a non-capped collection to a capped collection with the convertToCapped command: db.runCommand({"convertToCapped": "mycoll", size: 100000}); The size parameter specifies the size of the capped collection in bytes. Warning: This command obtains a global write lock and will block other operations until it has completed. Changed in version 2.2: Before 2.2, capped collections did not have an index on _id unless you specified autoIndexId to the create, after 2.2 this became the default. Automatically Remove Data After a Specified Period of Time For additional flexibility when expiring data, con- sider MongoDB’s TTL indexes, as described in Expire Data from Collections by Setting TTL (page 215). These indexes allow you to expire and remove data from normal collections using a special type, based on the value of a date-typed field and a TTL value for the index. TTL Collections (page 215) are not compatible with capped collections. Tailable Cursor You can use a tailable cursor with capped collections. Similar to the Unix tail -f command, the tailable cursor “tails” the end of a capped collection. As new documents are inserted into the capped collection, you can use the tailable cursor to continue retrieving documents. See Create Tailable Cursor (page 126) for information on creating a tailable cursor. Expire Data from Collections by Setting TTL New in version 2.2. This document provides an introduction to MongoDB’s “time to live” or TTL collection feature. TTL collections make it possible to store data in MongoDB and have the mongod automatically remove data after a specified number of seconds or at a specific clock time. Data expiration is useful for some classes of information, including machine generated event data, logs, and session information that only need to persist for a limited period of time. A special TTL index property (page 503) supports the implementation of TTL collections. The TTL feature relies on a background thread in mongod that reads the date-typed values in the index and removes expired documents from the collection. 5.1. Administration Concepts 215 MongoDB Documentation, Release 3.0.7 Procedures To create a TTL index (page 503), use the db.collection.createIndex() method with the expireAfterSeconds option on a field whose value is either a date (page 184) or an array that contains date values (page 184). Note: The TTL index is a single field index. Compound indexes do not support the TTL property. For more information on TTL indexes, see TTL Indexes (page 503). Expire Documents after a Specified Number of Seconds To expire data after a specified number of seconds has passed since the indexed field, create a TTL index on a field that holds values of BSON date type or an array of BSON date-typed objects and specify a positive non-zero value in the expireAfterSeconds field. A document will expire when the number of seconds in the expireAfterSeconds field has passed since the time specified in its indexed field. 81 For example, the following operation creates an index on the log_events collection’s createdAt field and spec- ifies the expireAfterSeconds value of 3600 to set the expiration time to be one hour after the time specified by createdAt. db.log_events.createIndex( { "createdAt":1 }, { expireAfterSeconds: 3600}) When adding documents to the log_events collection, set the createdAt field to the current time: db.log_events.insert( { "createdAt": new Date(), "logEvent":2, "logMessage": "Success!" }) MongoDB will automatically delete documents from the log_events collection when the document’s createdAt value 1 is older than the number of seconds specified in expireAfterSeconds. See also: $currentDate operator Expire Documents at a Specific Clock Time To expire documents at a specific clock time, begin by creating a TTL index on a field that holds values of BSON date type or an array of BSON date-typed objects and specify an expireAfterSeconds value of 0. For each document in the collection, set the indexed date field to a value corresponding to the time the document should expire. If the indexed date field contains a date in the past, MongoDB considers the document expired. For example, the following operation creates an index on the log_events collection’s expireAt field and specifies the expireAfterSeconds value of 0: db.log_events.createIndex( { "expireAt":1 }, { expireAfterSeconds:0}) For each document, set the value of expireAt to correspond to the time the document should expire. For instance, the following insert() operation adds a document that should expire at July 22, 2013 14:00:00. db.log_events.insert( { "expireAt": new Date('July 22, 2013 14:00:00'), "logEvent":2, 81 If the field contains an array of BSON date-typed objects, data expires if at least one of BSON date-typed object is older than the number of seconds specified in expireAfterSeconds. 216 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 "logMessage": "Success!" }) MongoDB will automatically delete documents from the log_events collection when the documents’ expireAt value is older than the number of seconds specified in expireAfterSeconds, i.e. 0 seconds older in this case. As such, the data expires at the specified expireAt value. 5.1.3 Optimization Strategies for MongoDB There are many factors that can affect database performance and responsiveness including index use, query structure, data models and application design, as well as operational factors such as architecture and system configuration. This section describes techniques for optimizing application performance with MongoDB. Analyzing MongoDB Performance (page 217) Discusses some of the factors that can influence MongoDB’s perfor- mance. Evaluate Performance of Current Operations (page 220) MongoDB provides introspection tools that describe the query execution process, to allow users to test queries and build more efficient queries. Optimize Query Performance (page 221) Introduces the use of projections (page 64) to reduce the amount of data MongoDB sends to clients. Design Notes (page 222) A collection of notes related to the architecture, design, and administration of MongoDB- based applications. Analyzing MongoDB Performance As you develop and operate applications with MongoDB, you may need to analyze the performance of the application and its database. When you encounter degraded performance, it is often a function of database access strategies, hardware availability, and the number of open database connections. Some users may experience performance limitations as a result of inadequate or inappropriate indexing strategies, or as a consequence of poor schema design patterns. Locking Performance (page 217) discusses how these can impact MongoDB’s internal locking. Performance issues may indicate that the database is operating at capacity and that it is time to add additional capacity to the database. In particular, the application’s working set should fit in the available physical memory. See Memory and the MMAPv1 Storage Engine (page 218) for more information on the working set. In some cases performance issues may be temporary and related to abnormal traffic load. As discussed in Number of Connections (page 218), scaling can help relax excessive traffic. Database Profiling (page 219) can help you to understand what operations are causing degradation. Locking Performance MongoDB uses a locking system to ensure data set consistency. If certain operations are long-running or a queue forms, performance will degrade as requests and operations wait for the lock. Lock-related slowdowns can be intermittent. To see if the lock has been affecting your performance, refer to the server-status-locks section and the globalLock section of the serverStatus output. Dividing locks.timeAcquiringMicros by locks.acquireWaitCount can give an approximate average wait time for a particular lock mode. locks.deadlockCount provide the number of times the lock acquisitions encountered deadlocks. 5.1. Administration Concepts 217 MongoDB Documentation, Release 3.0.7 If globalLock.currentQueue.total is consistently high, then there is a chance that a large number of re- quests are waiting for a lock. This indicates a possible concurrency issue that may be affecting performance. If globalLock.totalTime is high relative to uptime, the database has existed in a lock state for a significant amount of time. Long queries can result from ineffective use of indexes; non-optimal schema design; poor query structure; system architecture issues; or insufficient RAM resulting in page faults (page 218) and disk reads. Memory and the MMAPv1 Storage Engine Memory Use With the MMAPv1 (page 93) storage engine, MongoDB uses memory-mapped files to store data. Given a data set of sufficient size, the mongod process will allocate all available memory on the system for its use. While this is intentional and aids performance, the memory mapped files make it difficult to determine if the amount of RAM is sufficient for the data set. The memory usage statuses metrics of the serverStatus output can provide insight into MongoDB’s memory use. The mem.resident field provides the amount of resident memory in use. If this exceeds the amount of system memory and there is a significant amount of data on disk that isn’t in RAM, you may have exceeded the capacity of your system. You can inspect mem.mapped to check the amount of mapped memory that mongod is using. If this value is greater than the amount of system memory, some operations will require a page faults to read data from disk. Page Faults With the MMAPv1 storage engine, page faults can occur as MongoDB reads from or writes data to parts of its data files that are not currently located in physical memory. In contrast, operating system page faults happen when physical memory is exhausted and pages of physical memory are swapped to disk. MongoDB reports its triggered page faults as the total number of page faults in one second. To check for page faults, see the extra_info.page_faults value in the serverStatus output. Rapid increases in the MongoDB page fault counter may indicate that the server has too little physical memory. Page faults also can occur while accessing large data sets or scanning an entire collection. A single page fault completes quickly and is not problematic. However, in aggregate, large volumes of page faults typically indicate that MongoDB is reading too much data from disk. MongoDB can often “yield” read locks after a page fault, allowing other database processes to read while mongod loads the next page into memory. Yielding the read lock following a page fault improves concurrency, and also improves overall throughput in high volume systems. Increasing the amount of RAM accessible to MongoDB may help reduce the frequency of page faults. If this is not possible, you may want to consider deploying a sharded cluster or adding shards to your deployment to distribute load among mongod instances. See What are page faults? (page 775) for more information. Number of Connections In some cases, the number of connections between the applications and the database can overwhelm the ability of the server to handle requests. The following fields in the serverStatus document can provide insight: • globalLock.activeClients contains a counter of the total number of clients with active operations in progress or queued. • connections is a container for the following two fields: 218 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 – current the total number of current clients that connect to the database instance. – available the total number of unused connections available for new clients. If there are numerous concurrent application requests, the database may have trouble keeping up with demand. If this is the case, then you will need to increase the capacity of your deployment. For read-heavy applications, increase the size of your replica set and distribute read operations to secondary members. For write-heavy applications, deploy sharding and add one or more shards to a sharded cluster to distribute load among mongod instances. Spikes in the number of connections can also be the result of application or driver errors. All of the officially supported MongoDB drivers implement connection pooling, which allows clients to use and reuse connections more efficiently. Extremely high numbers of connections, particularly without corresponding workload is often indicative of a driver or other configuration error. Unless constrained by system-wide limits, MongoDB has no limit on incoming connections. On Unix-based systems, you can modify system limits using the ulimit command, or by editing your system’s /etc/sysctl file. See UNIX ulimit Settings (page 293) for more information. Database Profiling MongoDB’s “Profiler” is a database profiling system that can help identify inefficient queries and operations. The following profiling levels are available: Level Setting 0 Off. No profiling 1 On. Only includes “slow” operations 2 On. Includes all operations Enable the profiler by setting the profile value using the following command in the mongo shell: db.setProfilingLevel(1) The slowOpThresholdMs setting defines what constitutes a “slow” operation. To set the threshold above which the profiler considers operations “slow” (and thus, included in the level 1 profiling data), you can configure slowOpThresholdMs at runtime as an argument to the db.setProfilingLevel() operation. See The documentation of db.setProfilingLevel() for more information. By default, mongod records all “slow” queries to its log, as defined by slowOpThresholdMs. Note: Because the database profiler can negatively impact performance, only enable profiling for strategic intervals and as minimally as possible on production systems. You may enable profiling on a per-mongod basis. This setting will not propagate across a replica set or sharded cluster. You can view the output of the profiler in the system.profile collection of your database by issuing the show profile command in the mongo shell, or with the following operation: db.system.profile.find( { millis: { $gt: 100}}) This returns all operations that lasted longer than 100 milliseconds. Ensure that the value specified here (100, in this example) is above the slowOpThresholdMs threshold. 5.1. Administration Concepts 219 MongoDB Documentation, Release 3.0.7 You must use the $query operator to access the query field of documents within system.profile. Additional Resources • MongoDB Ops Optimization Consulting Package82 Evaluate Performance of Current Operations The following sections describe techniques for evaluating operational performance. Use the Database Profiler to Evaluate Operations Against the Database MongoDB provides a database profiler that shows performance characteristics of each operation against the database. Use the profiler to locate any queries or write operations that are running slow. You can use this information, for example, to determine what indexes to create. For more information, see Database Profiling (page 219). Use db.currentOp() to Evaluate mongod Operations The db.currentOp() method reports on current operations running on a mongod instance. Use explain to Evaluate Query Performance The cursor.explain() and db.collection.explain() methods return information on a query execu- tion, such as the index MongoDB selected to fulfill the query and execution statistics. You can run the methods in queryPlanner mode, executionStats mode, or allPlansExecution mode to control the amount of information returned. Example To use cursor.explain() on a query for documents matching the expression { a: 1 }, in the collection named records, use an operation that resembles the following in the mongo shell: db.records.find( { a:1 } ).explain("executionStats") For more information, see https://docs.mongodb.org/manual/reference/explain-results, cursor.explain(), db.collection.explain(), and Analyze Query Performance (page 114). Additional Resources • MongoDB Performance Evaluation and Tuning Consulting Package83 82https://www.mongodb.com/products/consulting?jmp=docs#ops_optimization 83https://www.mongodb.com/products/consulting?jmp=docs#performance_evaluation 220 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 Optimize Query Performance Create Indexes to Support Queries For commonly issued queries, create indexes (page 481). If a query searches multiple fields, create a compound index (page 488). Scanning an index is much faster than scanning a collection. The indexes structures are smaller than the documents reference, and store references in order. Example If you have a posts collection containing blog posts, and if you regularly issue a query that sorts on the author_name field, then you can optimize the query by creating an index on the author_name field: db.posts.createIndex( { author_name:1}) Indexes also improve efficiency on queries that routinely sort on a given field. Example If you regularly issue a query that sorts on the timestamp field, then you can optimize the query by creating an index on the timestamp field: Creating this index: db.posts.createIndex( { timestamp:1}) Optimizes this query: db.posts.find().sort( { timestamp:-1}) Because MongoDB can read indexes in both ascending and descending order, the direction of a single-key index does not matter. Indexes support queries, update operations, and some phases of the aggregation pipeline (page 441). Index keys that are of the BinData type are more efficiently stored in the index if: • the binary subtype value is in the range of 0-7 or 128-135, and • the length of the byte array is: 0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 12, 14, 16, 20, 24, or 32. Limit the Number of Query Results to Reduce Network Demand MongoDB cursors return results in groups of multiple documents. If you know the number of results you want, you can reduce the demand on network resources by issuing the limit() method. This is typically used in conjunction with sort operations. For example, if you need only 10 results from your query to the posts collection, you would issue the following command: db.posts.find().sort( { timestamp:-1 } ).limit(10) For more information on limiting results, see limit() Use Projections to Return Only Necessary Data When you need only a subset of fields from documents, you can achieve better performance by returning only the fields you need: 5.1. Administration Concepts 221 MongoDB Documentation, Release 3.0.7 For example, if in your query to the posts collection, you need only the timestamp, title, author, and abstract fields, you would issue the following command: db.posts.find( {}, { timestamp:1 , title:1 , author:1, abstract :1} ).sort( { timestamp:-1}) For more information on using projections, see Limit Fields to Return from a Query (page 109). Use $hint to Select a Particular Index In most cases the query optimizer (page 70) selects the optimal index for a specific operation; however, you can force MongoDB to use a specific index using the hint() method. Use hint() to support performance testing, or on some queries where you must select a field or field included in several indexes. Use the Increment Operator to Perform Operations Server-Side Use MongoDB’s $inc operator to increment or decrement values in documents. The operator increments the value of the field on the server side, as an alternative to selecting a document, making simple modifications in the client and then writing the entire document to the server. The $inc operator can also help avoid race conditions, which would result when two application instances queried for a document, manually incremented a field, and saved the entire document back at the same time. Additional Resources • MongoDB Performance Evaluation and Tuning Consulting Package84 Design Notes This page details features of MongoDB that may be important to keep in mind when developing applications. Schema Considerations Dynamic Schema Data in MongoDB has a dynamic schema. Collections do not enforce document structure. This facilitates iterative development and polymorphism. Nevertheless, collections often hold documents with highly ho- mogeneous structures. See Data Modeling Concepts (page 149) for more information. Some operational considerations include: • the exact set of collections to be used; • the indexes to be used: with the exception of the _id index, all indexes must be created explicitly; • shard key declarations: choosing a good shard key is very important as the shard key cannot be changed once set. Avoid importing unmodified data directly from a relational database. In general, you will want to “roll up” certain data into richer documents that take advantage of MongoDB’s support for embedded documents and nested arrays. 84https://www.mongodb.com/products/consulting?jmp=docs#performance_evaluation 222 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 Case Sensitive Strings MongoDB strings are case sensitive. So a search for "joe" will not find "Joe". Consider: • storing data in a normalized case format, or • using regular expressions ending with the i option, and/or • using $toLower or $toUpper in the aggregation framework (page 439). Type Sensitive Fields MongoDB data is stored in the BSON format, a binary encoded serialization of JSON-like documents. BSON encodes additional type information. See bsonspec.org85 for more information. Consider the following document which has a field x with the string value "123": { x: "123"} Then the following query which looks for a number value 123 will not return that document: db.mycollection.find( { x: 123}) General Considerations By Default, Updates Affect one Document To update multiple documents that meet your query criteria, set the update multi option to true or 1. See: Update Multiple Documents (page 78). Prior to MongoDB 2.2, you would specify the upsert and multi options in the update method as positional boolean options. See: the update method reference documentation. BSON Document Size Limit The BSON Document Size limit is currently set at 16MB per document. If you require larger documents, use GridFS (page 154). No Fully Generalized Transactions MongoDB does not have fully generalized transactions (page 82). If you model your data using rich documents that closely resemble your application’s objects, each logical object will be in one MongoDB document. MongoDB allows you to modify a document in a single atomic operation. These kinds of data modification pattern covers most common uses of transactions in other systems. Replica Set Considerations Use an Odd Number of Replica Set Members Replica sets (page 559) perform consensus elections. To ensure that elections will proceed successfully, either use an odd number of members, typically three, or else use an arbiter to ensure an odd number of votes. Keep Replica Set Members Up-to-Date MongoDB replica sets support automatic failover (page 580). It is impor- tant for your secondaries to be up-to-date. There are various strategies for assessing consistency: 1. Use monitoring tools to alert you to lag events. See Monitoring for MongoDB (page 191) for a detailed discus- sion of MongoDB’s monitoring options. 2. Specify appropriate write concern. 85http://bsonspec.org/#/specification 5.1. Administration Concepts 223 MongoDB Documentation, Release 3.0.7 3. If your application requires manual fail over, you can configure your secondaries as priority 0 (page 567). Priority 0 secondaries require manual action for a failover. This may be practical for a small replica set, but large deployments should fail over automatically. See also: replica set rollbacks (page 584). Sharding Considerations • Pick your shard keys carefully. You cannot choose a new shard key for a collection that is already sharded. • Shard key values are immutable. • When enabling sharding on an existing collection, MongoDB imposes a maximum size on those col- lections to ensure that it is possible to create chunks. For a detailed explanation of this limit, see: . To shard large amounts of data, create a new empty sharded collection, and ingest the data from the source collection using an application level import operation. • Unique indexes are not enforced across shards except for the shard key itself. See Enforce Unique Keys for Sharded Collections (page 732). • Consider pre-splitting (page 722) an empty sharded collection before a massive bulk import. Analyze Performance As you develop and operate applications with MongoDB, you may want to analyze the performance of the database as the application. Analyzing MongoDB Performance (page 217) discusses some of the operational factors that can influence performance. Additional Resources • MongoDB Ops Optimization Consulting Package86 5.2 Administration Tutorials The administration tutorials provide specific step-by-step instructions for performing common MongoDB setup, main- tenance, and configuration operations. Configuration, Maintenance, and Analysis (page 225) Describes routine management operations, including config- uration and performance analysis. Manage mongod Processes (page 229) Start, configure, and manage running mongod process. Rotate Log Files (page 236) Archive the current log files and start new ones. Continue reading from Configuration, Maintenance, and Analysis (page 225) for additional tutorials of funda- mental MongoDB maintenance procedures. Backup and Recovery (page 248) Outlines procedures for data backup and restoration with mongod instances and deployments. 86https://www.mongodb.com/products/consulting?jmp=docs#ops_optimization 224 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 Backup and Restore with Filesystem Snapshots (page 249) An outline of procedures for creating MongoDB data set backups using system-level file snapshot tool, such as LVM or native storage appliance tools. Backup and Restore Sharded Clusters (page 259) Detailed procedures and considerations for backing up sharded clusters and single shards. Recover Data after an Unexpected Shutdown (page 268) Recover data from MongoDB data files that were not properly closed or have an invalid state. Continue reading from Backup and Recovery (page 248) for additional tutorials of MongoDB backup and re- covery procedures. MongoDB Scripting (page 271) An introduction to the scripting capabilities of the mongo shell and the scripting capabilities embedded in MongoDB instances. MongoDB Tutorials (page 289) A complete list of tutorials in the MongoDB Manual that address MongoDB opera- tion and use. 5.2.1 Configuration, Maintenance, and Analysis The following tutorials describe routine management operations, including configuration and performance analysis: Disable Transparent Huge Pages (THP) (page 225) Describes Transparent Huge Pages (THP) and provides detailed instructions on disabling them. Use Database Commands (page 228) The process for running database commands that provide basic database oper- ations. Manage mongod Processes (page 229) Start, configure, and manage running mongod process. Terminate Running Operations (page 231) Stop in progress MongoDB client operations using db.killOp() and maxTimeMS(). Analyze Performance of Database Operations (page 232) Collect data that introspects the performance of query and update operations on a mongod instance. Rotate Log Files (page 236) Archive the current log files and start new ones. Manage Journaling (page 238) Describes the procedures for configuring and managing MongoDB’s journaling sys- tem which allows MongoDB to provide crash resiliency and durability. Store a JavaScript Function on the Server (page 240) Describes how to store JavaScript functions on a MongoDB server. Upgrade to the Latest Revision of MongoDB (page 241) Introduces the basic process for upgrading a MongoDB de- ployment between different minor release versions. Monitor MongoDB With SNMP on Linux (page 244) The SNMP extension, available in MongoDB Enterprise, al- lows MongoDB to provide database metrics via SNMP. Monitor MongoDB Windows with SNMP (page 245) The SNMP extension, available in the Windows build of Mon- goDB Enterprise, allows MongoDB to provide database metrics via SNMP. Troubleshoot SNMP (page 247) Outlines common errors and diagnostic processes useful for deploying MongoDB Enterprise with SNMP support. Disable Transparent Huge Pages (THP) Transparent Huge Pages (THP) is a Linux memory management system that reduces the overhead of Translation Lookaside Buffer (TLB) lookups on machines with large amounts of memory by using larger memory pages. 5.2. Administration Tutorials 225 MongoDB Documentation, Release 3.0.7 However, database workloads often perform poorly with THP, because they tend to have sparse rather than contiguous memory access patterns. You should disable THP on Linux machines to ensure best performance with MongoDB. Init Script Important: If you are using tuned or ktune (for example, if you are running Red Hat or CentOS 6+), you must additionally configure them so that THP is not re-enabled. See Using tuned and ktune (page 227). Step 1: Create the init.d script. Create the following file at /etc/init.d/disable-transparent-hugepages: #!/bin/sh ### BEGIN INIT INFO # Provides: disable-transparent-hugepages # Required-Start: $local_fs # Required-Stop: # X-Start-Before: mongod mongodb-mms-automation-agent # Default-Start: 2 3 4 5 # Default-Stop: 0 1 6 # Short-Description: Disable Linux transparent huge pages # Description: Disable Linux transparent huge pages, to improve # database performance. ### END INIT INFO case $1 in start) if [ -d /sys/kernel/mm/transparent_hugepage]; then thp_path=/sys/kernel/mm/transparent_hugepage elif [ -d /sys/kernel/mm/redhat_transparent_hugepage]; then thp_path=/sys/kernel/mm/redhat_transparent_hugepage else return 0 fi echo 'never'> ${thp_path}/enabled echo 'never'> ${thp_path}/defrag unset thp_path ;; esac Step 2: Make it executable. Run the following command to ensure that the init script can be used: sudo chmod 755 /etc/init.d/disable-transparent-hugepages Step 3: Configure your operating system to run it on boot. Use the appropriate command to configure the new init script on your Linux distribution. 226 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 Distribution Command Ubuntu and Debian sudo update-rc.d disable-transparent-hugepages defaults SUSE sudo insserv /etc/init.d/disable-transparent-hugepages Red Hat, CentOS, Amazon Linux, and derivatives sudo chkconfig --add disable-transparent-hugepages Step 4: Override tuned and ktune, if applicable If you are using tuned or ktune (for example, if you are running Red Hat or CentOS 6+) you must now configure them to preserve the above settings. Using tuned and ktune Important: If using tuned or ktune, you must perform this step in addition to installing the init script. tuned and ktune are dynamic kernel tuning tools available on Red Hat and CentOS that can disable transparent huge pages. To disable transparent huge pages in tuned or ktune, you need to edit or create a new profile that sets THP to never. Red Hat/CentOS 6 Step 1: Create a new profile. Create a new profile from an existing default profile by copying the relevant directory. In the example we use the default profile as the base and call our new profile no-thp. sudo cp -r /etc/tune-profiles/default /etc/tune-profiles/no-thp Step 2: Edit ktune.sh. Edit /etc/tune-profiles/no-thp/ktune.sh and add the following: set_transparent_hugepages never to the start() block of the file, before the return 0 statement. Step 3: Enable the new profile. Finally, enable the new profile by issuing: sudo tuned-adm profile no-thp Red Hat/CentOS 7 Step 1: Create a new profile. Create a new tuned profile directory: sudo mkdir /etc/tuned/no-thp 5.2. Administration Tutorials 227 MongoDB Documentation, Release 3.0.7 Step 2: Edit tuned.conf. Create and edit /etc/tuned/no-thp/tuned.conf so that it contains the fol- lowing: [main] include=virtual-guest [vm] transparent_hugepages=never Step 3: Enable the new profile. Finally, enable the new profile by issuing: sudo tuned-adm profile no-thp Test Your Changes You can check the status of THP support by issuing the following commands: cat/sys/kernel/mm/transparent_hugepage/enabled cat/sys/kernel/mm/transparent_hugepage/defrag On Red Hat Enterprise Linux, CentOS, and potentially other Red Hat-based derivatives, you may instead need to use the following: cat/sys/kernel/mm/redhat_transparent_hugepage/enabled cat/sys/kernel/mm/redhat_transparent_hugepage/defrag For both files, the correct output resembles: always madvise [never] Use Database Commands The MongoDB command interface provides access to all non CRUD database operations. Fetching server stats, initializing a replica set, and running a map-reduce job are all accomplished with commands. See https://docs.mongodb.org/manual/reference/command for list of all commands sorted by func- tion. Database Command Form You specify a command first by constructing a standard BSON document whose first key is the name of the command. For example, specify the isMaster command using the following BSON document: { isMaster:1} Issue Commands The mongo shell provides a helper method for running commands called db.runCommand(). The following operation in mongo runs the above command: db.runCommand( { isMaster:1}) 228 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 Many drivers provide an equivalent for the db.runCommand() method. Internally, running commands with db.runCommand() is equivalent to a special query against the $cmd collection. Many common commands have their own shell helpers or wrappers in the mongo shell and drivers, such as the db.isMaster() method in the mongo JavaScript shell. You can use the maxTimeMS option to specify a time limit for the execution of a command, see Terminate a Command (page 232) for more information on operation termination. admin Database Commands You must run some commands on the admin database. Normally, these operations resemble the followings: use admin db.runCommand( {buildInfo:1}) However, there’s also a command helper that automatically runs the command in the context of the admin database: db._adminCommand( {buildInfo:1}) Command Responses All commands return, at minimum, a document with an ok field indicating whether the command has succeeded: { 'ok':1} Failed commands return the ok field with a value of 0. Manage mongod Processes MongoDB runs as a standard program. You can start MongoDB from a command line by issuing the mongod com- mand and specifying options. For a list of options, see the mongod reference. MongoDB can also run as a Windows service. For details, see Configure a Windows Service for MongoDB (page 31). To install MongoDB, see Install MongoDB (page 5). The following examples assume the directory containing the mongod process is in your system paths. The mongod process is the primary database process that runs on an individual server. mongos provides a coherent MongoDB interface equivalent to a mongod from the perspective of a client. The mongo binary provides the administrative shell. This document discusses the mongod process; however, some portions of this document may be applicable to mongos instances. Start mongod Processes By default, MongoDB stores data in the /data/db directory. On Windows, MongoDB stores data in C:\data\db. On all platforms, MongoDB listens for connections from clients on port 27017. To start MongoDB using all defaults, issue the following command at the system shell: mongod 5.2. Administration Tutorials 229 MongoDB Documentation, Release 3.0.7 Specify a Data Directory If you want mongod to store data files at a path other than /data/db you can specify a dbPath. The dbPath must exist before you start mongod. If it does not exist, create the directory and the permissions so that mongod can read and write data to this path. For more information on permissions, see the security operations documentation (page 432). To specify a dbPath for mongod to use as a data directory, use the --dbpath option. The following invocation will start a mongod instance and store data in the /srv/mongodb path mongod --dbpath /srv/mongodb/ Specify a TCP Port Only a single process can listen for connections on a network interface at a time. If you run multiple mongod processes on a single machine, or have other processes that must use this port, you must assign each a different port to listen on for client connections. To specify a port to mongod, use the --port option on the command line. The following command starts mongod listening on port 12345: mongod --port 12345 Use the default port number when possible, to avoid confusion. Start mongod as a Daemon To run a mongod process as a daemon (i.e. fork), and write its output to a log file, use the --fork and --logpath options. You must create the log directory; however, mongod will create the log file if it does not exist. The following command starts mongod as a daemon and records log output to /var/log/mongodb.log. mongod --fork --logpath /var/log/mongodb.log Additional Configuration Options For an overview of common configurations and deployments for common use cases, see Run-time Database Configuration (page 196). Stop mongod Processes In a clean shutdown a mongod completes all pending operations, flushes all data to data files, and closes all data files. Other shutdowns are unclean and can compromise the validity of the data files. To ensure a clean shutdown, always shutdown mongod instances using one of the following methods: Use shutdownServer() Shut down the mongod from the mongo shell using the db.shutdownServer() method as follows: use admin db.shutdownServer() Calling the same method from a init script accomplishes the same result. For systems with authorization enabled, users may only issue db.shutdownServer() when authenticated to the admin database or via the localhost interface on systems without authentication enabled. 230 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 Use --shutdown From the Linux command line, shut down the mongod using the --shutdown option in the following command: mongod --shutdown Use CTRL-C When running the mongod instance in interactive mode (i.e. without --fork), issue Control-C to perform a clean shutdown. Use kill From the Linux command line, shut down a specific mongod instance using the following command: kill Warning: Never use kill -9 (i.e. SIGKILL) to terminate a mongod instance. Stop a Replica Set Procedure If the mongod is the primary in a replica set, the shutdown process for this mongod instance has the following steps: 1. Check how up-to-date the secondaries are. 2. If no secondary is within 10 seconds of the primary, mongod will return a message that it will not shut down. You can pass the shutdown command a timeoutSecs argument to wait for a secondary to catch up. 3. If there is a secondary within 10 seconds of the primary, the primary will step down and wait for the secondary to catch up. 4. After 60 seconds or once the secondary has caught up, the primary will shut down. Force Replica Set Shutdown If there is no up-to-date secondary and you want the primary to shut down, issue the shutdown command with the force argument, as in the following mongo shell operation: db.adminCommand({shutdown:1, force: true}) To keep checking the secondaries for a specified number of seconds if none are immediately up-to-date, issue shutdown with the timeoutSecs argument. MongoDB will keep checking the secondaries for the specified number of seconds if none are immediately up-to-date. If any of the secondaries catch up within the allotted time, the primary will shut down. If no secondaries catch up, it will not shut down. The following command issues shutdown with timeoutSecs set to 5: db.adminCommand({shutdown:1, timeoutSecs:5}) Alternately you can use the timeoutSecs argument with the db.shutdownServer() method: db.shutdownServer({timeoutSecs:5}) Terminate Running Operations Overview MongoDB provides two facilitates to terminate running operations: maxTimeMS() and db.killOp(). Use these operations as needed to control the behavior of operations in a MongoDB deployment. 5.2. Administration Tutorials 231 MongoDB Documentation, Release 3.0.7 Available Procedures maxTimeMS New in version 2.6. The maxTimeMS() method sets a time limit for an operation. When the operation reaches the specified time limit, MongoDB interrupts the operation at the next interrupt point. Terminate a Query From the mongo shell, use the following method to set a time limit of 30 milliseconds for this query: db.location.find( { "town":{ "$regex": "(Pine Lumber)", "$options": 'i' } } ).maxTimeMS(30) Terminate a Command Consider a potentially long running operation using distinct to return each dis- tinct‘‘collection‘‘ field that has a city key: db.runCommand( { distinct: "collection", key: "city"}) You can add the maxTimeMS field to the command document to set a time limit of 45 milliseconds for the operation: db.runCommand( { distinct: "collection", key: "city", maxTimeMS: 45}) db.getLastError() and db.getLastErrorObj() will return errors for interrupted options: { "n":0, "connectionId":1, "err": "operation exceeded time limit", "ok":1} killOp The db.killOp() method interrupts a running operation at the next interrupt point. db.killOp() identifies the target operation by operation ID. db.killOp() Warning: Terminate running operations with extreme caution. Only use db.killOp() to terminate operations initiated by clients and do not terminate internal database operations. Related To return a list of running operations see db.currentOp(). Analyze Performance of Database Operations The database profiler collects fine grained data about MongoDB write operations, cursors, database commands on a running mongod instance. You can enable profiling on a per-database or per-instance basis. The profiling level (page 233) is also configurable when enabling profiling. The database profiler writes all the data it collects to the system.profile (page 297) collection, which is a capped collection (page 213). See Database Profiler Output (page 298) for overview of the data in the system.profile (page 297) documents created by the profiler. 232 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 This document outlines a number of key administration options for the database profiler. For additional related infor- mation, consider the following resources: • Database Profiler Output (page 298) • Profile Command • db.currentOp() Profiling Levels The following profiling levels are available: • 0 - the profiler is off, does not collect any data. mongod always writes operations longer than the slowOpThresholdMs threshold to its log. • 1 - collects profiling data for slow operations only. By default slow operations are those slower than 100 milliseconds. You can modify the threshold for “slow” operations with the slowOpThresholdMs runtime option or the setParameter command. See the Specify the Threshold for Slow Operations (page 233) section for more information. • 2 - collects profiling data for all database operations. Enable Database Profiling and Set the Profiling Level You can enable database profiling from the mongo shell or through a driver using the profile command. This section will describe how to do so from the mongo shell. See your driver documentation if you want to control the profiler from within your application. When you enable profiling, you also set the profiling level (page 233). The profiler records data in the system.profile (page 297) collection. MongoDB creates the system.profile (page 297) collection in a database after you enable profiling for that database. To enable profiling and set the profiling level, use the db.setProfilingLevel() helper in the mongo shell, passing the profiling level as a parameter. For example, to enable profiling for all database operations, consider the following operation in the mongo shell: db.setProfilingLevel(2) The shell returns a document showing the previous level of profiling. The "ok" : 1 key-value pair indicates the operation succeeded: { "was":0, "slowms": 100, "ok":1} To verify the new setting, see the Check Profiling Level (page 234) section. Specify the Threshold for Slow Operations The threshold for slow operations applies to the entire mongod in- stance. When you change the threshold, you change it for all databases on the instance. Important: Changing the slow operation threshold for the database profiler also affects the profiling subsystem’s slow operation threshold for the entire mongod instance. Always set the threshold to the highest useful value. By default the slow operation threshold is 100 milliseconds. Databases with a profiling level of 1 will log operations slower than 100 milliseconds. 5.2. Administration Tutorials 233 MongoDB Documentation, Release 3.0.7 To change the threshold, pass two parameters to the db.setProfilingLevel() helper in the mongo shell. The first parameter sets the profiling level for the current database, and the second sets the default slow operation threshold for the entire mongod instance. For example, the following command sets the profiling level for the current database to 0, which disables profiling, and sets the slow-operation threshold for the mongod instance to 20 milliseconds. Any database on the instance with a profiling level of 1 will use this threshold: db.setProfilingLevel(0,20) Check Profiling Level To view the profiling level (page 233), issue the following from the mongo shell: db.getProfilingStatus() The shell returns a document similar to the following: { "was":0, "slowms": 100} The was field indicates the current level of profiling. The slowms field indicates how long an operation must exist in milliseconds for an operation to pass the “slow” threshold. MongoDB will log operations that take longer than the threshold if the profiling level is 1. This document returns the profiling level in the was field. For an explanation of profiling levels, see Profiling Levels (page 233). To return only the profiling level, use the db.getProfilingLevel() helper in the mongo as in the following: db.getProfilingLevel() Disable Profiling To disable profiling, use the following helper in the mongo shell: db.setProfilingLevel(0) Enable Profiling for an Entire mongod Instance For development purposes in testing environments, you can enable database profiling for an entire mongod instance. The profiling level applies to all databases provided by the mongod instance. To enable profiling for a mongod instance, pass the following parameters to mongod at startup or within the configuration file: mongod --profile=1 --slowms=15 This sets the profiling level to 1, which collects profiling data for slow operations only, and defines slow operations as those that last longer than 15 milliseconds. See also: mode and slowOpThresholdMs. Database Profiling and Sharding You cannot enable profiling on a mongos instance. To enable profiling in a shard cluster, you must enable profiling for each mongod instance in the cluster. View Profiler Data The database profiler logs information about database operations in the system.profile (page 297) collection. 234 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 To view profiling information, query the system.profile (page 297) collection. You can use $comment to add data to the query document to make it easier to analyze data from the profiler. To view example queries, see Profiler Overhead (page 236). For an explanation of the output data, see Database Profiler Output (page 298). Example Profiler Data Queries This section displays example queries to the system.profile (page 297) col- lection. For an explanation of the query output, see Database Profiler Output (page 298). To return the most recent 10 log entries in the system.profile (page 297) collection, run a query similar to the following: db.system.profile.find().limit(10).sort( { ts:-1 } ).pretty() To return all operations except command operations ($cmd), run a query similar to the following: db.system.profile.find( { op: { $ne: 'command' } } ).pretty() To return operations for a particular collection, run a query similar to the following. This example returns operations in the mydb database’s test collection: db.system.profile.find( { ns: 'mydb.test' } ).pretty() To return operations slower than 5 milliseconds, run a query similar to the following: db.system.profile.find( { millis: { $gt:5 } } ).pretty() To return information from a certain time range, run a query similar to the following: db.system.profile.find( { ts:{ $gt: new ISODate("2012-12-09T03:00:00Z"), $lt: new ISODate("2012-12-09T03:40:00Z") } } ).pretty() The following example looks at the time range, suppresses the user field from the output to make it easier to read, and sorts the results by how long each operation took to run: db.system.profile.find( { ts:{ $gt: new ISODate("2011-07-12T03:00:00Z"), $lt: new ISODate("2011-07-12T03:40:00Z") } }, { user:0} ).sort( { millis:-1}) Show the Five Most Recent Events On a database that has profiling enabled, the show profile helper in the mongo shell displays the 5 most recent operations that took at least 1 millisecond to execute. Issue show profile from the mongo shell, as follows: show profile 5.2. Administration Tutorials 235 MongoDB Documentation, Release 3.0.7 Profiler Overhead When enabled, profiling has a minor effect on performance. The system.profile (page 297) collection is a capped collection with a default size of 1 megabyte. A collection of this size can typically store several thousand profile documents, but some application may use more or less profiling data per operation. Change Size of system.profile Collection on the Primary To change the size of the system.profile (page 297) collection, you must: 1. Disable profiling. 2. Drop the system.profile (page 297) collection. 3. Create a new system.profile (page 297) collection. 4. Re-enable profiling. For example, to create a new system.profile (page 297) collections that’s 4000000 bytes, use the following sequence of operations in the mongo shell: db.setProfilingLevel(0) db.system.profile.drop() db.createCollection( "system.profile", { capped: true, size:4000000}) db.setProfilingLevel(1) Change Size of system.profile Collection on a Secondary To change the size of the system.profile (page 297) collection on a secondary, you must stop the secondary, run it as a standalone, and then perform the steps above. When done, restart the standalone as a member of the replica set. For more information, see Perform Maintenance on Replica Set Members (page 630). Additional Resources • MongoDB Performance Evaluation and Tuning Consulting Package87 Rotate Log Files Overview When used with the --logpath option or systemLog.path setting, mongod and mongos instances report a live account of all activity and operations to a log file. When reporting activity data to a log file, by default, MongoDB only rotates logs in response to the logRotate command, or when the mongod or mongos process receives a SIGUSR1 signal from the operating system. MongoDB’s standard log rotation approach archives the current log file and starts a new one. To do this, the mongod or mongos instance renames the current log file by appending a UTC timestamp to the filename, in ISODate format. It then opens a new log file, closes the old log file, and sends all new log entries to the new log file. You can also configure MongoDB to support the Linux/Unix logrotate utility by setting systemLog.logRotate or --logRotate to reopen. With reopen, mongod or mongos closes the log file, and then reopens a log file with the same name, expecting that another process renamed the file prior to rotation. 87https://www.mongodb.com/products/consulting?jmp=docs#performance_evaluation 236 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 Finally, you can configure mongod to send log data to the syslog. using the --syslog option. In this case, you can take advantage of alternate logrotation tools. See also: For information on logging, see the Process Logging (page 194) section. Default Log Rotation Behavior By default, MongoDB uses the --logRotate rename behavior. With rename, mongod or mongos renames the current log file by appending a UTC timestamp to the filename, opens a new log file, closes the old log file, and sends all new log entries to the new log file. Step 1: Start a mongod instance. mongod -v --logpath /var/log/mongodb/server1.log You can also explicitly specify logRotate --rename. Step 2: List the log files In a separate terminal, list the matching files: ls /var/log/mongodb/server1.log* The results should include one log file, server1.log. Step 3: Rotate the log file. Rotate the log file by issuing the logRotate command from the admin database in a mongo shell: use admin db.runCommand({ logRotate :1}) Step 4: View the new log files List the new log files to view the newly-created log: ls /var/log/mongodb/server1.log* There should be two log files listed: server1.log, which is the log file that mongod or mongos made when it reopened the log file, and server1.log., the renamed original log file. Rotating log files does not modify the “old” rotated log files. When you rotate a log, you rename the server1.log file to include the timestamp, and a new, empty server1.log file receives all new log input. Log Rotation with --logRotate reopen New in version 3.0.0. Log rotation with --logRotate reopen closes and opens the log file following the typical Linux/Unix log rotate behavior. Step 1: Start a mongod instance, specifying the reopen --logRotate behavior. mongod -v --logpath /var/log/mongodb/server1.log --logRotate reopen --logappend You must use the --logappend option with --logRotate reopen. 5.2. Administration Tutorials 237 MongoDB Documentation, Release 3.0.7 Step 2: List the log files In a separate terminal, list the matching files: ls /var/log/mongodb/server1.log* The results should include one log file, server1.log. Step 3: Rotate the log file. Rotate the log file by issuing the logRotate command from the admin database in a mongo shell: use admin db.runCommand({ logRotate :1}) You should rename the log file using an external process, following the typical Linux/Unix log rotate behavior. Syslog Log Rotation New in version 2.2. With syslog log rotation, mongod sends log data to the syslog rather than writing it to a file. Step 1: Start a mongod instance with the --syslog option mongod --syslog Do not include --logpath. Since --syslog tells mongod to send log data to the syslog, specifying a --logpath will causes an error. To specify the facility level used when logging messages to the syslog, use the --syslogFacility option or systemLog.syslogFacility configuration setting. Step 2: Rotate the log. Store and rotate the log output using your systems default log rotation mechanism. Forcing a Log Rotation with SIGUSR1 For Linux and Unix-based systems, you can use the SIGUSR1 signal to rotate the logs for a single process, as in the following: kill -SIGUSR1 Manage Journaling MongoDB uses write ahead logging to an on-disk journal to guarantee write operation (page 75) durability and to provide crash resiliency. Before applying a change to the data files, MongoDB writes the change operation to the journal. If MongoDB should terminate or encounter an error before it can write the changes from the journal to the data files, MongoDB can re-apply the write operation and maintain a consistent state. Without a journal, if mongod exits unexpectedly, you must assume your data is in an inconsistent state, and you must run either repair (page 268) or, preferably, resync (page 633) from a clean member of the replica set. With journaling enabled, if mongod stops unexpectedly, the program can recover everything written to the journal, and the data remains in a consistent state. By default, the greatest extent of lost writes, i.e., those not made to the journal, are those made in the last 100 milliseconds. See commitIntervalMs for more information on the default. 238 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 With journaling, if you want a data set to reside entirely in RAM, you need enough RAM to hold the data set plus the “write working set.” The “write working set” is the amount of unique data you expect to see written between re-mappings of the private view. For information on views, see Storage Views used in Journaling (page 315). Important: Changed in version 2.0: For 64-bit builds of mongod, journaling is enabled by default. For other platforms, see storage.journal.enabled. Procedures Enable Journaling Changed in version 2.0: For 64-bit builds of mongod, journaling is enabled by default. To enable journaling, start mongod with the --journal command line option. If no journal files exist, when mongod starts, it must preallocate new journal files. During this operation, the mongod is not listening for connections until preallocation completes: for some systems this may take a several minutes. During this period your applications and the mongo shell are not available. Disable Journaling Warning: Do not disable journaling on production systems. If your mongod instance stops without shutting down cleanly unexpectedly for any reason, (e.g. power failure) and you are not running with journaling, then you must recover from an unaffected replica set member or backup, as described in repair (page 268). To disable journaling, start mongod with the --nojournal command line option. Get Commit Acknowledgment You can get commit acknowledgment with the Write Concern (page 80) and the j option. For details, see Write Concern Reference (page 133). Avoid Preallocation Lag To avoid preallocation lag (page 314), you can preallocate files in the journal directory by copying them from another instance of mongod. Preallocated files do not contain data. It is safe to later remove them. But if you restart mongod with journaling, mongod will create them again. Example The following sequence preallocates journal files for an instance of mongod running on port 27017 with a database path of /data/db. For demonstration purposes, the sequence starts by creating a set of journal files in the usual way. 1. Create a temporary directory into which to create a set of journal files: mkdir ~/tmpDbpath 2. Create a set of journal files by staring a mongod instance that uses the temporary directory: mongod --port 10000 --dbpath ~/tmpDbpath --journal 3. When you see the following log output, indicating mongod has the files, press CONTROL+C to stop the mongod instance: [initandlisten] waiting for connections on port 10000 4. Preallocate journal files for the new instance of mongod by moving the journal files from the data directory of the existing instance to the data directory of the new instance: 5.2. Administration Tutorials 239 MongoDB Documentation, Release 3.0.7 mv ~/tmpDbpath/journal /data/db/ 5. Start the new mongod instance: mongod --port 27017 --dbpath /data/db --journal Monitor Journal Status Use the following commands and methods to monitor journal status: • serverStatus The serverStatus command returns database status information that is useful for assessing performance. • journalLatencyTest Use journalLatencyTest to measure how long it takes on your volume to write to the disk in an append- only fashion. You can run this command on an idle system to get a baseline sync time for journaling. You can also run this command on a busy system to see the sync time on a busy system, which may be higher if the journal directory is on the same volume as the data files. The journalLatencyTest command also provides a way to check if your disk drive is buffering writes in its local cache. If the number is very low (i.e., less than 2 milliseconds) and the drive is non-SSD, the drive is probably buffering writes. In that case, enable cache write-through for the device in your operating system, unless you have a disk controller card with battery backed RAM. Change the Group Commit Interval Changed in version 2.0. You can set the group commit interval using the --journalCommitInterval command line option. The allowed range is 2 to 300 milliseconds. Lower values increase the durability of the journal at the expense of disk performance. Recover Data After Unexpected Shutdown On a restart after a crash, MongoDB replays all journal files in the journal directory before the server becomes available. If MongoDB must replay journal files, mongod notes these events in the log output. There is no reason to run repairDatabase in these situations. Store a JavaScript Function on the Server Note: Do not store application logic in the database. There are performance limitations to running JavaScript inside of MongoDB. Application code also is typically most effective when it shares version control with the application itself. There is a special system collection named system.js that can store JavaScript functions for reuse. To store a function, you can use the db.collection.save(), as in the following examples: db.system.js.save( { _id: "echoFunction", value: function(x) { return x; } } ) db.system.js.save( 240 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 { _id: "myAddFunction", value: function (x, y){ return x+ y; } } ); • The _id field holds the name of the function and is unique per database. • The value field holds the function definition. Once you save a function in the system.js collection, you can use the function from any JavaScript context; e.g. $where operator, mapReduce command or db.collection.mapReduce(). In the mongo shell, you can use db.loadServerScripts() to load all the scripts saved in the system.js collection for the current database. Once loaded, you can invoke the functions directly in the shell, as in the following example: db.loadServerScripts(); echoFunction(3); myAddFunction(3,5); Upgrade to the Latest Revision of MongoDB Revisions provide security patches, bug fixes, and new or changed features that do not contain any backward breaking changes. Always upgrade to the latest revision in your release series. The third number in the MongoDB version number (page 936) indicates the revision. Before Upgrading • Ensure you have an up-to-date backup of your data set. See MongoDB Backup Methods (page 188). • Consult the following documents for any special considerations or compatibility issues specific to your Mon- goDB release: – The release notes, located at Release Notes (page 785). – The documentation for your driver. See Drivers88 and Driver Compatibility89 pages for more information. • If your installation includes replica sets, plan the upgrade during a predefined maintenance window. • Before you upgrade a production environment, use the procedures in this document to upgrade a staging environ- ment that reproduces your production environment, to ensure that your production configuration is compatible with all changes. Upgrade Procedure Important: Always backup all of your data before upgrading MongoDB. Upgrade each mongod and mongos binary separately, using the procedure described here. When upgrading a binary, use the procedure Upgrade a MongoDB Instance (page 242). Follow this upgrade procedure: 88https://docs.mongodb.org/ecosystem/drivers 89https://docs.mongodb.org/ecosystem/drivers/driver-compatibility-reference 5.2. Administration Tutorials 241 MongoDB Documentation, Release 3.0.7 1. For deployments that use authentication, first upgrade all of your MongoDB drivers. To upgrade, see the documentation for your driver as well as the Driver Compatibility90 page. 2. Upgrade sharded clusters, as described in Upgrade Sharded Clusters (page 242). 3. Upgrade any standalone instances. See Upgrade a MongoDB Instance (page 242). 4. Upgrade any replica sets that are not part of a sharded cluster, as described in Upgrade Replica Sets (page 243). Upgrade a MongoDB Instance To upgrade a mongod or mongos instance, use one of the following approaches: • Upgrade the instance using the operating system’s package management tool and the official MongoDB pack- ages. This is the preferred approach. See Install MongoDB (page 5). • Upgrade the instance by replacing the existing binaries with new binaries. See Replace the Existing Binaries (page 242). Replace the Existing Binaries Important: Always backup all of your data before upgrading MongoDB. This section describes how to upgrade MongoDB by replacing the existing binaries. The preferred approach to an upgrade is to use the operating system’s package management tool and the official MongoDB packages, as described in Install MongoDB (page 5). To upgrade a mongod or mongos instance by replacing the existing binaries: 1. Download the binaries for the latest MongoDB revision from the MongoDB Download Page91 and store the binaries in a temporary location. The binaries download as compressed files that uncompress to the directory structure used by the MongoDB installation. 2. Shutdown the instance. 3. Replace the existing MongoDB binaries with the downloaded binaries. 4. Restart the instance. Upgrade Sharded Clusters To upgrade a sharded cluster: 1. Disable the cluster’s balancer, as described in Disable the Balancer (page 717). 2. Upgrade each mongos instance by following the instructions below in Upgrade a MongoDB Instance (page 242). You can upgrade the mongos instances in any order. 3. Upgrade each mongod config server (page 670) individually starting with the last config server listed in your mongos --configdb string and working backward. To keep the cluster online, make sure at least one config server is always running. For each config server upgrade, follow the instructions below in Upgrade a MongoDB Instance (page 242) Example 90https://docs.mongodb.org/ecosystem/drivers/driver-compatibility-reference 91http://downloads.mongodb.org/ 242 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 Given the following config string: mongos --configdb cfg0.example.net:27019,cfg1.example.net:27019,cfg2.example.net:27019 You would upgrade the config servers in the following order: (a) cfg2.example.net (b) cfg1.example.net (c) cfg0.example.net 4. Upgrade each shard. • If a shard is a replica set, upgrade the shard using the procedure below titled Upgrade Replica Sets (page 243). • If a shard is a standalone instance, upgrade the shard using the procedure below titled Upgrade a MongoDB Instance (page 242). 5. Re-enable the balancer, as described in Enable the Balancer (page 717). Upgrade Replica Sets To upgrade a replica set, upgrade each member individually, starting with the secondaries and finishing with the primary. Plan the upgrade during a predefined maintenance window. Upgrade Secondaries Upgrade each secondary separately as follows: 1. Upgrade the secondary’s mongod binary by following the instructions below in Upgrade a MongoDB Instance (page 242). 2. After upgrading a secondary, wait for the secondary to recover to the SECONDARY state before upgrading the next instance. To check the member’s state, issue rs.status() in the mongo shell. The secondary may briefly go into STARTUP2 or RECOVERING. This is normal. Make sure to wait for the secondary to fully recover to SECONDARY before you continue the upgrade. Upgrade the Primary 1. Step down the primary to initiate the normal failover (page 580) procedure. Using one of the following: • The rs.stepDown() helper in the mongo shell. • The replSetStepDown database command. During failover, the set cannot accept writes. Typically this takes 10-20 seconds. Plan the upgrade during a predefined maintenance window. Note: Stepping down the primary is preferable to directly shutting down the primary. Stepping down expedites the failover procedure. 2. Once the primary has stepped down, call the rs.status() method from the mongo shell until you see that another member has assumed the PRIMARY state. 3. Shut down the original primary and upgrade its instance by following the instructions below in Upgrade a MongoDB Instance (page 242). 5.2. Administration Tutorials 243 MongoDB Documentation, Release 3.0.7 Additional Resources • MongoDB Major Version Upgrade Consulting Package92 Monitor MongoDB With SNMP on Linux New in version 2.2. Enterprise Feature SNMP is only available in MongoDB Enterprise93. Overview MongoDB Enterprise can provide database metrics via SNMP, in support of centralized data collection and aggrega- tion. This procedure explains the setup and configuration of a mongod instance as an SNMP subagent, as well as initializing and testing of SNMP support with MongoDB Enterprise. See also: Troubleshoot SNMP (page 247) and Monitor MongoDB Windows with SNMP (page 245) for complete instructions on using MongoDB with SNMP on Windows systems. Considerations Only mongod instances provide SNMP support. mongos and the other MongoDB binaries do not support SNMP. Configuration Files Changed in version 2.6. MongoDB Enterprise contains the following configuration files to support SNMP: • MONGOD-MIB.txt: The management information base (MIB) file that defines MongoDB’s SNMP output. • mongod.conf.subagent: The configuration file to run mongod as the SNMP subagent. This file sets SNMP run-time configuration options, including the AgentX socket to connect to the SNMP master. • mongod.conf.master: The configuration file to run mongod as the SNMP master. This file sets SNMP run-time configuration options. Procedure Step 1: Copy configuration files. Use the following sequence of commands to move the SNMP configuration files to the SNMP service configuration directory. 92https://www.mongodb.com/products/consulting?jmp=docs#major_version_upgrade 93http://www.mongodb.com/products/mongodb-enterprise?jmp=docs 244 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 First, create the SNMP configuration directory if needed and then, from the installation directory, copy the configura- tion files to the SNMP service configuration directory: mkdir -p /etc/snmp/ cp MONGOD-MIB.txt /usr/share/snmp/mibs/MONGOD-MIB.txt cp mongod.conf.subagent /etc/snmp/mongod.conf The configuration filename is tool-dependent. For example, when using net-snmp the configuration file is snmpd.conf. By default SNMP uses UNIX domain for communication between the agent (i.e. snmpd or the master) and sub-agent (i.e. MongoDB). Ensure that the agentXAddress specified in the SNMP configuration file for MongoDB matches the agentXAddress in the SNMP master configuration file. Step 2: Start MongoDB. Start mongod with the snmp-subagent to send data to the SNMP master. mongod --snmp-subagent Step 3: Confirm SNMP data retrieval. Use snmpwalk to collect data from mongod: Connect an SNMP client to verify the ability to collect SNMP data from MongoDB. Install the net-snmp94 package to access the snmpwalk client. net-snmp provides the snmpwalk SNMP client. snmpwalk -m /usr/share/snmp/mibs/MONGOD-MIB.txt -v 2c -c mongodb 127.0.0.1: 1.3.6.1.4.1.34601 refers to the port defined by the SNMP master, not the primary port used by mongod for client communi- cation. Optional: Run MongoDB as SNMP Master You can run mongod with the snmp-master option for testing purposes. To do this, use the SNMP master configu- ration file instead of the subagent configuration file. From the directory containing the unpacked MongoDB installation files: cp mongod.conf.master /etc/snmp/mongod.conf Additionally, start mongod with the snmp-master option, as in the following: mongod --snmp-master Monitor MongoDB Windows with SNMP New in version 2.6. Enterprise Feature SNMP is only available in MongoDB Enterprise95. 94http://www.net-snmp.org/ 95http://www.mongodb.com/products/mongodb-enterprise?jmp=docs 5.2. Administration Tutorials 245 MongoDB Documentation, Release 3.0.7 Overview MongoDB Enterprise can provide database metrics via SNMP, in support of centralized data collection and aggrega- tion. This procedure explains the setup and configuration of a mongod.exe instance as an SNMP subagent, as well as initializing and testing of SNMP support with MongoDB Enterprise. See also: Monitor MongoDB With SNMP on Linux (page 244) and Troubleshoot SNMP (page 247) for more information. Considerations Only mongod.exe instances provide SNMP support. mongos.exe and the other MongoDB binaries do not support SNMP. Configuration Files Changed in version 2.6. MongoDB Enterprise contains the following configuration files to support SNMP: • MONGOD-MIB.txt: The management information base (MIB) file that defines MongoDB’s SNMP output. • mongod.conf.subagent: The configuration file to run mongod.exe as the SNMP subagent. This file sets SNMP run-time configuration options, including the AgentX socket to connect to the SNMP master. • mongod.conf.master: The configuration file to run mongod.exe as the SNMP master. This file sets SNMP run-time configuration options. Procedure Step 1: Copy configuration files. Use the following sequence of commands to move the SNMP configuration files to the SNMP service configuration directory. First, create the SNMP configuration directory if needed and then, from the installation directory, copy the configura- tion files to the SNMP service configuration directory: md C:\snmp\etc\config copy MONGOD-MIB.txt C:\snmp\etc\config\MONGOD-MIB.txt copy mongod.conf.subagent C:\snmp\etc\config\mongod.conf The configuration filename is tool-dependent. For example, when using net-snmp the configuration file is snmpd.conf. Edit the configuration file to ensure that the communication between the agent (i.e. snmpd or the master) and sub- agent (i.e. MongoDB) uses TCP. Ensure that the agentXAddress specified in the SNMP configuration file for MongoDB matches the agentXAddress in the SNMP master configuration file. 246 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 Step 2: Start MongoDB. Start mongod.exe with the snmp-subagent to send data to the SNMP master. mongod.exe --snmp-subagent Step 3: Confirm SNMP data retrieval. Use snmpwalk to collect data from mongod.exe: Connect an SNMP client to verify the ability to collect SNMP data from MongoDB. Install the net-snmp96 package to access the snmpwalk client. net-snmp provides the snmpwalk SNMP client. snmpwalk -m C:\snmp\etc\config\MONGOD-MIB.txt -v 2c -c mongodb 127.0.0.1: 1.3.6.1.4.1.34601 refers to the port defined by the SNMP master, not the primary port used by mongod.exe for client communication. Optional: Run MongoDB as SNMP Master You can run mongod.exe with the snmp-master option for testing purposes. To do this, use the SNMP master configuration file instead of the subagent configuration file. From the directory containing the unpacked MongoDB installation files: copy mongod.conf.master C:\snmp\etc\config\mongod.conf Additionally, start mongod.exe with the snmp-master option, as in the following: mongod.exe --snmp-master Troubleshoot SNMP New in version 2.6. Enterprise Feature SNMP is only available in MongoDB Enterprise. Overview MongoDB Enterprise can provide database metrics via SNMP, in support of centralized data collection and aggre- gation. This document identifies common problems you may encounter when deploying MongoDB Enterprise with SNMP as well as possible solutions for these issues. See Monitor MongoDB With SNMP on Linux (page 244) and Monitor MongoDB Windows with SNMP (page 245) for complete installation instructions. Issues Failed to Connect The following in the mongod logfile: Warning: Failed to connect to the agentx master agent 96http://www.net-snmp.org/ 5.2. Administration Tutorials 247 MongoDB Documentation, Release 3.0.7 AgentX is the SNMP agent extensibility protocol defined in Internet RFC 274197. It explains how to define additional data to monitor over SNMP. When MongoDB fails to connect to the agentx master agent, use the following procedure to ensure that the SNMP subagent can connect properly to the SNMP master. 1. Make sure the master agent is running. 2. Compare the SNMP master’s configuration file with the subagent configuration file. Ensure that the agentx socket definition is the same between the two. 3. Check the SNMP configuration files to see if they specify using UNIX Domain Sockets. If so, confirm that the mongod has appropriate permissions to open a UNIX domain socket. Error Parsing Command Line One of the following errors at the command line: Error parsing command line: unknown option snmp-master try 'mongod --help' for more information Error parsing command line: unknown option snmp-subagent try 'mongod --help' for more information mongod binaries that are not part of the Enterprise Edition produce this error. Install the Enterprise Edition (page 33) and attempt to start mongod again. Other MongoDB binaries, including mongos will produce this error if you attempt to star them with snmp-master or snmp-subagent. Only mongod supports SNMP. Error Starting SNMPAgent The following line in the log file indicates that mongod cannot read the mongod.conf file: [SNMPAgent] warning: error starting SNMPAgent as master err:1 If running on Linux, ensure mongod.conf exists in the /etc/snmp directory, and ensure that the mongod UNIX user has permission to read the mongod.conf file. If running on Windows, ensure mongod.conf exists in C:\snmp\etc\config. 5.2.2 Backup and Recovery The following tutorials describe backup and restoration for a mongod instance: Backup and Restore with Filesystem Snapshots (page 249) An outline of procedures for creating MongoDB data set backups using system-level file snapshot tool, such as LVM or native storage appliance tools. Restore a Replica Set from MongoDB Backups (page 252) Describes procedure for restoring a replica set from an archived backup such as a mongodump or MongoDB Cloud Manager98 Backup file. Back Up and Restore with MongoDB Tools (page 254) Describes a procedure for exporting the contents of a database to either a binary dump or a textual exchange format, and for importing these files into a database. Backup and Restore Sharded Clusters (page 259) Detailed procedures and considerations for backing up sharded clusters and single shards. Recover Data after an Unexpected Shutdown (page 268) Recover data from MongoDB data files that were not prop- erly closed or have an invalid state. 97http://www.ietf.org/rfc/rfc2741.txt 98https://cloud.mongodb.com/?jmp=docs 248 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 Backup and Restore with Filesystem Snapshots This document describes a procedure for creating backups of MongoDB systems using system-level tools, such as LVM or storage appliance, as well as the corresponding restoration strategies. These filesystem snapshots, or “block-level” backup methods use system level tools to create copies of the device that holds MongoDB’s data files. These methods complete quickly and work reliably, but require more system configura- tion outside of MongoDB. See also: MongoDB Backup Methods (page 188) and Back Up and Restore with MongoDB Tools (page 254). Snapshots Overview Snapshots work by creating pointers between the live data and a special snapshot volume. These pointers are the- oretically equivalent to “hard links.” As the working data diverges from the snapshot, the snapshot process uses a copy-on-write strategy. As a result the snapshot only stores modified data. After making the snapshot, you mount the snapshot image on your file system and copy data from the snapshot. The resulting backup contains a full copy of all data. Snapshots have the following limitations: • The database must be valid when the snapshot takes place. This means that all writes accepted by the database need to be fully written to disk: either to the journal or to data files. If all writes are not on disk when the backup occurs, the backup will not reflect these changes. If writes are in progress when the backup occurs, the data files will reflect an inconsistent state. With journaling all data-file states resulting from in-progress writes are recoverable; without journaling you must flush all pending writes to disk before running the backup operation and must ensure that no writes occur during the entire backup procedure. If you do use journaling, the journal must reside on the same volume as the data. • Snapshots create an image of an entire disk image. Unless you need to back up your entire system, consider isolating your MongoDB data files, journal (if applicable), and configuration on one logical disk that doesn’t contain any other data. Alternately, store all MongoDB data files on a dedicated device so that you can make backups without duplicat- ing extraneous data. • Ensure that you copy data from snapshots and onto other systems to ensure that data is safe from site failures. • Although different snapshots methods provide different capability, the LVM method outlined below does not provide any capacity for capturing incremental backups. Snapshots With Journaling If your mongod instance has journaling enabled, then you can use any kind of file system or volume/block level snapshot tool to create backups. If you manage your own infrastructure on a Linux-based system, configure your system with LVM to provide your disk packages and provide snapshot capability. You can also use LVM-based setups within a cloud/virtualized environment. Note: Running LVM provides additional flexibility and enables the possibility of using snapshots to back up Mon- goDB. 5.2. Administration Tutorials 249 MongoDB Documentation, Release 3.0.7 Snapshots with Amazon EBS in a RAID 10 Configuration If your deployment depends on Amazon’s Elastic Block Storage (EBS) with RAID configured within your instance, it is impossible to get a consistent state across all disks using the platform’s snapshot tool. As an alternative, you can do one of the following: • Flush all writes to disk and create a write lock to ensure consistent state during the backup process. If you choose this option see Create Backups on Instances that do not have Journaling Enabled (page 252). • Configure LVM to run and hold your MongoDB data files on top of the RAID within your system. If you choose this option, perform the LVM backup operation described in Create a Snapshot (page 250). Backup and Restore Using LVM on a Linux System This section provides an overview of a simple backup process using LVM on a Linux system. While the tools, com- mands, and paths may be (slightly) different on your system the following steps provide a high level overview of the backup operation. Note: Only use the following procedure as a guideline for a backup system and infrastructure. Production backup systems must consider a number of application specific requirements and factors unique to specific environments. Create a Snapshot To create a snapshot with LVM, issue a command as root in the following format: lvcreate --size 100M --snapshot --name mdb-snap01 /dev/vg0/mongodb This command creates an LVM snapshot (with the --snapshot option) named mdb-snap01 of the mongodb volume in the vg0 volume group. This example creates a snapshot named mdb-snap01 located at /dev/vg0/mdb-snap01. The location and paths to your systems volume groups and devices may vary slightly depending on your operating system’s LVM configuration. The snapshot has a cap of at 100 megabytes, because of the parameter --size 100M. This size does not re- flect the total amount of the data on the disk, but rather the quantity of differences between the current state of /dev/vg0/mongodb and the creation of the snapshot (i.e. /dev/vg0/mdb-snap01.) Warning: Ensure that you create snapshots with enough space to account for data growth, particularly for the period of time that it takes to copy data out of the system or to a temporary image. If your snapshot runs out of space, the snapshot image becomes unusable. Discard this logical volume and create another. The snapshot will exist when the command returns. You can restore directly from the snapshot at any time or by creating a new logical volume and restoring from this snapshot to the alternate image. While snapshots are great for creating high quality backups very quickly, they are not ideal as a format for storing backup data. Snapshots typically depend and reside on the same storage infrastructure as the original disk images. Therefore, it’s crucial that you archive these snapshots and store them elsewhere. Archive a Snapshot After creating a snapshot, mount the snapshot and copy the data to separate storage. Your system might try to compress the backup images as you move them offline. Alternatively, take a block level copy of the snapshot image, such as with the following procedure: umount /dev/vg0/mdb-snap01 dd if=/dev/vg0/mdb-snap01 | gzip > mdb-snap01.gz The above command sequence does the following: 250 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 • Ensures that the /dev/vg0/mdb-snap01 device is not mounted. Never take a block level copy of a filesys- tem or filesystem snapshot that is mounted. • Performs a block level copy of the entire snapshot image using the dd command and compresses the result in a gzipped file in the current working directory. Warning: This command will create a large gz file in your current working directory. Make sure that you run this command in a file system that has enough free space. Restore a Snapshot To restore a snapshot created with the above method, issue the following sequence of com- mands: lvcreate --size 1G --name mdb-new vg0 gzip -d -c mdb-snap01.gz | dd of=/dev/vg0/mdb-new mount /dev/vg0/mdb-new /srv/mongodb The above sequence does the following: • Creates a new logical volume named mdb-new, in the /dev/vg0 volume group. The path to the new device will be /dev/vg0/mdb-new. Warning: This volume will have a maximum size of 1 gigabyte. The original file system must have had a total size of 1 gigabyte or smaller, or else the restoration will fail. Change 1G to your desired volume size. • Uncompresses and unarchives the mdb-snap01.gz into the mdb-new disk image. • Mounts the mdb-new disk image to the /srv/mongodb directory. Modify the mount point to correspond to your MongoDB data file location, or other location as needed. Note: The restored snapshot will have a stale mongod.lock file. If you do not remove this file from the snap- shot, and MongoDB may assume that the stale lock file indicates an unclean shutdown. If you’re running with storage.journal.enabled enabled, and you do not use db.fsyncLock(), you do not need to remove the mongod.lock file. If you use db.fsyncLock() you will need to remove the lock. Restore Directly from a Snapshot To restore a backup without writing to a compressed gz file, use the following sequence of commands: umount /dev/vg0/mdb-snap01 lvcreate --size 1G --name mdb-new vg0 dd if=/dev/vg0/mdb-snap01 of=/dev/vg0/mdb-new mount /dev/vg0/mdb-new /srv/mongodb Remote Backup Storage You can implement off-system backups using the combined process (page 251) and SSH. This sequence is identical to procedures explained above, except that it archives and compresses the backup on a remote system using SSH. Consider the following procedure: umount /dev/vg0/mdb-snap01 dd if=/dev/vg0/mdb-snap01 | ssh username@example.com gzip > /opt/backup/mdb-snap01.gz lvcreate --size 1G --name mdb-new vg0 ssh username@example.com gzip -d -c /opt/backup/mdb-snap01.gz | dd of=/dev/vg0/mdb-new mount /dev/vg0/mdb-new /srv/mongodb 5.2. Administration Tutorials 251 MongoDB Documentation, Release 3.0.7 Create Backups on Instances that do not have Journaling Enabled If your mongod instance does not run with journaling enabled, or if your journal is on a separate volume, obtaining a functional backup of a consistent state is more complicated. As described in this section, you must flush all writes to disk and lock the database to prevent writes during the backup process. If you have a replica set configuration, then for your backup use a secondary which is not receiving reads (i.e. hidden member). Important: This procedure is only supported with the MMAPv1 storage engine. In the following procedure, you must issue the db.fsyncLock() and db.fsyncUnlock() operations on the same connection. The client that issues db.fsyncLock() is solely responsible for issuing a db.fsyncUnlock() operation and must be able to handle potential error conditions so that it can perform the db.fsyncUnlock() before terminating the connection. Step 1: Flush writes to disk and lock the database to prevent further writes. To flush writes to disk and to “lock” the database, issue the db.fsyncLock() method in the mongo shell: db.fsyncLock(); Step 2: Perform the backup operation described in Create a Snapshot. Step 3: After the snapshot completes, unlock the database. To unlock the database after the snapshot has com- pleted, use the following command in the mongo shell: db.fsyncUnlock(); Changed in version 2.2: When used in combination with fsync or db.fsyncLock(), mongod will block reads, including those from mongodump, when queued write operation waits behind the fsync lock. Do not use mongodump with db.fsyncLock(). Additional Resources See also MongoDB Cloud Manager99 for seamless automation, backup, and monitoring. Restore a Replica Set from MongoDB Backups This procedure outlines the process for taking MongoDB data and restoring that data into a new replica set. Use this approach for seeding test deployments from production backups as well as part of disaster recovery. You cannot restore a single data set to three new mongod instances and then create a replica set. In this situation MongoDB will force the secondaries to perform an initial sync. The procedures in this document describe the correct and efficient ways to deploy a replica set. Restore Database into a Single Node Replica Set Step 1: Obtain backup MongoDB Database files. The backup files may come from a file system snapshot (page 249). The MongoDB Cloud Manager100 produces MongoDB database files for stored snapshots101 and point in 99https://cloud.mongodb.com/?jmp=docs 100https://cloud.mongodb.com/?jmp=docs 101https://docs.cloud.mongodb.com/tutorial/restore-from-snapshot/ 252 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 time snapshots102. For Ops Manager, an on-premise solution available in MongoDB Enterprise Advanced103, see also the Ops Manager Backup overview104. You can also use mongorestore to restore database files using data created with mongodump. See Back Up and Restore with MongoDB Tools (page 254) for more information. Step 2: Start a mongod using data files from the backup as the data path. Start a mongod instance for a new single-node replica set. Specify the path to the backup data files with --dbpath option and the replica set name with the --replSet option. mongod --dbpath /data/db --replSet Step 3: Connect a mongo shell to the mongod instance. For example, to connect to a mongod running on localhost on the default port of 27017, simply issue: mongo Step 4: Initiate the new replica set. Use rs.initiate() on the replica set member: rs.initiate() MongoDB initiates a set that consists of the current member and that uses the default replica set configuration. Add Members to the Replica Set MongoDB provides two options for restoring secondary members of a replica set: • Manually copy the database files to each data directory. • Allow initial sync (page 594) to distribute data automatically. The following sections outlines both approaches. Note: If your database is large, initial sync can take a long time to complete. For large databases, it might be preferable to copy the database files onto each host. Copy Database Files and Restart mongod Instance Use the following sequence of operations to “seed” additional members of the replica set with the restored data by copying MongoDB data files directly. Step 1: Shut down the mongod instance that you restored. Use --shutdown or db.shutdownServer() to ensure a clean shut down. Step 2: Copy the primary’s data directory to each secondary. Copy the primary’s data directory into the dbPath of the other members of the replica set. The dbPath is /data/db by default. Step 3: Start the mongod instance that you restored. 102https://docs.cloud.mongodb.com/tutorial/restore-from-point-in-time-snapshot/ 103https://www.mongodb.com/products/mongodb-enterprise-advanced?jmp=docs 104https://docs.opsmanager.mongodb.com/current/core/backup-overview 5.2. Administration Tutorials 253 MongoDB Documentation, Release 3.0.7 Step 4: Add the secondaries to the replica set. In a mongo shell connected to the primary, add the secondaries to the replica set using rs.add(). See Deploy a Replica Set (page 603) for more information about deploying a replica set. Update Secondaries using Initial Sync Use the following sequence of operations to “seed” additional members of the replica set with the restored data using the default initial sync operation. Step 1: Ensure that the data directories on the prospective replica set members are empty. Step 2: Add each prospective member to the replica set. When you add a member to the replica set, Initial Sync (page 594) copies the data from the primary to the new member. Back Up and Restore with MongoDB Tools This document describes the process for creating backups and restoring data using the utilities provided with Mon- goDB. Because all of these tools primarily operate by interacting with a running mongod instance, they can impact the performance of your running database. Not only do they create traffic for a running database instance, they also force the database to read all data through memory. When MongoDB reads infrequently used data, it can supplant more frequently accessed data, causing a deterioration in performance for the database’s regular workload. No matter how you decide to import or export your data, consider the following guidelines: • Label files so that you can identify the contents of the export or backup as well as the point in time the ex- port/backup reflect. • Do not create or apply exports if the backup process itself will have an adverse effect on a production system. • Make sure that the backups reflect a consistent data state. Export or backup processes can impact data integrity (i.e. type fidelity) and consistency if updates continue during the backup process. • Test backups and exports by restoring and importing to ensure that the backups are useful. See also: MongoDB Backup Methods (page 188) or MongoDB Cloud Manager Backup documentation105 for more information on backing up MongoDB instances. Additionally, consider the following references for the MongoDB import/export tools: • mongoimport • mongoexport • mongorestore • mongodump Binary BSON Dumps The mongorestore and mongodump utilities work with BSON (page 182) data dumps, and are useful for creating backups of small deployments. For resilient and non-disruptive backups, use a file system or block-level disk snapshot function, such as the methods described in the MongoDB Backup Methods (page 188) document. 105https://docs.cloud.mongodb.com/tutorial/nav/backup-use/ 254 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 Use these tools for backups if other backup methods, such as the MongoDB Cloud Manager106 or file system snapshots (page 249) are unavailable. Backup a Database with mongodump mongodump does not dump the content of the local database. To back up all the databases in a cluster via mongodump, you should have the backup (page 411) role. The backup (page 411) role provides the required privileges for backing up all databases. The role confers no additional access, in keeping with the policy of least privilege. To back up a given database, you must have read access on the database. Several roles provide this access, including the backup (page 411) role. To back up the system.profile (page 297) collection, which is created when you activate database profiling (page 219), you must have additional read access on this collection. Several roles provide this access, including the clusterAdmin (page 408) and dbAdmin (page 407) roles. Changed in version 2.6. To back up users and user-defined roles (page 335) for a given database, you must have access to the admin database. MongoDB stores the user data and role definitions for all databases in the admin database. Specifically, to back up a given database’s users, you must have the find (page 420) action (page 419) on the admin database’s admin.system.users (page 297) collection. The backup (page 411) and userAdminAnyDatabase (page 412) roles both provide this privilege. To back up the user-defined roles on a database, you must have the find (page 420) action on the admin database’s admin.system.roles (page 297) collection. Both the backup (page 411) and userAdminAnyDatabase (page 412) roles provide this privilege. Basic mongodump Operations The mongodump utility backs up data by connecting to a running mongod or mongos instance. The utility can create a backup for an entire server, database or collection, or can use a query to backup just part of a collection. When you run mongodump without any arguments, the command connects to the MongoDB instance on the local system (e.g. 127.0.0.1 or localhost) on port 27017 and creates a database backup named dump/ in the current directory. To backup data from a mongod or mongos instance running on the same machine and on the default port of 27017, use the following command: mongodump The data format used by mongodump from version 2.2 or later is incompatible with earlier versions of mongod. Do not use recent versions of mongodump to back up older data stores. You can also specify the --host and --port of the MongoDB instance that the mongodump should connect to. For example: mongodump --host mongodb.example.net --port 27017 mongodump will write BSON files that hold a copy of data accessible via the mongod listening on port 27017 of the mongodb.example.net host. See Create Backups from Non-Local mongod Instances (page 256) for more information. To specify a different output directory, you can use the --out or -o option: 106https://cloud.mongodb.com/?jmp=docs 5.2. Administration Tutorials 255 MongoDB Documentation, Release 3.0.7 mongodump --out /data/backup/ To limit the amount of data included in the database dump, you can specify --db and --collection as options to mongodump. For example: mongodump --collection myCollection --db test This operation creates a dump of the collection named myCollection from the database test in a dump/ subdi- rectory of the current working directory. mongodump overwrites output files if they exist in the backup data folder. Before running the mongodump command multiple times, either ensure that you no longer need the files in the output folder (the default is the dump/ folder) or rename the folders or files. Point in Time Operation Using Oplogs Use the --oplog option with mongodump to collect the oplog entries to build a point-in-time snapshot of a database within a replica set. With --oplog, mongodump copies all the data from the source database as well as all of the oplog entries from the beginning to the end of the backup procedure. This operation, in conjunction with mongorestore --oplogReplay, allows you to restore a backup that reflects the specific moment in time that corresponds to when mongodump completed creating the dump file. Create Backups from Non-Local mongod Instances The --host and --port options for mongodump allow you to connect to and backup from a remote host. Consider the following example: mongodump --host mongodb1.example.net --port 3017 --username user --password pass --out /opt/backup/mongodump-2013-10-24 On any mongodump command you may, as above, specify username and password credentials to specify database authentication. Restore a Database with mongorestore On systems running with authorization, a user must have access that includes the readWrite (page 406) role for each database being restored. The readWriteAnyDatabase (page 412) role and the restore (page 411) role each provide access to restore any database. If running mongorestore with --oplogReplay, however, neither role is sufficient. Instead, create a user-defined role (page 391) that has anyAction (page 424) on anyResource (page 419) and grant only to users who must run mongorestore with --oplogReplay. Changed in version 2.6. To restore users and user-defined roles (page 335) on a given database, you must have access to the admin database. MongoDB stores the user data and role definitions for all databases in the admin database. Specifically, to restore users to a given database, you must have the insert (page 420) action (page 419) on the admin database’s admin.system.users (page 297) collection. The restore (page 411) role provides this privilege. To restore user-defined roles to a database, you must have the insert (page 420) action on the admin database’s admin.system.roles (page 297) collection. The restore (page 411) role provides this privilege. If your database is running with authentication enabled, you must possess the userAdmin (page 408) role on the database you are restoring, or the userAdminAnyDatabase (page 412) role, which allows you to restore user data to any database. The restore (page 411) role also provides the requisite privileges. Basic mongorestore Operations The mongorestore utility restores a binary backup created by mongodump. By default, mongorestore looks for a database backup in the dump/ directory. The mongorestore utility restores data by connecting to a running mongod or mongos directly. 256 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 mongorestore can restore either an entire database backup or a subset of the backup. To use mongorestore to connect to an active mongod or mongos, use a command with the following prototype form: mongorestore --port Consider the following example: mongorestore dump-2013-10-25/ Here, mongorestore imports the database backup in the dump-2013-10-25 directory to the mongod instance running on the localhost interface. Restore Point in Time Oplog Backup If you created your database dump using the --oplog option to ensure a point-in-time snapshot, call mongorestore with the --oplogReplay option, as in the following example: mongorestore --oplogReplay You may also consider using the mongorestore --objcheck option to check the integrity of objects while inserting them into the database, or you may consider the mongorestore --drop option to drop each collection from the database before restoring from backups. Restore Backups to Non-Local mongod Instances By default, mongorestore connects to a MongoDB instance running on the localhost interface (e.g. 127.0.0.1) and on the default port (27017). If you want to restore to a different host or port, use the --host and --port options. Consider the following example: mongorestore --host mongodb1.example.net --port 3017 --username user --password pass /opt/backup/mongodump-2013-10-24 As above, you may specify username and password connections if your mongod requires authentication. Human Intelligible Import/Export Formats MongoDB’s mongoimport and mongoexport tools allow you to work with your data in a human-readable Extended JSON or CSV format. This is useful for simple ingestion to or from a third-party system, and when you want to backup or export a small subset of your data. For more complex data migration tasks, you may want to write your own import and export scripts using a client driver to interact with the database. The examples in this section use the MongoDB tools mongoimport and mongoexport. These tools may also be useful for importing data into a MongoDB database from third party applications. If you want to simply copy a database or collection from one instance to another, consider using the copydb, clone, or cloneCollection commands, which may be more suited to this task. The mongo shell provides the db.copyDatabase() method. Warning: Warning: Avoid using mongoimport and mongoexport for full instance production backups. They do not reliably preserve all rich BSON data types, because JSON can only represent a subset of the types supported by BSON. Use mongodump and mongorestore as described in MongoDB Backup Methods (page 188) for this kind of functionality. Collection Export with mongoexport 5.2. Administration Tutorials 257 MongoDB Documentation, Release 3.0.7 Export in CSV Format Changed in version 3.0.0: mongoexport removed the --csv option. Use the --type=csv option to specify CSV format for the output. In the following example, mongoexport exports data from the collection contacts collection in the users database in CSV format to the file /opt/backups/contacts.csv. The mongod instance that mongoexport connects to is running on the localhost port number 27017. When you export in CSV format, you must specify the fields in the documents to export. The operation specifies the name and address fields to export. mongoexport --db users --collection contacts --type=csv --fields name,address --out /opt/backups/contacts.csv For CSV exports only, you can also specify the fields in a file containing the line-separated list of fields to export. The file must have only one field per line. For example, you can specify the name and address fields in a file fields.txt: name address Then, using the --fieldFile option, specify the fields to export with the file: mongoexport --db users --collection contacts --type=csv --fieldFile fields.txt --out /opt/backups/contacts.csv Changed in version 3.0.0: mongoexport removed the --csv option and replaced with the --type option. Export in JSON Format This example creates an export of the contacts collection from the MongoDB instance running on the localhost port number 27017. This writes the export to the contacts.json file in JSON format. mongoexport --db sales --collection contacts --out contacts.json Export from Remote Host Running with Authentication The following example exports the contacts collec- tion from the marketing database, which requires authentication. This data resides on the MongoDB instance located on the host mongodb1.example.net running on port 37017, which requires the username user and the password pass. mongoexport --host mongodb1.example.net --port 37017 --username user --password pass --collection contacts --db marketing --out mdb1-examplenet.json Export Query Results You can export only the results of a query by supplying a query filter with the --query option, and limit the results to a single database using the “--db” option. For instance, this command returns all documents in the sales database’s contacts collection that contain a field named field with a value of 1. mongoexport --db sales --collection contacts --query '{"field": 1}' You must enclose the query in single quotes (e.g. ’) to ensure that it does not interact with your shell environment. Collection Import with mongoimport Simple Usage mongoimport restores a database from a backup taken with mongoexport. Most of the argu- ments to mongoexport also exist for mongoimport. In the following example, mongoimport imports the data in the JSON data from the contacts.json file into the collection contacts in the users database. 258 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 mongoimport --db users --collection contacts --file contacts.json Import JSON to Remote Host Running with Authentication In the following example, mongoimport imports data from the file /opt/backups/mdb1-examplenet.json into the contacts collection within the database marketing on a remote MongoDB database with authentication enabled. mongoimport connects to the mongod instance running on the host mongodb1.example.net over port 37017. It authenticates with the username user and the password pass. mongoimport --host mongodb1.example.net --port 37017 --username user --password pass --collection contacts --db marketing --file /opt/backups/mdb1-examplenet.json CSV Import In the following example, mongoimport imports the csv formatted data in the /opt/backups/contacts.csv file into the collection contacts in the users database on the Mon- goDB instance running on the localhost port numbered 27017. Specifying --headerline instructs mongoimport to determine the name of the fields using the first line in the CSV file. mongoimport --db users --collection contacts --type csv --headerline --file /opt/backups/contacts.csv mongoimport uses the input file name, without the extension, as the collection name if -c or --collection is unspecified. The following example is therefore equivalent: mongoimport --db users --type csv --headerline --file /opt/backups/contacts.csv Use the “--ignoreBlanks” option to ignore blank fields. For CSV and TSV imports, this option provides the desired functionality in most cases because it avoids inserting fields with null values into your collection. Additional Resources • Backup and its Role in Disaster Recovery White Paper107 • Cloud Backup through MongoDB Cloud Manager108 • Blog Post: Backup vs. Replication, Why you Need Both109 • Backup Service with Ops Manager, an on-premise solution available in MongoDB Enterprise Advanced110 Backup and Restore Sharded Clusters The following tutorials describe backup and restoration for sharded clusters: Backup a Small Sharded Cluster with mongodump (page 260) If your sharded cluster holds a small data set, you can use mongodump to capture the entire backup in a reasonable amount of time. Backup a Sharded Cluster with Filesystem Snapshots (page 261) Use file system snapshots back up each compo- nent in the sharded cluster individually. The procedure involves stopping the cluster balancer. If your system configuration allows file system backups, this might be more efficient than using MongoDB tools. Backup a Sharded Cluster with Database Dumps (page 263) Create backups using mongodump to back up each component in the cluster individually. 107https://www.mongodb.com/lp/white-paper/backup-disaster-recovery?jmp=docs 108https://cloud.mongodb.com/?jmp=docs 109http://www.mongodb.com/blog/post/backup-vs-replication-why-do-you-need-both?jmp=docs 110https://www.mongodb.com/products/mongodb-enterprise-advanced?jmp=docs 5.2. Administration Tutorials 259 MongoDB Documentation, Release 3.0.7 Schedule Backup Window for Sharded Clusters (page 265) Limit the operation of the cluster balancer to provide a window for regular backup operations. Restore a Single Shard (page 265) An outline of the procedure and consideration for restoring a single shard from a backup. Restore a Sharded Cluster (page 266) An outline of the procedure and consideration for restoring an entire sharded cluster from backup. Backup a Small Sharded Cluster with mongodump Overview If your sharded cluster holds a small data set, you can connect to a mongos using mongodump. You can create backups of your MongoDB cluster, if your backup infrastructure can capture the entire backup in a reasonable amount of time and if you have a storage system that can hold the complete MongoDB data set. See MongoDB Backup Methods (page 188) and Backup and Restore Sharded Clusters (page 259) for complete infor- mation on backups in MongoDB and backups of sharded clusters in particular. Important: By default mongodump issue its queries to the non-primary nodes. To back up all the databases in a cluster via mongodump, you should have the backup (page 411) role. The backup (page 411) role provides the required privileges for backing up all databases. The role confers no additional access, in keeping with the policy of least privilege. To back up a given database, you must have read access on the database. Several roles provide this access, including the backup (page 411) role. To back up the system.profile (page 297) collection, which is created when you activate database profiling (page 219), you must have additional read access on this collection. Several roles provide this access, including the clusterAdmin (page 408) and dbAdmin (page 407) roles. Changed in version 2.6. To back up users and user-defined roles (page 335) for a given database, you must have access to the admin database. MongoDB stores the user data and role definitions for all databases in the admin database. Specifically, to back up a given database’s users, you must have the find (page 420) action (page 419) on the admin database’s admin.system.users (page 297) collection. The backup (page 411) and userAdminAnyDatabase (page 412) roles both provide this privilege. To back up the user-defined roles on a database, you must have the find (page 420) action on the admin database’s admin.system.roles (page 297) collection. Both the backup (page 411) and userAdminAnyDatabase (page 412) roles provide this privilege. Considerations If you use mongodump without specifying a database or collection, mongodump will capture collection data and the cluster meta-data from the config servers (page 670). You cannot use the --oplog option for mongodump when capturing data from mongos. As a result, if you need to capture a backup that reflects a single moment in time, you must stop all writes to the cluster for the duration of the backup operation. Procedure Capture Data You can perform a backup of a sharded cluster by connecting mongodump to a mongos. Use the following operation at your system’s prompt: 260 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 mongodump --host mongos3.example.net --port 27017 mongodump will write BSON files that hold a copy of data stored in the sharded cluster accessible via the mongos listening on port 27017 of the mongos3.example.net host. Restore Data Backups created with mongodump do not reflect the chunks or the distribution of data in the sharded collection or collections. Like all mongodump output, these backups contain separate directories for each database and BSON files for each collection in that database. You can restore mongodump output to any MongoDB instance, including a standalone, a replica set, or a new sharded cluster. When restoring data to sharded cluster, you must deploy and configure sharding before restoring data from the backup. See Deploy a Sharded Cluster (page 691) for more information. Additional Resources See also MongoDB Cloud Manager111 for seamless automation, backup, and monitoring. Backup a Sharded Cluster with Filesystem Snapshots Overview This document describes a procedure for taking a backup of all components of a sharded cluster. This pro- cedure uses file system snapshots to capture a copy of the mongod instance. An alternate procedure uses mongodump to create binary database dumps when file-system snapshots are not available. See Backup a Sharded Cluster with Database Dumps (page 263) for the alternate procedure. See MongoDB Backup Methods (page 188) and Backup and Restore Sharded Clusters (page 259) for complete infor- mation on backups in MongoDB and backups of sharded clusters in particular. Important: To capture a point-in-time backup from a sharded cluster you must stop all writes to the cluster. On a running production system, you can only capture an approximation of point-in-time snapshot. Considerations Balancing It is essential that you stop the balancer before capturing a backup. If the balancer is active while you capture backups, the backup artifacts may be incomplete and/or have duplicate data, as chunks may migrate while recording backups. Precision In this procedure, you will stop the cluster balancer and take a backup up of the config database, and then take backups of each shard in the cluster using a file-system snapshot tool. If you need an exact moment-in-time snapshot of the system, you will need to stop all application writes before taking the filesystem snapshots; otherwise the snapshot will only approximate a moment in time. For approximate point-in-time snapshots, you can improve the quality of the backup while minimizing impact on the cluster by taking the backup from a secondary member of the replica set that provides each shard. Consistency If the journal and data files are on the same logical volume, you can use a single point-in-time snapshot to capture a valid copy of the data. If the journal and data files are on different file systems, you must use db.fsyncLock() and db.fsyncUnLock() to capture a valid copy of your data. 111https://cloud.mongodb.com/?jmp=docs 5.2. Administration Tutorials 261 MongoDB Documentation, Release 3.0.7 Procedure Step 1: Disable the balancer. Disable the balancer process that equalizes the distribution of data among the shards. To disable the balancer, use the sh.stopBalancer() method in the mongo shell. Consider the following example: use config sh.stopBalancer() For more information, see the Disable the Balancer (page 717) procedure. Step 2: If necessary, lock one secondary member of each replica set in each shard. If your mongod does not have journaling enabled or your journal and data files are on different volumes, you must lock your mongod before capturing a back up. If your mongod has journaling enabled and your journal and data files are on the same volume, you may skip this step. If you need to lock the mongod, attempt to lock one secondary member of each replica set in each shard so that your backups reflect the state of your database at the nearest possible approximation of a single moment in time. To lock a secondary, connect through the mongo shell to the secondary member’s mongod instance and issue the db.fsyncLock() method. Step 3: Back up one of the config servers. Backing up a config server (page 670) backs up the sharded cluster’s metadata. You need back up only one config server, as they all hold the same data. Do one of the following to back up one of the config servers: Create a file-system snapshot of the config server. Do this only if the config server has journaling enabled. Use the procedure in Backup and Restore with Filesystem Snapshots (page 249). Never use db.fsyncLock() on config databases. Create a database dump to backup the config server. Issue mongodump against one of the config mongod instances. If you are running MongoDB 2.4 or later with the --configsvr option, then include the --oplog option to ensure that the dump includes a partial oplog containing operations from the duration of the mongodump operation. For example: mongodump --oplog Step 4: Back up the replica set members of the shards that you locked. You may back up the shards in parallel. For each shard, create a snapshot. Use the procedure in Backup and Restore with Filesystem Snapshots (page 249). Step 5: Unlock locked replica set members. If you locked any mongod instances to capture the backup, unlock them now. Unlock all locked replica set members of each shard using the db.fsyncUnlock() method in the mongo shell. Step 6: Enable the balancer. Re-enable the balancer with the sh.setBalancerState() method. Use the following command sequence when connected to the mongos with the mongo shell: 262 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 use config sh.setBalancerState(true) Additional Resources See also MongoDB Cloud Manager112 for seamless automation, backup, and monitoring. Backup a Sharded Cluster with Database Dumps Overview This document describes a procedure for taking a backup of all components of a sharded cluster. This procedure uses mongodump to create dumps of the mongod instance. An alternate procedure uses file system snap- shots to capture the backup data, and may be more efficient in some situations if your system configuration allows file system backups. See Backup and Restore Sharded Clusters (page 259) for more information. See MongoDB Backup Methods (page 188) and Backup and Restore Sharded Clusters (page 259) for complete infor- mation on backups in MongoDB and backups of sharded clusters in particular. Prerequisites Important: To capture a point-in-time backup from a sharded cluster you must stop all writes to the cluster. On a running production system, you can only capture an approximation of point-in-time snapshot. To back up all the databases in a cluster via mongodump, you should have the backup (page 411) role. The backup (page 411) role provides the required privileges for backing up all databases. The role confers no additional access, in keeping with the policy of least privilege. To back up a given database, you must have read access on the database. Several roles provide this access, including the backup (page 411) role. To back up the system.profile (page 297) collection, which is created when you activate database profiling (page 219), you must have additional read access on this collection. Several roles provide this access, including the clusterAdmin (page 408) and dbAdmin (page 407) roles. Changed in version 2.6. To back up users and user-defined roles (page 335) for a given database, you must have access to the admin database. MongoDB stores the user data and role definitions for all databases in the admin database. Specifically, to back up a given database’s users, you must have the find (page 420) action (page 419) on the admin database’s admin.system.users (page 297) collection. The backup (page 411) and userAdminAnyDatabase (page 412) roles both provide this privilege. To back up the user-defined roles on a database, you must have the find (page 420) action on the admin database’s admin.system.roles (page 297) collection. Both the backup (page 411) and userAdminAnyDatabase (page 412) roles provide this privilege. Consideration To create these backups of a sharded cluster, you will stop the cluster balancer and take a backup of the config database, and then take backups of each shard in the cluster using mongodump to capture the backup data. To capture a more exact moment-in-time snapshot of the system, you will need to stop all application writes before taking the filesystem snapshots; otherwise the snapshot will only approximate a moment in time. For approximate point-in-time snapshots, taking the backup from a single offline secondary member of the replica set that provides each shard can improve the quality of the backup while minimizing impact on the cluster. Procedure 112https://cloud.mongodb.com/?jmp=docs 5.2. Administration Tutorials 263 MongoDB Documentation, Release 3.0.7 Step 1: Disable the balancer process. Disable the balancer process that equalizes the distribution of data among the shards. To disable the balancer, use the sh.stopBalancer() method in the mongo shell. For example: use config sh.setBalancerState(false) For more information, see the Disable the Balancer (page 717) procedure. Warning: If you do not stop the balancer, the backup could have duplicate data or omit data as chunks migrate while recording backups. Step 2: Lock replica set members. Lock one member of each replica set in each shard so that your backups reflect the state of your database at the nearest possible approximation of a single moment in time. Lock these mongod instances in as short of an interval as possible. To lock or freeze a sharded cluster, issue db.fsyncLock() on a member of each replica set in the cluster. Ensure that the oplog has sufficient capacity to allow these secondaries to catch up to the state of the primaries after finishing the backup procedure. See Oplog Size (page 593) for more information. Step 3: Backup one config server. Run mongodump against a config server mongod instance to back up the clus- ter’s metadata. The config server mongod instance must be version 2.4 or later and must run with the --configsvr option. You only need to back up one config server. Use mongodump with the --oplog option to backup one of the config servers (page 670). mongodump --oplog Step 4: Backup replica set members. Back up the “frozen” replica set members of the shards using mongodump and specifying the --oplog option. You may back up the shards in parallel. Consider the following invocation: mongodump --oplog --out /data/backup/ You must run mongodump on the same system where the mongod ran. mongodump writes the output of this dump as well as the oplog.bson file to the /data/backup/ directory. Step 5: Unlock replica set members. Use db.fsyncUnlock() to unlock the locked replica set members of each shard. Allow these members to catch up with the state of the primary. Step 6: Re-enable the balancer process. Re-enable the balancer with the sh.setBalancerState() method. Use the following command sequence when connected to the mongos with the mongo shell: use config sh.setBalancerState(true) Additional Resources See also MongoDB Cloud Manager113 for seamless automation, backup, and monitoring. 113https://cloud.mongodb.com/?jmp=docs 264 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 Schedule Backup Window for Sharded Clusters Overview In a sharded cluster, the balancer process is responsible for distributing sharded data around the cluster, so that each shard has roughly the same amount of data. However, when creating backups from a sharded cluster it is important that you disable the balancer while taking backups to ensure that no chunk migrations affect the content of the backup captured by the backup procedure. Using the procedure outlined in the section Disable the Balancer (page 717) you can manually stop the balancer process temporarily. As an alternative you can use this procedure to define a balancing window so that the balancer is always disabled during your automated backup operation. Procedure If you have an automated backup schedule, you can disable all balancing operations for a period of time. For instance, consider the following command: use config db.settings.update( { _id: "balancer" }, { $set: { activeWindow: { start: "6:00", stop: "23:00"}}}, true ) This operation configures the balancer to run between 6:00am and 11:00pm, server time. Schedule your backup operation to run and complete outside of this time. Ensure that the backup can complete outside the window when the balancer is running and that the balancer can effectively balance the collection among the shards in the window allotted to each. Restore a Single Shard Overview Restoring a single shard from backup with other unaffected shards requires a number of special consider- ations and practices. This document outlines the additional tasks you must perform when restoring a single shard. Consider the following resources on backups in general as well as backup and restoration of sharded clusters specifi- cally: • Backup and Restore Sharded Clusters (page 259) • Restore a Sharded Cluster (page 266) • MongoDB Backup Methods (page 188) Procedure Always restore sharded clusters as a whole. When you restore a single shard, keep in mind that the balancer process might have moved chunks to or from this shard since the last backup. If that’s the case, you must manually move those chunks, as described in this procedure. Step 1: Restore the shard as you would any other mongod instance. See MongoDB Backup Methods (page 188) for overviews of these procedures. Step 2: Manage the chunks. For all chunks that migrate away from this shard, you do not need to do anything at this time. You do not need to delete these documents from the shard because the chunks are automatically filtered out from queries by mongos. You can remove these documents from the shard, if you like, at your leisure. For chunks that migrate to this shard after the most recent backup, you must manually recover the chunks using back- ups of other shards, or some other source. To determine what chunks have moved, view the changelog collection in the Config Database (page 737). 5.2. Administration Tutorials 265 MongoDB Documentation, Release 3.0.7 Restore a Sharded Cluster Overview You can restore a sharded cluster either from snapshots (page 249) or from BSON database dumps (page 263) created by the mongodump tool. This document describes procedures to • Restore a Sharded Cluster with Filesystem Snapshots (page 266) • Restore a Sharded Cluster with Database Dumps (page 267) Procedures Restore a Sharded Cluster with Filesystem Snapshots The following procedure outlines the steps to restore a sharded cluster from filesystem snapshots. For information on using filesystem snapshots to backup sharded clusters, see Backup a Sharded Cluster with Filesystem Snapshots (page 261). Step 1: Shut down the entire cluster. Stop all mongos and mongod processes, including all shards and all config servers. To stop all members, connect to each member and issue following operations: use admin db.shutdownServer() For version 2.4 or earlier, use db.shutdownServer({force:true}). Step 2: Restore the data files. On each server, extract the data files to the location where the mongod instance will access them and restore the following: • Data files for each server in each shard. Because each production shard is a replica set, for each shard, restore all the members of the replica set. See Restore a Replica Set from MongoDB Backups (page 252). • Data files for each config server. See also: Restore a Snapshot (page 251) Step 3: Restart the config servers. Restart each config server (page 670) mongod instance by issuing a command similar to the following for each, using values appropriate to your configuration: mongod --configsvr --dbpath /data/configdb --port 27019 Step 4: Start one mongos instance. Start one mongos instance. For the --configdb, specify the hostnames (and port numbers) of the config servers started in the step Restart the config servers. (page ??) Step 5: If shard hostnames have changed, update the config database. If shard hostnames have changed, update the shards (page 742) collection in the Config Database (page 737) to reflect the new hostnames. Step 6: Restart all the shard mongod instances. 266 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 Step 7: Restart the other mongos instances. Restart the remaining two mongos instances. For the --configdb, specify the hostnames (and port numbers) of the config servers started in the step Restart the con- fig servers. (page ??) Step 8: Verify that the cluster is operational. Connect to a mongos instance from a mongo shell and use the db.printShardingStatus() method to ensure that the cluster is operational, as follows: db.printShardingStatus() show collections Restore a Sharded Cluster with Database Dumps Changed in version 3.0: mongorestore requires a running MongoDB instances. Earlier versions of mongorestore did not require a running MongoDB instances and instead used the --dbpath option. For instructions specific to your version of mongorestore, refer to the appropriate version of the manual. The following procedure outlines the steps to restore a sharded cluster from the BSON database dumps created by mongodump. For information on using mongodump to backup sharded clusters, see Backup a Sharded Cluster with Database Dumps (page 263) The procedure deploys a new sharded cluster and restores data from database dumps. Step 1: Deploy a new replica set for each shard. For each shard, deploy a new replica set: 1. Start a new mongod for each member of the replica set. Include any other configuration as appropriate. 2. Connect a mongo to one of the mongod instances. In the mongo shell: (a) Run rs.initiate(). (b) Use rs.add() to add the other members of the replica set. For detailed instructions on deploying a replica set, see Deploy a Replica Set (page 603). Step 2: Deploy three new config servers. Start three mongod instances for the config servers (i.e. mongod --configsvr). Include any other configuration as appropriate. For detailed instructions on setting up the config servers, see Start the Config Server Database Instances (page 691). Step 3: Start the mongos instances. Start the mongos instances, specifying the new config servers with --configdb. Include any other configuration as appropriate. For detailed instructions on starting the mongos instances for a sharded cluster, see Start the mongos Instances (page 692). Step 4: Add shards to the cluster. Connect a mongo shell to a mongos instance. Use sh.addShard() to add each replica sets as a shard. For detailed instructions in adding shards to the cluster, see Add Shards to the Cluster (page 692). Step 5: Shut down the mongos instances. Once the new sharded cluster is up, shut down all mongos instances. 5.2. Administration Tutorials 267 MongoDB Documentation, Release 3.0.7 Step 6: Restore the shard data. For each shard, use mongorestore to restore the data dump to the primary’s data directory. Include the --drop option to drop the collections before restoring and, because the backup procedure (page 263) included the --oplog option, include the --oplogReplay option for mongorestore. For example, on the primary for ShardA, run the mongorestore. Specify any other configuration as appropriate. mongorestore --drop --oplogReplay /data/dump/shardA After you have finished restoring all the shards, shut down all shard instances. Step 7: Restore the config server data. For each config server, use mongorestore to restore the data dump to each config server’s data directory. Include the --drop option to drop the collections before restoring and, be- cause the backup procedure (page 263) included the --oplog option, include the --oplogReplay option for mongorestore. mongorestore --drop --oplogReplay /data/dump/configData Step 8: Start one mongos instance. Start one mongos instance. For the --configdb, specify the hostnames (and port numbers) of the config servers started in the step Deploy three new config servers. (page ??) Step 9: If shard hostnames have changed, update the config database. If shard hostnames have changed, update the shards (page 742) collection in the Config Database (page 737) to reflect the new hostnames. Step 10: Restart all the shard mongod instances. Step 11: Restart the other mongos instances. Restart the remaining two mongos instances. For the --configdb, specify the hostnames (and port numbers) of the config servers started in the step Deploy three new config servers. (page ??) Step 12: Verify that the cluster is operational. Connect to a mongos instance from a mongo shell and use the db.printShardingStatus() method to ensure that the cluster is operational, as follows: db.printShardingStatus() show collections See also: MongoDB Backup Methods (page 188), Backup and Restore Sharded Clusters (page 259) Recover Data after an Unexpected Shutdown If MongoDB does not shutdown cleanly, the on-disk representation of the data files will likely reflect an inconsistent state which could lead to data corruption. 114 To prevent data inconsistency and corruption, always shut down the database cleanly and use the durability journaling. MongoDB writes data to the journal, by default, every 100 milliseconds, such that MongoDB can always recover to a consistent state even in the case of an unclean shutdown due to power loss or other system failure. If you are not running as part of a replica set and do not have journaling enabled, use the following procedure to recover data that may be in an inconsistent state. If you are running as part of a replica set, you should always restore 114 You can also use the db.collection.validate() method to test the integrity of a single collection. However, this process is time consuming, and without journaling you can safely assume that the data is in an invalid state and you should either run the repair operation or resync from an intact member of the replica set. 268 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 from a backup or restart the mongod instance with an empty dbPath and allow MongoDB to perform an initial sync to restore the data. To ensure a clean shut down, use one of the following methods: • db.shutdownServer() from the mongo shell, • Your system’s init script, • “Control-C” when running mongod in interactive mode, • kill $(pidof mongod); or kill -2 $(pidof mongod), • On Linux, the mongod --shutdown option. See also: The Administration (page 187) documents, including Replica Set Syncing (page 593), and the documentation on the --repair repairPath and storage.journal.enabled settings. Process Indications When you are aware of a mongod instance running without journaling that stops unexpectedly and you’re not running with replication, you should always run the repair operation before starting MongoDB again. If you’re using replication, then restore from a backup and allow replication to perform an initial sync (page 593) to restore data. If the mongod.lock file in the data directory specified by dbPath,/data/db by default, is not a zero-byte file, then mongod will refuse to start, and you will find a message that contains the following line in your MongoDB log our output: Unclean shutdown detected. This indicates that you need to run mongod with the --repair option. If you run repair when the mongodb.lock file exists in your dbPath, or the optional --repairpath, you will see a message that contains the following line: old lock file: /data/db/mongod.lock. probably means unclean shutdown If you see this message, as a last resort you may remove the lockfile and run the repair operation before starting the database normally, as in the following procedure: Overview Warning: Recovering a member of a replica set. Do not use this procedure to recover a member of a replica set. Instead you should either restore from a backup (page 188) or perform an initial sync using data from an intact member of the set, as described in Resync a Member of a Replica Set (page 633). There are two processes to repair data files that result from an unexpected shutdown: • Use the --repair option in conjunction with the --repairpath option. mongod will read the existing data files, and write the existing data to new data files. You do not need to remove the mongod.lock file before using this procedure. • Use the --repair option. mongod will read the existing data files, write the existing data to new files and replace the existing, possibly corrupt, files with new files. You must remove the mongod.lock file before using this procedure. 5.2. Administration Tutorials 269 MongoDB Documentation, Release 3.0.7 Note: --repair functionality is also available in the shell with the db.repairDatabase() helper for the repairDatabase command. Procedures Important: Always Run mongod as the same user to avoid changing the permissions of the MongoDB data files. Repair Data Files and Preserve Original Files To repair your data files using the --repairpath option to preserve the original data files unmodified. Step 1: Start mongod using the option to replace the original files with the repaired files. Start the mongod instance using the --repair option and the --repairpath option. Issue a command similar to the following: mongod --dbpath /data/db --repair --repairpath /data/db0 When this completes, the new repaired data files will be in the /data/db0 directory. Step 2: Start mongod with the new data directory. Start mongod using the following invocation to point the dbPath at /data/db0: mongod --dbpath /data/db0 Once you confirm that the data files are operational you may delete or archive the old data files in the /data/db directory. You may also wish to move the repaired files to the old database location or update the dbPath to indicate the new location. Repair Data Files without Preserving Original Files To repair your data files without preserving the original files, do not use the --repairpath option, as in the following procedure: Warning: After you remove the mongod.lock file you must run the --repair process before using your database. Step 1: Remove the stale lock file. For example: rm /data/db/mongod.lock Replace /data/db with your dbPath where your MongoDB instance’s data files reside. Step 2: Start mongod using the option to replace the original files with the repaired files. Start the mongod instance using the --repair option, which replaces the original data files with the repaired data files. Issue a command similar to the following: mongod --dbpath /data/db --repair When this completes, the repaired data files will replace the original data files in the /data/db directory. 270 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 Step 3: Start mongod as usual. Start mongod using the following invocation to point the dbPath at /data/db: mongod --dbpath /data/db mongod.lock In normal operation, you should never remove the mongod.lock file and start mongod. Instead consider the one of the above methods to recover the database and remove the lock files. In dire situations you can remove the lockfile, and start the database using the possibly corrupt files, and attempt to recover data from the database; however, it’s impossible to predict the state of the database in these situations. If you are not running with journaling, and your database shuts down unexpectedly for any reason, you should always proceed as if your database is in an inconsistent and likely corrupt state. If at all possible restore from backup (page 188) or, if running as a replica set, restore by performing an initial sync using data from an intact member of the set, as described in Resync a Member of a Replica Set (page 633). 5.2.3 MongoDB Scripting The mongo shell is an interactive JavaScript shell for MongoDB, and is part of all MongoDB distributions115. This section provides an introduction to the shell, and outlines key functions, operations, and use of the mongo shell. Also consider FAQ: The mongo Shell (page 756) and the shell method and other relevant reference material. Note: Most examples in the MongoDB Manual use the mongo shell; however, many drivers provide similar interfaces to MongoDB. Server-side JavaScript (page 271) Details MongoDB’s support for executing JavaScript code for server-side opera- tions. Data Types in the mongo Shell (page 273) Describes the super-set of JSON available for use in the mongo shell. Write Scripts for the mongo Shell (page 275) An introduction to the mongo shell for writing scripts to manipulate data and administer MongoDB. Getting Started with the mongo Shell (page 277) Introduces the use and operation of the MongoDB shell. Access the mongo Shell Help Information (page 281) Describes the available methods for accessing online help for the operation of the mongo interactive shell. mongo Shell Quick Reference (page 283) A high level reference to the use and operation of the mongo shell. Server-side JavaScript Overview MongoDB provides the following commands, methods, and operator that perform server-side execution of JavaScript code: • mapReduce and the corresponding mongo shell method db.collection.mapReduce(). mapReduce operations map, or associate, values to keys, and for keys with multiple values, reduce the values for each key to a single object. For more information, see Map-Reduce (page 442). • $where operator that evaluates a JavaScript expression or a function in order to query for documents. 115http://www.mongodb.org/downloads 5.2. Administration Tutorials 271 MongoDB Documentation, Release 3.0.7 You can also specify a JavaScript file to the mongo shell to run on the server. For more information, see Running .js files via a mongo shell Instance on the Server (page 272) JavaScript in MongoDB Although these methods use JavaScript, most interactions with MongoDB do not use JavaScript but use an idiomatic driver in the language of the interacting application. You can also disable server-side execution of JavaScript. For details, see Disable Server-Side Execution of JavaScript (page 273). Running .js files via a mongo shell Instance on the Server You can specify a JavaScript (.js) file to a mongo shell instance to execute the file on the server. This is a good technique for performing batch administrative work. When you run mongo shell on the server, connecting via the localhost interface, the connection is fast with low latency. The command helpers (page 284) provided in the mongo shell are not available in JavaScript files because they are not valid JavaScript. The following table maps the most common mongo shell helpers to their JavaScript equivalents. Shell Helpers JavaScript Equivalents show dbs, show databases db.adminCommand('listDatabases') use db= db.getSiblingDB('') show collections db.getCollectionNames() show users db.getUsers() show roles db.getRoles({showBuiltinRoles: true}) show log db.adminCommand({ 'getLog': ''}) show logs db.adminCommand({ 'getLog':'*'}) it cursor= db.collection.find() if ( cursor.hasNext() ){ cursor.next(); } Concurrency Changed in version 2.4. The V8 JavaScript engine, which became the default in 2.4, allows multiple JavaScript operations to execute at the same time. Prior to 2.4, MongoDB operations that required the JavaScript interpreter had to acquire a lock, and a single mongod could only run a single JavaScript operation at a time. 272 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 Refer to the individual method or operator documentation for any concurrency information. See also the concurrency table (page 759). Disable Server-Side Execution of JavaScript You can disable all server-side execution of JavaScript, by passing the --noscripting option on the command line or setting security.javascriptEnabled in a configuration file. See also: Store a JavaScript Function on the Server (page 240) Data Types in the mongo Shell MongoDB BSON provides support for additional data types than JSON. Drivers provide native support for these data types in host languages and the mongo shell also provides several helper classes to support the use of these data types in the mongo JavaScript shell. See the Extended JSON reference for additional information. Types Date The mongo shell provides various methods to return the date, either as a string or as a Date object: • Date() method which returns the current date as a string. • new Date() constructor which returns a Date object using the ISODate() wrapper. • ISODate() constructor which returns a Date object using the ISODate() wrapper. Internally, Date (page 184) objects are stored as a 64 bit integer representing the number of milliseconds since the Unix epoch (Jan 1, 1970), which results in a representable date range of about 290 millions years into the past and future. Return Date as a String To return the date as a string, use the Date() method, as in the following example: var myDateString= Date(); To print the value of the variable, type the variable name in the shell, as in the following: myDateString The result is the value of myDateString: Wed Dec 19 2012 01:03:25 GMT-0500 (EST) To verify the type, use the typeof operator, as in the following: typeof myDateString The operation returns string. Return Date The mongo shell wraps objects of Date type with the ISODate helper; however, the objects remain of type Date. The following example uses both the new Date() constructor and the ISODate() constructor to return Date objects. 5.2. Administration Tutorials 273 MongoDB Documentation, Release 3.0.7 var myDate= new Date(); var myDateInitUsingISODateWrapper= ISODate(); You can use the new operator with the ISODate() constructor as well. To print the value of the variable, type the variable name in the shell, as in the following: myDate The result is the Date value of myDate wrapped in the ISODate() helper: ISODate("2012-12-19T06:01:17.171Z") To verify the type, use the instanceof operator, as in the following: myDate instanceof Date myDateInitUsingISODateWrapper instanceof Date The operation returns true for both. ObjectId The mongo shell provides the ObjectId() wrapper class around the ObjectId data type. To generate a new ObjectId, use the following operation in the mongo shell: new ObjectId See ObjectId (page 180) for full documentation of ObjectIds in MongoDB. NumberLong By default, the mongo shell treats all numbers as floating-point values. The mongo shell provides the NumberLong() wrapper to handle 64-bit integers. The NumberLong() wrapper accepts the long as a string: NumberLong("2090845886852") The following examples use the NumberLong() wrapper to write to the collection: db.collection.insert( { _id: 10, calc: NumberLong("2090845886852")}) db.collection.update( { _id: 10}, { $set: { calc: NumberLong("2555555000000")}}) db.collection.update( { _id: 10}, { $inc: { calc: NumberLong(5)}}) Retrieve the document to verify: db.collection.findOne( { _id: 10}) In the returned document, the calc field contains a NumberLong object: { "_id" : 10, "calc" : NumberLong("2555555000005")} If you use the $inc to increment the value of a field that contains a NumberLong object by a float, the data type changes to a floating point value, as in the following example: 1. Use $inc to increment the calc field by 5, which the mongo shell treats as a float: db.collection.update( { _id: 10}, { $inc: { calc:5}}) 274 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 2. Retrieve the updated document: db.collection.findOne( { _id: 10}) In the updated document, the calc field contains a floating point value: { "_id" : 10, "calc": 2555555000010} NumberInt By default, the mongo shell treats all numbers as floating-point values. The mongo shell provides the NumberInt() constructor to explicitly specify 32-bit integers. Check Types in the mongo Shell To determine the type of fields, the mongo shell provides the instanceof and typeof operators. instanceof instanceof returns a boolean to test if a value is an instance of some type. For example, the following operation tests whether the _id field is an instance of type ObjectId: mydoc._id instanceof ObjectId The operation returns true. typeof typeof returns the type of a field. For example, the following operation returns the type of the _id field: typeof mydoc._id In this case typeof will return the more generic object type rather than ObjectId type. Write Scripts for the mongo Shell You can write scripts for the mongo shell in JavaScript that manipulate data in MongoDB or perform administrative operation. For more information about the mongo shell see MongoDB Scripting (page 271), and see the Running .js files via a mongo shell Instance on the Server (page 272) section for more information about using these mongo script. This tutorial provides an introduction to writing JavaScript that uses the mongo shell to access MongoDB. Opening New Connections From the mongo shell or from a JavaScript file, you can instantiate database connections using the Mongo() con- structor: new Mongo() new Mongo() new Mongo() Consider the following example that instantiates a new connection to the MongoDB instance running on localhost on the default port and sets the global db variable to myDatabase using the getDB() method: conn= new Mongo(); db= conn.getDB("myDatabase"); 5.2. Administration Tutorials 275 MongoDB Documentation, Release 3.0.7 If connecting to a MongoDB instance that has enforces access control, you can use the db.auth() method to authenticate. Additionally, you can use the connect() method to connect to the MongoDB instance. The following example connects to the MongoDB instance that is running on localhost with the non-default port 27020 and set the global db variable: db= connect("localhost:27020/myDatabase"); See also: https://docs.mongodb.org/manual/reference/method/ Differences Between Interactive and Scripted mongo When writing scripts for the mongo shell, consider the following: • To set the db global variable, use the getDB() method or the connect() method. You can assign the database reference to a variable other than db. • Write operations in the mongo shell use the “safe writes” by default. If performing bulk operations, use the Bulk() methods. See Write Method Acknowledgements (page 869) for more information. Changed in version 2.6: Before MongoDB 2.6, call db.getLastError() explicitly to wait for the result of write operations (page 75). • You cannot use any shell helper (e.g. use , show dbs, etc.) inside the JavaScript file because they are not valid JavaScript. The following table maps the most common mongo shell helpers to their JavaScript equivalents. Shell Helpers JavaScript Equivalents show dbs, show databases db.adminCommand('listDatabases') use db= db.getSiblingDB('') show collections db.getCollectionNames() show users db.getUsers() show roles db.getRoles({showBuiltinRoles: true}) show log db.adminCommand({ 'getLog': ''}) show logs db.adminCommand({ 'getLog':'*'}) it cursor= db.collection.find() if ( cursor.hasNext() ){ cursor.next(); } 276 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 • In interactive mode, mongo prints the results of operations including the content of all cursors. In scripts, either use the JavaScript print() function or the mongo specific printjson() function which returns formatted JSON. Example To print all items in a result cursor in mongo shell scripts, use the following idiom: cursor= db.collection.find(); while ( cursor.hasNext() ) { printjson( cursor.next() ); } Scripting From the system prompt, use mongo to evaluate JavaScript. --eval option Use the --eval option to mongo to pass the shell a JavaScript fragment, as in the following: mongo test --eval "printjson(db.getCollectionNames())" This returns the output of db.getCollectionNames() using the mongo shell connected to the mongod or mongos instance running on port 27017 on the localhost interface. Execute a JavaScript file You can specify a .js file to the mongo shell, and mongo will execute the JavaScript directly. Consider the following example: mongo localhost:27017/test myjsfile.js This operation executes the myjsfile.js script in a mongo shell that connects to the test database on the mongod instance accessible via the localhost interface on port 27017. Alternately, you can specify the mongodb connection parameters inside of the javascript file using the Mongo() constructor. See Opening New Connections (page 275) for more information. You can execute a .js file from within the mongo shell, using the load() function, as in the following: load("myjstest.js") This function loads and executes the myjstest.js file. The load() method accepts relative and absolute paths. If the current working directory of the mongo shell is /data/db, and the myjstest.js resides in the /data/db/scripts directory, then the following calls within the mongo shell would be equivalent: load("scripts/myjstest.js") load("/data/db/scripts/myjstest.js") Note: There is no search path for the load() function. If the desired script is not in the current working directory or the full specified path, mongo will not be able to access the file. Getting Started with the mongo Shell This document provides a basic introduction to using the mongo shell. See Install MongoDB (page 5) for instructions on installing MongoDB for your system. 5.2. Administration Tutorials 277 MongoDB Documentation, Release 3.0.7 Start the mongo Shell To start the mongo shell and connect to your MongoDB instance running on localhost with default port: 1. Go to your : cd 2. Type ./bin/mongo to start mongo: ./bin/mongo If you have added the /bin to the PATH environment variable, you can just type mongo instead of ./bin/mongo. 3. To display the database you are using, type db: db The operation should return test, which is the default database. To switch databases, issue the use helper, as in the following example: use To list the available databases, use the helper show dbs. See also How can I access different databases temporarily? (page 756) to access a different database from the current database without switching your current database context (i.e. db..) To start the mongo shell with other options, see examples of starting up mongo and mongo reference which provides details on the available options. Note: When starting, mongo checks the user’s HOME directory for a JavaScript file named .mongorc.js. If found, mongo interprets the content of .mongorc.js before displaying the prompt for the first time. If you use the shell to evaluate a JavaScript file or expression, either by using the --eval option on the command line or by specifying a .js file to mongo, mongo will read the .mongorc.js file after the JavaScript has finished processing. You can prevent .mongorc.js from being loaded by using the --norc option. Executing Queries From the mongo shell, you can use the shell methods to run queries, as in the following example: db..find() • The db refers to the current database. • The is the name of the collection to query. See Collection Help (page 282) to list the available collections. If the mongo shell does not accept the name of the collection, for instance if the name contains a space, hyphen, or starts with a number, you can use an alternate syntax to refer to the collection, as in the following: db["3test"].find() db.getCollection("3test").find() • The find() method is the JavaScript method to retrieve documents from . The find() method returns a cursor to the results; however, in the mongo shell, if the returned cursor is not assigned to a variable using the var keyword, then the cursor is automatically iterated up to 20 times to print up to the first 20 documents that match the query. The mongo shell will prompt Type it to iterate another 20 times. 278 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 You can set the DBQuery.shellBatchSize attribute to change the number of iteration from the default value 20, as in the following example which sets it to 10: DBQuery.shellBatchSize= 10; For more information and examples on cursor handling in the mongo shell, see Cursors (page 66). See also Cursor Help (page 282) for list of cursor help in the mongo shell. For more documentation of basic MongoDB operations in the mongo shell, see: • Getting Started with MongoDB116 • mongo Shell Quick Reference (page 283) • Read Operations (page 62) • Write Operations (page 75) • Indexing Tutorials (page 517) Print The mongo shell automatically prints the results of the find() method if the returned cursor is not assigned to a variable using the var keyword. To format the result, you can add the .pretty() to the operation, as in the following: db..find().pretty() In addition, you can use the following explicit print methods in the mongo shell: • print() to print without formatting • print(tojson()) to print with JSON formatting and equivalent to printjson() • printjson() to print with JSON formatting and equivalent to print(tojson()) Evaluate a JavaScript File You can execute a .js file from within the mongo shell, using the load() function, as in the following: load("myjstest.js") This function loads and executes the myjstest.js file. The load() method accepts relative and absolute paths. If the current working directory of the mongo shell is /data/db, and the myjstest.js resides in the /data/db/scripts directory, then the following calls within the mongo shell would be equivalent: load("scripts/myjstest.js") load("/data/db/scripts/myjstest.js") Note: There is no search path for the load() function. If the desired script is not in the current working directory or the full specified path, mongo will not be able to access the file. 116http://docs.mongodb.org/getting-started/shell 5.2. Administration Tutorials 279 MongoDB Documentation, Release 3.0.7 Use a Custom Prompt You may modify the content of the prompt by creating the variable prompt in the shell. The prompt variable can hold strings as well as any arbitrary JavaScript. If prompt holds a function that returns a string, mongo can display dynamic information in each prompt. Consider the following examples: Example Create a prompt with the number of operations issued in the current session, define the following variables: cmdCount=1; prompt= function() { return (cmdCount++)+ "> "; } The prompt would then resemble the following: 1> db.collection.find() 2> show collections 3> Example To create a mongo shell prompt in the form of @$ define the following variables: host= db.serverStatus().host; prompt= function() { return db+"@"+host+"$ "; } The prompt would then resemble the following: @$ use records switched to db records records@$ Example To create a mongo shell prompt that contains the system up time and the number of documents in the current database, define the following prompt variable: prompt= function() { return "Uptime:"+db.serverStatus().uptime+" Documents:"+db.stats().objects+" > "; } The prompt would then resemble the following: Uptime:5897 Documents:6> db.people.save({name: "James"}); Uptime:5948 Documents:7> Use an External Editor in the mongo Shell New in version 2.2. In the mongo shell you can use the edit operation to edit a function or variable in an external editor. The edit operation uses the value of your environments EDITOR variable. 280 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 At your system prompt you can define the EDITOR variable and start mongo with the following two operations: export EDITOR=vim mongo Then, consider the following example shell session: MongoDB shell version: 2.2.0 > function f() {} > edit f >f function f() { print("this really works"); } > f() this really works >o={} {} > edit o >o { "soDoes": "this"} > Note: As mongo shell interprets code edited in an external editor, it may modify code in functions, depending on the JavaScript compiler. For mongo may convert 1+1 to 2 or remove comments. The actual changes affect only the appearance of the code and will vary based on the version of JavaScript used but will not affect the semantics of the code. Exit the Shell To exit the shell, type quit() or use the shortcut. See also: Getting Started Guide117 Access the mongo Shell Help Information In addition to the documentation in the MongoDB Manual, the mongo shell provides some additional information in its “online” help system. This document provides an overview of accessing this help information. See also: • mongo Manual Page • MongoDB Scripting (page 271), and • mongo Shell Quick Reference (page 283). Command Line Help To see the list of options and help for starting the mongo shell, use the --help option from the command line: 117https://docs.mongodb.org/getting-started/shell 5.2. Administration Tutorials 281 MongoDB Documentation, Release 3.0.7 mongo --help Shell Help To see the list of help, in the mongo shell, type help: help Database Help • To see the list of databases on the server, use the show dbs command: show dbs New in version 2.4: show databases is now an alias for show dbs • To see the list of help for methods you can use on the db object, call the db.help() method: db.help() • To see the implementation of a method in the shell, type the db. without the parenthesis (()), as in the following example which will return the implementation of the method db.updateUser(): db.updateUser Collection Help • To see the list of collections in the current database, use the show collections command: show collections • To see the help for methods available on the collection objects (e.g. db.), use the db..help() method: db.collection.help() can be the name of a collection that exists, although you may specify a collection that doesn’t exist. • To see the collection method implementation, type the db.. name without the parenthesis (()), as in the following example which will return the implementation of the save() method: db.collection.save Cursor Help When you perform read operations (page 63) with the find() method in the mongo shell, you can use various cursor methods to modify the find() behavior and various JavaScript methods to handle the cursor returned from the find() method. • To list the available modifier and cursor handling methods, use the db.collection.find().help() command: 282 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 db.collection.find().help() can be the name of a collection that exists, although you may specify a collection that doesn’t exist. • To see the implementation of the cursor method, type the db..find(). name without the parenthesis (()), as in the following example which will return the implementation of the toArray() method: db.collection.find().toArray Some useful methods for handling cursors are: • hasNext() which checks whether the cursor has more documents to return. • next() which returns the next document and advances the cursor position forward by one. • forEach() which iterates the whole cursor and applies the to each document returned by the cursor. The expects a single argument which corresponds to the document from each iteration. For examples on iterating a cursor and retrieving the documents from the cursor, see cursor handling (page 66). See also js-query-cursor-methods for all available cursor methods. Type Help To get a list of the wrapper classes available in the mongo shell, such as BinData(), type help misc in the mongo shell: help misc mongo Shell Quick Reference mongo Shell Command History You can retrieve previous commands issued in the mongo shell with the up and down arrow keys. Command history is stored in ~/.dbshell file. See .dbshell for more information. Command Line Options The mongo shell can be started with numerous options. See mongo shell page for details on all available options. The following table displays some common options for mongo: Op- tion Description --help Show command line options --nodb Start mongo shell without connecting to a database. To connect later, see Opening New Connections (page 275). --shellUsed in conjunction with a JavaScript file (i.e. <file.js>) to continue in the mongo shell after running the JavaScript file. See JavaScript file (page 277) for an example. 5.2. Administration Tutorials 283 MongoDB Documentation, Release 3.0.7 Command Helpers The mongo shell provides various help. The following table displays some common help methods and commands: Help Methods and Commands Description help Show help. db.help() Show help for database methods. db..help()Show help on collection methods. The can be the name of an existing collection or a non-existing collection. show dbs Print a list of all databases on the server. use Switch current database to . The mongo shell variable db is set to the current database. show collections Print a list of all collections for current database show users Print a list of users for current database. show roles Print a list of all roles, both user-defined and built-in, for the current database. show profile Print the five most recent operations that took 1 millisecond or more. See documentation on the database profiler (page 232) for more information. show databases New in version 2.4: Print a list of all available databases. load() Execute a JavaScript file. See Getting Started with the mongo Shell (page 277) for more information. Basic Shell JavaScript Operations The mongo shell provides a JavaScript API for database operations. In the mongo shell, db is the variable that references the current database. The variable is automatically set to the default database test or is set when you use the use to switch current database. The following table displays some common JavaScript operations: 284 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 JavaScript Database Operations Description db.auth() If running in secure mode, authenticate the user. coll = db. Set a specific collection in the current database to a vari- able coll, as in the following example: coll= db.myCollection; You can perform operations on the myCollection using the variable, as in the following example: coll.find(); find() Find all documents in the collection and returns a cursor. See the db.collection.find() and Query Docu- ments (page 98) for more information and examples. See Cursors (page 66) for additional information on cur- sor handling in the mongo shell. insert() Insert a new document into the collection. update() Update an existing document in the collection. See Write Operations (page 75) for more information. save() Insert either a new document or update an existing doc- ument in the collection. See Write Operations (page 75) for more information. remove() Delete documents from the collection. See Write Operations (page 75) for more information. drop() Drops or removes completely the collection. createIndex() Create a new index on the collection if the index does not exist; otherwise, the operation has no effect. db.getSiblingDB() Return a reference to another database using this same connection without explicitly switching the current database. This allows for cross database queries. See How can I access different databases temporarily? (page 756) for more information. For more information on performing operations in the shell, see: • MongoDB CRUD Concepts (page 62) • Read Operations (page 62) • Write Operations (page 75) • js-administrative-methods Keyboard Shortcuts Changed in version 2.2. The mongo shell provides most keyboard shortcuts similar to those found in the bash shell or in Emacs. For some functions mongo provides multiple key bindings, to accommodate several familiar paradigms. The following table enumerates the keystrokes supported by the mongo shell: Keystroke Function Up-arrow previous-history Down-arrow next-history Home beginning-of-line End end-of-line Tab autocomplete Continued on next page 5.2. Administration Tutorials 285 MongoDB Documentation, Release 3.0.7 Table 5.1 – continued from previous page Keystroke Function Left-arrow backward-character Right-arrow forward-character Ctrl-left-arrow backward-word Ctrl-right-arrow forward-word Meta-left-arrow backward-word Meta-right-arrow forward-word Ctrl-A beginning-of-line Ctrl-B backward-char Ctrl-C exit-shell Ctrl-D delete-char (or exit shell) Ctrl-E end-of-line Ctrl-F forward-char Ctrl-G abort Ctrl-J accept-line Ctrl-K kill-line Ctrl-L clear-screen Ctrl-M accept-line Ctrl-N next-history Ctrl-P previous-history Ctrl-R reverse-search-history Ctrl-S forward-search-history Ctrl-T transpose-chars Ctrl-U unix-line-discard Ctrl-W unix-word-rubout Ctrl-Y yank Ctrl-Z Suspend (job control works in linux) Ctrl-H (i.e. Backspace) backward-delete-char Ctrl-I (i.e. Tab) complete Meta-B backward-word Meta-C capitalize-word Meta-D kill-word Meta-F forward-word Meta-L downcase-word Meta-U upcase-word Meta-Y yank-pop Meta-[Backspace] backward-kill-word Meta-< beginning-of-history Meta-> end-of-history Queries In the mongo shell, perform read operations using the find() and findOne() methods. The find() method returns a cursor object which the mongo shell iterates to print documents on screen. By default, mongo prints the first 20. The mongo shell will prompt the user to “Type it” to continue iterating the next 20 results. The following table provides some common read operations in the mongo shell: 286 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 Read Operations Description db.collection.find() Find the documents matching the criteria in the collection. If the criteria is not specified or is empty (i.e {} ), the read operation selects all doc- uments in the collection. The following example selects the documents in the users collection with the name field equal to "Joe": coll= db.users; coll.find( { name: "Joe"}); For more information on specifying the cri- teria, see Query Documents (page 98). db.collection.find(, ) Find documents matching the criteria and re- turn just specific fields in the . The following example selects all documents from the collection but returns only the name field and the _id field. The _id is always returned unless explicitly spec- ified to not return. coll= db.users; coll.find( { }, { name: true } ); For more information on specifying the , see Limit Fields to Return from a Query (page 109). db.collection.find().sort() Return results in the specified . The following example selects all documents from the collection and returns the results sorted by the name field in ascending order (1). Use -1 for descending or- der: coll= db.users; coll.find().sort( { name:1}); db.collection.find().sort() Return the documents matching the criteria in the specified . db.collection.find( ... ).limit( ) Limit result to rows. Highly recommended if you need only a certain number of rows for best perfor- mance. db.collection.find( ... ).skip( ) Skip results. count() Returns total number of documents in the collection. db.collection.find().count() Returns the total number of documents that match the query. The count() ignores limit() and skip(). For example, if 100 records match but the limit is 10, count() will return 100. This will be faster than it- erating yourself, but still take time. db.collection.findOne() Find and return a single document. Returns null if not found. The following example selects a single document in the users collection with the name field matches to "Joe": coll= db.users; coll.findOne( { name: "Joe"}); Internally, the findOne() method is the find() method with a limit(1). 5.2. Administration Tutorials 287 MongoDB Documentation, Release 3.0.7 See Query Documents (page 98) and Read Operations (page 62) documentation for more information and exam- ples. See https://docs.mongodb.org/manual/reference/operator/query to specify other query operators. Error Checking Methods Changed in version 2.6. The mongo shell write methods now integrates the Write Concern (page 80) directly into the method execution rather than with a separate db.getLastError() method. As such, the write methods now return a WriteResult() object that contains the results of the operation, including any write errors and write concern errors. Previous versions used db.getLastError() and db.getLastErrorObj() methods to return error informa- tion. Administrative Command Helpers The following table lists some common methods to support database administration: JavaScript Database Administration Methods Description db.cloneDatabase()Clone the current database from the specified. The database instance must be in noauth mode. db.copyDatabase(, , ) Copy the database from the to the database on the current server. The database instance must be in noauth mode. db.fromColl.renameCollection()Rename collection from fromColl to . db.repairDatabase() Repair and compact the current database. This operation can be very slow on large databases. db.getCollectionNames()Get the list of all collections in the current database. db.dropDatabase() Drops the current database. See also administrative database methods for a full list of methods. Opening Additional Connections You can create new connections within the mongo shell. The following table displays the methods to create the connections: JavaScript Connection Create Methods Description db= connect("<:port>/") Open a new database connection. conn= new Mongo() db= conn.getDB("dbname") Open a connection to a new server using new Mongo(). Use getDB() method of the connection to select a database. See also Opening New Connections (page 275) for more information on the opening new connections from the mongo shell. 288 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 Miscellaneous The following table displays some miscellaneous methods: Method Description Object.bsonsize() Prints the BSON size of a in bytes See the MongoDB JavaScript API Documentation118 for a full list of JavaScript methods . Additional Resources Consider the following reference material that addresses the mongo shell and its interface: • mongo • js-administrative-methods • database-commands • Aggregation Reference (page 469) • Getting Started Guide119 Additionally, the MongoDB source code repository includes a jstests directory120 which contains numerous mongo shell scripts. 5.2.4 MongoDB Tutorials This page lists the tutorials available as part of the MongoDB Manual. In addition to these tutorial in the manual, MongoDB provides Getting Started Guides in various driver editions. If there is a process or pattern that you would like to see included here, please open a Jira Case121. Installation • Install MongoDB From Tarball (page 23) • Install MongoDB on Red Hat Enterprise or CentOS Linux (page 7) • Install MongoDB on Debian (page 20) • Install MongoDB on Ubuntu (page 17) • Install MongoDB on Amazon Linux (page 14) • Install MongoDB on SUSE (page 11) • Install MongoDB on OS X (page 25) • Install MongoDB on Windows (page 28) 118http://api.mongodb.org/js/index.html 119https://docs.mongodb.org/getting-started/shell 120https://github.com/mongodb/mongo/tree/master/jstests/ 121https://jira.mongodb.org/browse/DOCS 5.2. Administration Tutorials 289 MongoDB Documentation, Release 3.0.7 Administration Replica Sets • Deploy a Replica Set (page 603) • Deploy Replica Set and Configure Authentication and Authorization (page 356) • Convert a Standalone to a Replica Set (page 614) • Add Members to a Replica Set (page 616) • Remove Members from Replica Set (page 618) • Replace a Replica Set Member (page 620) • Adjust Priority for Replica Set Member (page 620) • Resync a Member of a Replica Set (page 633) • Deploy a Geographically Redundant Replica Set (page 608) • Change the Size of the Oplog (page 628) • Force a Member to Become Primary (page 631) • Change Hostnames in a Replica Set (page 642) • Add an Arbiter to Replica Set (page 614) • Convert a Secondary to an Arbiter (page 626) • Configure a Secondary’s Sync Target (page 645) • Configure a Delayed Replica Set Member (page 624) • Configure a Hidden Replica Set Member (page 623) • Configure Non-Voting Replica Set Member (page 625) • Prevent Secondary from Becoming Primary (page 621) • Configure Replica Set Tag Sets (page 635) • Manage Chained Replication (page 641) • Reconfigure a Replica Set with Unavailable Members (page 638) • Recover Data after an Unexpected Shutdown (page 268) • Troubleshoot Replica Sets (page 646) Sharding • Deploy a Sharded Cluster (page 691) • Convert a Replica Set to a Replicated Sharded Cluster (page 699) • Add Shards to a Cluster (page 697) • Remove Shards from an Existing Sharded Cluster (page 719) • Deploy Three Config Servers for Production Deployments (page 698) • Migrate Config Servers with the Same Hostname (page 707) • Migrate Config Servers with Different Hostnames (page 707) 290 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 • Replace Disabled Config Server (page 708) • Migrate a Sharded Cluster to Different Hardware (page 709) • Backup Cluster Metadata (page 712) • Backup a Small Sharded Cluster with mongodump (page 260) • Backup a Sharded Cluster with Filesystem Snapshots (page 261) • Backup a Sharded Cluster with Database Dumps (page 263) • Restore a Single Shard (page 265) • Restore a Sharded Cluster (page 266) • Schedule Backup Window for Sharded Clusters (page 265) • Manage Shard Tags (page 730) Basic Operations • Use Database Commands (page 228) • Recover Data after an Unexpected Shutdown (page 268) • Expire Data from Collections by Setting TTL (page 215) • Analyze Performance of Database Operations (page 232) • Rotate Log Files (page 236) • Build Old Style Indexes (page 524) • Manage mongod Processes (page 229) • Back Up and Restore with MongoDB Tools (page 254) • Backup and Restore with Filesystem Snapshots (page 249) Security • Configure Linux iptables Firewall for MongoDB (page 340) • Configure Windows netsh Firewall for MongoDB (page 343) • Enable Client Access Control (page 360) • Create a User Administrator (page 387) • Manage User and Roles (page 389) • Generate a Key File (page 383) • Configure MongoDB with Kerberos Authentication on Linux (page 376) • Create a Vulnerability Report (page 403) Development Patterns • Perform Two Phase Commits (page 119) • Create an Auto-Incrementing Sequence Field (page 129) 5.2. Administration Tutorials 291 MongoDB Documentation, Release 3.0.7 • Enforce Unique Keys for Sharded Collections (page 732) • Aggregation Examples (page 452) • Model Data to Support Keyword Search (page 169) • Limit Number of Elements in an Array after an Update (page 112) • Perform Incremental Map-Reduce (page 463) • Troubleshoot the Map Function (page 465) • Troubleshoot the Reduce Function (page 466) • Store a JavaScript Function on the Server (page 240) Text Search Patterns • Create a text Index (page 540) • Specify a Language for Text Index (page 540) • Specify Name for text Index (page 542) • Control Search Results with Weights (page 543) • Limit the Number of Entries Scanned (page 545) Data Modeling Patterns • Model One-to-One Relationships with Embedded Documents (page 156) • Model One-to-Many Relationships with Embedded Documents (page 157) • Model One-to-Many Relationships with Document References (page 158) • Model Data for Atomic Operations (page 168) • Model Tree Structures with Parent References (page 161) • Model Tree Structures with Child References (page 162) • Model Tree Structures with Materialized Paths (page 165) • Model Tree Structures with Nested Sets (page 167) See also: The MongoDB Manual contains administrative documentation and tutorials though out several sections. See Replica Set Tutorials (page 602) and Sharded Cluster Tutorials (page 690) for additional tutorials and information. 5.3 Administration Reference UNIX ulimit Settings (page 293) Describes user resources limits (i.e. ulimit) and introduces the considerations and optimal configurations for systems that run MongoDB deployments. System Collections (page 297) Introduces the internal collections that MongoDB uses to track per-database metadata, including indexes, collections, and authentication credentials. Database Profiler Output (page 298) Describes the data collected by MongoDB’s operation profiler, which intro- spects operations and reports data for analysis on performance and behavior. 292 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 Server Status Output (page 302) Provides an example and a high level overview of the output of the serverStatus command. Journaling Mechanics (page 314) Describes the internal operation of MongoDB’s journaling facility and outlines how the journal allows MongoDB to provide provides durability and crash resiliency. Exit Codes and Statuses (page 316) Lists the unique codes returned by mongos and mongod processes upon exit. 5.3.1 UNIX ulimit Settings Most UNIX-like operating systems, including Linux and OS X, provide ways to limit and control the usage of system resources such as threads, files, and network connections on a per-process and per-user basis. These “ulimits” prevent single users from using too many system resources. Sometimes, these limits have low default values that can cause a number of issues in the course of normal MongoDB operation. Note: Red Hat Enterprise Linux and CentOS 6 place a max process limitation of 1024 which overrides ulimit set- tings. Create a file named /etc/security/limits.d/99-mongodb-nproc.conf with new soft nproc and hard nproc values to increase the process limit. See /etc/security/limits.d/90-nproc.conf file as an example. Resource Utilization mongod and mongos each use threads and file descriptors to track connections and manage internal operations. This section outlines the general resource utilization patterns for MongoDB. Use these figures in combination with the actual information about your deployment and its use to determine ideal ulimit settings. Generally, all mongod and mongos instances: • track each incoming connection with a file descriptor and a thread. • track each internal thread or pthread as a system process. mongod • 1 file descriptor for each data file in use by the mongod instance. • 1 file descriptor for each journal file used by the mongod instance when storage.journal.enabled is true. • In replica sets, each mongod maintains a connection to all other members of the set. mongod uses background threads for a number of internal processes, including TTL collections (page 215), replica- tion, and replica set health checks, which may require a small number of additional resources. mongos In addition to the threads and file descriptors for client connections, mongos must maintain connects to all config servers and all shards, which includes all members of all replica sets. For mongos, consider the following behaviors: • mongos instances maintain a connection pool to each shard so that the mongos can reuse connections and quickly fulfill requests without needing to create new connections. 5.3. Administration Reference 293 MongoDB Documentation, Release 3.0.7 • You can limit the number of incoming connections using the maxIncomingConnections run-time option. By restricting the number of incoming connections you can prevent a cascade effect where the mongos creates too many connections on the mongod instances. Note: Changed in version 2.6: MongoDB removed the upward limit on the maxIncomingConnections setting. Review and Set Resource Limits ulimit You can use the ulimit command at the system prompt to check system limits, as in the following example: $ ulimit -a -t: cpu time(seconds) unlimited -f: file size(blocks) unlimited -d: data seg size(kbytes) unlimited -s: stack size(kbytes) 8192 -c: core file size(blocks)0 -m: resident set size(kbytes) unlimited -u: processes 192276 -n: file descriptors 21000 -l: locked-in-memory size(kb) 40000 -v: address space(kb) unlimited -x: file locks unlimited -i: pending signals 192276 -q: bytes in POSIX msg queues 819200 -e: max nice 30 -r: max rt priority 65 -N 15: unlimited ulimit refers to the per-user limitations for various resources. Therefore, if your mongod instance executes as a user that is also running multiple processes, or multiple mongod processes, you might see contention for these resources. Also, be aware that the processes value (i.e. -u) refers to the combined number of distinct processes and sub-process threads. You can change ulimit settings by issuing a command in the following form: ulimit -n There are both “hard” and the “soft” ulimits that affect MongoDB’s performance. The “hard” ulimit refers to the maximum number of processes that a user can have active at any time. This is the ceiling: no non-root process can increase the “hard” ulimit. In contrast, the “soft” ulimit is the limit that is actually enforced for a session or process, but any process can increase it up to “hard” ulimit maximum. A low “soft” ulimit can cause can’t create new thread, closing connection errors if the number of connections grows too high. For this reason, it is extremely important to set both ulimit values to the recom- mended values. ulimit will modify both “hard” and “soft” values unless the -H or -S modifiers are specified when modifying limit values. For many distributions of Linux you can change values by substituting the -n option for any possible value in the output of ulimit -a. On OS X, use the launchctl limit command. See your operating system documentation for the precise procedure for changing system limits on running systems. After changing the ulimit settings, you must restart the process to take advantage of the modified settings. You can use the /proc file system to see the current limitations on a running process. 294 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 Depending on your system’s configuration, and default settings, any change to system limits made using ulimit may revert following system a system restart. Check your distribution and operating system documentation for more information. Note: SUSE Linux Enterprise Server 11 and potentially other versions of SLES and other SUSE distributions ship with virtual memory address space limited to 8GB by default. This must be adjusted in order to prevent virtual memory allocation failures as the database grows. The SLES packages for MongoDB adjust these limits in the default scripts, but you will need to make this change manually if you are using custom scripts and/or the tarball release rather than the SLES packages. Recommended ulimit Settings Every deployment may have unique requirements and settings; however, the following thresholds and settings are particularly important for mongod and mongos deployments: •-f (file size): unlimited •-t (cpu time): unlimited •-v (virtual memory): unlimited 122 •-n (open files): 64000 •-m (memory size): unlimited 1 123 •-u (processes/threads): 64000 Always remember to restart your mongod and mongos instances after changing the ulimit settings to ensure that the changes take effect. Linux distributions using Upstart For Linux distributions that use Upstart, you can specify limits within service scripts if you start mongod and/or mongos instances as Upstart services. You can do this by using limit stanzas124. Specify the Recommended ulimit Settings (page 295), as in the following example: limit fsize unlimited unlimited # (file size) limit cpu unlimited unlimited # (cpu time) limit as unlimited unlimited # (virtual memory size) limit nofile 64000 64000 # (open files) limit nproc 64000 64000 # (processes/threads) Each limit stanza sets the “soft” limit to the first value specified and the “hard” limit to the second. After changing limit stanzas, ensure that the changes take effect by restarting the application services, using the following form: restart 122 If you limit virtual or resident memory size on a system running MongoDB the operating system will refuse to honor additional allocation requests. 123 The -m parameter to ulimit has no effect on Linux systems with kernel versions more recent than 2.4.30. You may omit -m if you wish. 124http://upstart.ubuntu.com/wiki/Stanzas#limit 5.3. Administration Reference 295 MongoDB Documentation, Release 3.0.7 Linux distributions using systemd For Linux distributions that use systemd, you can specify limits within the [Service] sections of service scripts if you start mongod and/or mongos instances as systemd services. You can do this by using resource limit direc- tives125. Specify the Recommended ulimit Settings (page 295), as in the following example: [Service] # Other directives omitted # (file size) LimitFSIZE=infinity # (cpu time) LimitCPU=infinity # (virtual memory size) LimitAS=infinity # (open files) LimitNOFILE=64000 # (processes/threads) LimitNPROC=64000 Each systemd limit directive sets both the “hard” and “soft” limits to the value specified. After changing limit stanzas, ensure that the changes take effect by restarting the application services, using the following form: systemctl restart /proc File System Note: This section applies only to Linux operating systems. The /proc file-system stores the per-process limits in the file system object located at /proc//limits, where is the process’s PID or process identifier. You can use the following bash function to return the content of the limits object for a process or processes with a given name: return-limits(){ for process in $@; do process_pids=`ps -C $process -o pid --no-headers | cut -d"" -f 2` if [ -z $@]; then echo"[no $process running]" else for pid in $process_pids; do echo"[$process#$pid -- limits]" cat /proc/$pid/limits done fi done } You can copy and paste this function into a current shell session or load it as part of a script. Call the function with one the following invocations: 125http://www.freedesktop.org/software/systemd/man/systemd.exec.html#LimitCPU= 296 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 return-limits mongod return-limits mongos return-limits mongod mongos 5.3.2 System Collections Synopsis MongoDB stores system information in collections that use the .system.* namespace, which Mon- goDB reserves for internal use. Do not create collections that begin with system. MongoDB also stores some additional instance-local metadata in the local database (page 652), specifically for repli- cation purposes. Collections System collections include these collections stored in the admin database: admin.system.roles New in version 2.6. The admin.system.roles (page 297) collection stores custom roles that administrators create and assign to users to provide access to specific resources. admin.system.users Changed in version 2.6. The admin.system.users (page 297) collection stores the user’s authentication credentials as well as any roles assigned to the user. Users may define authorization roles in the admin.system.roles (page 297) collection. admin.system.version New in version 2.6. Stores the schema version of the user credential documents. System collections also include these collections stored directly in each database: .system.namespaces Deprecated since version 3.0: Access this data using listCollections. The .system.namespaces (page 297) collection contains information about all of the database’s collections. .system.indexes Deprecated since version 3.0: Access this data using listIndexes. The .system.indexes (page 297) collection lists all the indexes in the database. .system.profile The .system.profile (page 297) collection stores database profiling information. For in- formation on profiling, see Database Profiling (page 219). .system.js The .system.js (page 297) collection holds special JavaScript code for use in server side JavaScript (page 271). See Store a JavaScript Function on the Server (page 240) for more information. 5.3. Administration Reference 297 MongoDB Documentation, Release 3.0.7 5.3.3 Database Profiler Output The database profiler captures data information about read and write operations, cursor operations, and database com- mands. To configure the database profile and set the thresholds for capturing profile data, see the Analyze Performance of Database Operations (page 232) section. The database profiler writes data in the system.profile (page 297) collection, which is a capped collection. To view the profiler’s output, use normal MongoDB queries on the system.profile (page 297) collection. Note: Because the database profiler writes data to the system.profile (page 297) collection in a database, the profiler will profile some write activity, even for databases that are otherwise read-only. Example system.profile Document The documents in the system.profile (page 297) collection have the following form. This example document reflects an insert operation: { "op": "insert", "ns": "test.orders", "query":{ "_id":1, "cust_id": "A123", "amount": 500, "status": "A" }, "ninserted":1, "keyUpdates":0, "writeConflicts":0, "numYield":0, "locks":{ "Global":{ "acquireCount":{ "w": NumberLong(1) } }, "MMAPV1Journal":{ "acquireCount":{ "w": NumberLong(2) } }, "Database":{ "acquireCount":{ "w": NumberLong(1) } }, "Collection":{ "acquireCount":{ "W": NumberLong(1) } } }, , "millis":0, "execStats":{ }, "ts": ISODate("2012-12-10T19:31:28.977Z"), 298 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 "client": "127.0.0.1", "allUsers":[], "user":"" } Output Reference For any single operation, the documents created by the database profiler will include a subset of the following fields. The precise selection of fields in these documents depends on the type of operation. Note: For the output specific to the version of your MongoDB, refer to the appropriate version of the MongoDB Manual. system.profile.op The type of operation. The possible values are: •insert •query •update •remove •getmore •command system.profile.ns The namespace the operation targets. Namespaces in MongoDB take the form of the database, followed by a dot (.), followed by the name of the collection. system.profile.query The query document (page 98) used, or for an insert operation, the inserted document. If the document exceeds 50 kilobytes, the value is a string summary of the object. If the string summary exceeds 50 kilobytes, the string summary is truncated, denoted with an ellipsis (...) at the end of the string. Changed in version 3.0.4: For "getmore" (page 299) operations on cursors returned from a db.collection.find() or a db.collection.aggregate(), the query (page 299) field contains respectively the query predicate or the issued aggregate command document. For details on the aggregate command document, see the aggregate reference page. system.profile.command The command operation. If the command document exceeds 50 kilobytes, the value is a string summary of the object. If the string summary exceeds 50 kilobytes, the string summary is truncated, denoted with an ellipsis (...) at the end of the string. system.profile.updateobj The document passed in during an update (page 104) operation. If the document exceeds 50 kilo- bytes, the value is a string summary of the object. If the string summary exceeds 50 kilobytes, the string summary is truncated, denoted with an ellipsis (...) at the end of the string. system.profile.cursorid The ID of the cursor accessed by a query and getmore operations. system.profile.ntoreturn The number of documents the operation specified to return. For example, the profile command would return one document (a results document) so the ntoreturn (page 299) value would be 1. The limit(5) command would return five documents so the ntoreturn (page 299) value would be 5. 5.3. Administration Reference 299 MongoDB Documentation, Release 3.0.7 If the ntoreturn (page 299) value is 0, the command did not specify a number of documents to return, as would be the case with a simple find() command with no limit specified. system.profile.ntoskip The number of documents the skip() method specified to skip. system.profile.nscanned The number of documents that MongoDB scans in the index (page 481) in order to carry out the operation. In general, if nscanned (page 300) is much higher than nreturned (page 301), the database is scanning many objects to find the target objects. Consider creating an index to improve this. system.profile.nscannedObjects The number of documents that MongoDB scans from the collection in order to carry out the operation. system.profile.moved Changed in version 3.0.0: Only appears when using the MMAPv1 storage engine. This field appears with a value of true when an update operation moved one or more documents to a new location on disk. If the operation did not result in a move, this field does not appear. Operations that result in a move take more time than in-place updates and typically occur as a result of document growth. system.profile.nmoved Changed in version 3.0.0: Only appears when using the MMAPv1 storage engine. The number of documents the operation moved on disk. This field appears only if the operation resulted in a move. The field’s implicit value is zero, and the field is present only when non-zero. system.profile.scanAndOrder scanAndOrder (page 300) is a boolean that is true when a query cannot use the ordering in the index to return the requested sorted results; i.e. MongoDB must sort the documents after it receives the documents from a cursor. The field only appears when the value is true. system.profile.ndeleted The number of documents deleted by the operation. system.profile.ninserted The number of documents inserted by the operation. system.profile.nMatched New in version 2.6. The number of documents that match the system.profile.query (page 299) condition for the update operation. system.profile.nModified New in version 2.6. The number of documents modified by the update operation. system.profile.upsert A boolean that indicates the update operation’s upsert option value. Only appears if upsert is true. system.profile.keyUpdates The number of index (page 481) keys the update changed in the operation. Changing an index key carries a small performance cost because the database must remove the old key and inserts a new key into the B-tree index. system.profile.writeConflicts New in version 3.0.0. The number of conflicts encountered during the write operation; e.g. an update operation attempts to modify the same document as another update operation. See also write conflict. 300 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 system.profile.numYield The number of times the operation yielded to allow other operations to complete. Typically, operations yield when they need access to data that MongoDB has not yet fully read into memory. This allows other operations that have data in memory to complete while MongoDB reads in data for the yielding operation. For more information, see the FAQ on when operations yield (page 759). system.profile.locks New in version 3.0.0: locks (page 301) replaces the lockStats field. The system.profile.locks (page 301) provides information for various lock types and lock modes (page 758) held during the operation. The possible lock types are: •Global represents global lock. •MMAPV1Journal represents MMAPv1 storage engine specific lock to synchronize journal writes; for non-MMAPv1 storage engines, the mode for MMAPV1Journal is empty. •Database represents database lock. •Collection represents collection lock. •Metadata represents metadata lock. •oplog represents lock on the oplog. The possible locking modes for the lock types are as follows: •R represents Shared (S) lock. •W represents Exclusive (X) lock. •r represents Intent Shared (IS) lock. •w represents Intent Exclusive (IX) lock. The returned lock information for the various lock types include: system.profile.locks.acquireCount Number of times the operation acquired the lock in the specified mode. system.profile.locks.acquireWaitCount Number of times the operation had to wait for the acquireCount (page 301) lock acquisitions because the locks were held in a conflicting mode. acquireWaitCount (page 301) is less than or equal to acquireCount (page 301). system.profile.locks.timeAcquiringMicros Cumulative time in microseconds that the operation had to wait to acquire the locks. timeAcquiringMicros (page 301) divided by acquireWaitCount (page 301) gives an approxi- mate average wait time for the particular lock mode. system.profile.locks.deadlockCount Number of times the operation encountered deadlocks while waiting for lock acquisitions. For more information on lock modes, see What type of locking does MongoDB use? (page 758). system.profile.nreturned The number of documents returned by the operation. system.profile.responseLength The length in bytes of the operation’s result document. A large responseLength (page 301) can affect performance. To limit the size of the result document for a query operation, you can use any of the following: •Projections (page 109) 5.3. Administration Reference 301 MongoDB Documentation, Release 3.0.7 •The limit() method •The batchSize() method Note: When MongoDB writes query profile information to the log, the responseLength (page 301) value is in a field named reslen. system.profile.millis The time in milliseconds from the perspective of the mongod from the beginning of the operation to the end of the operation. system.profile.execStats Changed in version 3.0. A document that contains the execution statistics of the query operation. For other operations, the value is an empty document. The system.profile.execStats (page 302) presents the statistics as a tree; each node provides the statistics for the operation executed during that stage of the query operation. Note: The following fields list for execStats (page 302) is not meant to be exhaustive as the returned fields vary per stage. system.profile.execStats.stage New in version 3.0: stage (page 302) replaces the type field. The descriptive name for the operation performed as part of the query execution; e.g. •COLLSCAN for a collection scan •IXSCAN for scanning index keys •FETCH for retrieving documents system.profile.execStats.inputStages New in version 3.0: inputStages (page 302) replaces the children field. An array that contains statistics for the operations that are the input stages of the current stage. system.profile.ts The timestamp of the operation. system.profile.client The IP address or hostname of the client connection where the operation originates. For some operations, such as db.eval(), the client is 0.0.0.0:0 instead of an actual client. system.profile.allUsers An array of authenticated user information (user name and database) for the session. See also Client Authenti- cation (page 328). system.profile.user The authenticated user who ran the operation. If the operation was not run by an authenticated user, this field’s value is an empty string. 5.3.4 Server Status Output This document provides a quick overview and example of the serverStatus command. The helper db.serverStatus() in the mongo shell provides access to this output. For full documentation of the content of this output, see https://docs.mongodb.org/manual/reference/command/serverStatus. 302 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 Note: The output fields vary depending on the version of MongoDB, underlying operating system platform, the storage engine, and the kind of node, including mongos, mongod or replica set member. For the serverStatus output specific to the version of your MongoDB, refer to the appropriate version of the MongoDB Manual. Changed in version 3.0: The server status output no longer includes the workingSet, indexCounters, and recordStats sections. The server-status-instance-information section displays information regarding the specific mongod and mongos and its state. "host": "", "version": "", "process": "", "pid":, "uptime":, "uptimeMillis":, "uptimeEstimate":, "localTime": ISODate(""), The server-status-asserts document reports the number of assertions or errors produced by the server: "asserts":{ "regular":, "warning":, "msg":, "user":, "rollovers": }, The server-status-backgroundflushing document reports on the process MongoDB uses to write data to disk. The server-status-backgroundflushing information only returns for instances that use the MMAPv1 storage engine: "backgroundFlushing":{ "flushes":, "total_ms":, "average_ms":, "last_ms":, "last_finished": ISODate("") }, The server-status-connections field reports on MongoDB’s current number of open incoming connections: New in version 2.4: The totalCreated field. "connections":{ "current":, "available":, "totalCreated": NumberLong() }, The server-status-cursors document reports on current cursor use and state: "cursors":{ "note": "deprecated, use server status metrics", "clientCursors_size":, "totalOpen":, "pinned":, "totalNoTimeout":, "timedOut": }, 5.3. Administration Reference 303 MongoDB Documentation, Release 3.0.7 The server-status-journaling document reports on data that reflect this mongod instance’s journaling-related opera- tions and performance during a journal group commit interval (page 240). The server-status-journaling information only returns for instances that use the MMAPv1 storage engine and have journaling enabled: "dur":{ "commits":, "journaledMB":, "writeToDataFilesMB":, "compression":, "commitsInWriteLock":, "earlyCommits":, "timeMs":{ "dt":, "prepLogBuffer":, "writeToJournal":, "writeToDataFiles":, "remapPrivateView":, "commits":, "commitsInWriteLock": } }, The fields in the server-status-extra-info document provide platform specific information. The following example block is from a Linux-based system: "extra_info":{ "note": "fields vary by platform", "heap_usage_bytes":, "page_faults": }, The server-status-globallock field reports on MongoDB’s global system lock. In most cases the locks document provides more fine grained data that reflects lock use: "globalLock":{ "totalTime":, "currentQueue":{ "total":, "readers":, "writers": }, "activeClients":{ "total":, "readers":, "writers": } }, The server-status-locks section reports statistics for each lock type and mode: "locks":{ "Global":{ "acquireCount":{ "r": NumberLong(), "w": NumberLong(), "R": NumberLong(), "W": NumberLong() }, "acquireWaitCount":{ "r": NumberLong(), 304 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 "w": NumberLong(), "R": NumberLong(), "W": NumberLong() }, "timeAcquiringMicros":{ "r": NumberLong(), "w": NumberLong(), "R": NumberLong(), "W": NumberLong() }, "deadlockCount":{ "r": NumberLong(), "w": NumberLong(), "R": NumberLong(), "W": NumberLong() } }, "MMAPV1Journal":{ "acquireCount":{ "r": NumberLong(), "w": NumberLong(), "R": NumberLong(), "W": NumberLong() }, "acquireWaitCount":{ "r": NumberLong(), "w": NumberLong(), "R": NumberLong(), "W": NumberLong() }, "timeAcquiringMicros":{ "r": NumberLong(), "w": NumberLong(), "R": NumberLong(), "W": NumberLong() }, "deadlockCount":{ "r": NumberLong(), "w": NumberLong(), "R": NumberLong(), "W": NumberLong() } }, "Database":{ "acquireCount":{ "r": NumberLong(), "w": NumberLong(), "R": NumberLong(), "W": NumberLong() }, "acquireWaitCount":{ "r": NumberLong(), "w": NumberLong(), "R": NumberLong(), "W": NumberLong() }, "timeAcquiringMicros":{ "r": NumberLong(), 5.3. Administration Reference 305 MongoDB Documentation, Release 3.0.7 "w": NumberLong(), "R": NumberLong(), "W": NumberLong() }, "deadlockCount":{ "r": NumberLong(), "w": NumberLong(), "R": NumberLong(), "W": NumberLong() } }, "Collection":{ "acquireCount":{ "r": NumberLong(), "w": NumberLong(), "R": NumberLong(), "W": NumberLong() }, "acquireWaitCount":{ "r": NumberLong(), "w": NumberLong(), "R": NumberLong(), "W": NumberLong() }, "timeAcquiringMicros":{ "r": NumberLong(), "w": NumberLong(), "R": NumberLong(), "W": NumberLong() }, "deadlockCount":{ "r": NumberLong(), "w": NumberLong(), "R": NumberLong(), "W": NumberLong() } }, "Metadata":{ "acquireCount":{ "r": NumberLong(), "w": NumberLong(), "R": NumberLong(), "W": NumberLong() }, "acquireWaitCount":{ "r": NumberLong(), "w": NumberLong(), "R": NumberLong(), "W": NumberLong() }, "timeAcquiringMicros":{ "r": NumberLong(), "w": NumberLong(), "R": NumberLong(), "W": NumberLong() }, "deadlockCount":{ "r": NumberLong(), 306 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 "w": NumberLong(), "R": NumberLong(), "W": NumberLong() } }, "oplog":{ "acquireCount":{ "r": NumberLong(), "w": NumberLong(), "R": NumberLong(), "W": NumberLong() }, "acquireWaitCount":{ "r": NumberLong(), "w": NumberLong(), "R": NumberLong(), "W": NumberLong() }, "timeAcquiringMicros":{ "r": NumberLong(), "w": NumberLong(), "R": NumberLong(), "W": NumberLong() }, "deadlockCount":{ "r": NumberLong(), "w": NumberLong(), "R": NumberLong(), "W": NumberLong() } } }, The server-status-network document reports on network use and state: "network":{ "bytesIn":, "bytesOut":, "numRequests": }, The server-status-opcounters document reports the number of operations this MongoDB instance has processed: "opcounters":{ "insert":, "query":, "update":, "delete":, "getmore":, "command": }, The server-status-opcounters-repl document reports the number of replicated operations: "opcountersRepl":{ "insert":, "query":, "update":, "delete":, 5.3. Administration Reference 307 MongoDB Documentation, Release 3.0.7 "getmore":, "command": }, The server-status-storage-engine document reports details about the current storage engine: "storageEngine":{ "name": }, The server-status-writebacksqueued document reports the number of writebacks: "writeBacksQueued":, The server-status-memory field reports on MongoDB’s current memory use: "mem":{ "bits":, "resident":, "virtual":, "supported":< boolean>, "mapped":, "mappedWithJournal":, "note": "not all mem info support on this platform" }, The server-status-repl document reports on the state of replication and the replica set. This document only appears for replica sets. "repl":{ "setName":, "setVersion":, "ismaster":< boolean>, "secondary":< boolean>, "hosts":[ , , ], "primary":, "me":, "electionId": ObjectId(""), "rbid":, "slaves":[ { "rid":, "optime":, "host":, "memberID": } ], }, The server-status-range-deleter document reports the number of operations this MongoDB instance has processed. The rangeDeleter document is only present in the output of serverStatus when explicitly enabled. "rangeDeleter":{ "lastDeleteStats":[ { "deletedDocs": NumberLong(), 308 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 "queueStart":, "queueEnd":, "deleteStart":, "deleteEnd":, "waitForReplStart":, "waitForReplEnd": } ] } The server-status-security document reports details about the security features and use: "security":{ "SSLServerSubjectName":, "SSLServerHasCertificateAuthority":< boolean>, "SSLServerCertificateExpirationDate": }, The server-status-metrics document contains a number of operational metrics that are useful for monitoring the state and workload of a mongod instance. New in version 2.4. Changed in version 2.6: Added the cursor document. "metrics":{ "command":{ "":{ "failed":, "total": } }, "cursor":{ "timedOut": NumberLong(), "open":{ "noTimeout": NumberLong(), "pinned": NumberLong(), "multiTarget": NumberLong(), "singleTarget": NumberLong(), "total": NumberLong(), } }, "document":{ "deleted": NumberLong(), "inserted": NumberLong(), "returned": NumberLong(), "updated": NumberLong() }, "getLastError":{ "wtime":{ "num":, "totalMillis": }, "wtimeouts": NumberLong() }, "operation":{ "fastmod": NumberLong(), "idhack": NumberLong(), "scanAndOrder": NumberLong() }, 5.3. Administration Reference 309 MongoDB Documentation, Release 3.0.7 "queryExecutor":{ "scanned": NumberLong() }, "record":{ "moves": NumberLong() }, "repl":{ "apply":{ "batches":{ "num":, "totalMillis": }, "ops": NumberLong() }, "buffer":{ "count": NumberLong(), "maxSizeBytes":, "sizeBytes": NumberLong() }, "network":{ "bytes": NumberLong(), "getmores":{ "num":, "totalMillis": }, "ops": NumberLong(), "readersCreated": NumberLong() }, "oplog":{ "insert":{ "num":, "totalMillis": }, "insertBytes": NumberLong() }, "preload":{ "docs":{ "num":, "totalMillis": }, "indexes":{ "num":, "totalMillis": } } }, "storage":{ "freelist":{ "search":{ "bucketExhausted":, "requests":, "scanned": } } }, "ttl":{ "deletedDocuments": NumberLong(), "passes": NumberLong() 310 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 } }, The server-status-wiredTiger statistics section reports details about the WiredTiger statistics: New in version 3.0: server-status-wiredTiger statistics section. This section appears only for the WiredTiger storage engine. "wiredTiger":{ "uri": "statistics:", "LSM":{ "sleep for LSM checkpoint throttle":, "sleep for LSM merge throttle":, "rows merged in an LSM tree":, "application work units currently queued":, "merge work units currently queued":, "tree queue hit maximum":, "switch work units currently queued":, "tree maintenance operations scheduled":, "tree maintenance operations discarded":, "tree maintenance operations executed": }, "async":{ "number of allocation state races":, "number of operation slots viewed for allocation":, "current work queue length":, "number of flush calls":, "number of times operation allocation failed":, "maximum work queue length":, "number of times worker found no work":, "total allocations":, "total compact calls":, "total insert calls":, "total remove calls":, "total search calls":, "total update calls": }, "block-manager":{ "mapped bytes read":, "bytes read":, "bytes written":, "mapped blocks read":, "blocks pre-loaded":, "blocks read":, "blocks written": }, "cache":{ "tracked dirty bytes in the cache":, "bytes currently in the cache":, "maximum bytes configured":, "bytes read into cache":, "bytes written from cache":, "pages evicted by application threads":, "checkpoint blocked page eviction":, "unmodified pages evicted":, "page split during eviction deepened the tree":, "modified pages evicted":, "pages selected for eviction unable to be evicted":, "pages evicted because they exceeded the in-memory maximum":, 5.3. Administration Reference 311 MongoDB Documentation, Release 3.0.7 "pages evicted because they had chains of deleted items":, "failed eviction of pages that exceeded the in-memory maximum":, "hazard pointer blocked page eviction":, "internal pages evicted":, "maximum page size at eviction":, "eviction server candidate queue empty when topping up":, "eviction server candidate queue not empty when topping up":, "eviction server evicting pages":, "eviction server populating queue, but not evicting pages":, "eviction server unable to reach eviction goal":, "pages split during eviction":, "pages walked for eviction":, "eviction worker thread evicting pages":, "in-memory page splits":, "percentage overhead":, "tracked dirty pages in the cache":, "pages currently held in the cache":, "pages read into cache":, "pages written from cache": }, "connection":{ "pthread mutex condition wait calls":, "files currently open":, "memory allocations":, "memory frees":, "memory re-allocations":, "total read I/Os":, "pthread mutex shared lock read-lock calls":, "pthread mutex shared lock write-lock calls":, "total write I/Os": }, "cursor":{ "cursor create calls":, "cursor insert calls":, "cursor next calls":, "cursor prev calls":, "cursor remove calls":, "cursor reset calls":, "cursor search calls":, "cursor search near calls":, "cursor update calls": }, "data-handle":{ "connection dhandles swept":, "connection candidate referenced":, "connection sweeps":, "connection time-of-death sets":, "session dhandles swept":, "session sweep attempts": }, "log":{ "log buffer size increases":, "total log buffer size":, "log bytes of payload data":, "log bytes written":, "yields waiting for previous log file close":, "total size of compressed records":, "total in-memory size of compressed records":, 312 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 "log records too small to compress":, "log records not compressed":, "log records compressed":, "maximum log file size":, "pre-allocated log files prepared":, "number of pre-allocated log files to create":, "pre-allocated log files used":, "log read operations":, "log release advances write LSN":, "records processed by log scan":, "log scan records requiring two reads":, "log scan operations":, "consolidated slot closures":, "logging bytes consolidated":, "consolidated slot joins":, "consolidated slot join races":, "slots selected for switching that were unavailable":, "record size exceeded maximum":, "failed to find a slot large enough for record":, "consolidated slot join transitions":, "log sync operations":, "log sync_dir operations":, "log server thread advances write LSN":, "log write operations": }, "reconciliation":{ "page reconciliation calls":, "page reconciliation calls for eviction":, "split bytes currently awaiting free":, "split objects currently awaiting free": }, "session":{ "open cursor count":, "open session count": }, "thread-yield":{ "page acquire busy blocked":, "page acquire eviction blocked":, "page acquire locked blocked":, "page acquire read blocked":, "page acquire time sleeping (usecs)": }, "transaction":{ "transaction begins":, "transaction checkpoints":, "transaction checkpoint currently running":, "transaction checkpoint max time (msecs)":, "transaction checkpoint min time (msecs)":, "transaction checkpoint most recent time (msecs)":, "transaction checkpoint total time (msecs)":, "transactions committed":, "transaction failures due to cache overflow":, "transaction range of IDs currently pinned":, "transactions rolled back": }, "concurrentTransactions":{ "write":{ "out":, 5.3. Administration Reference 313 MongoDB Documentation, Release 3.0.7 "available":, "totalTickets": }, "read":{ "out":, "available":, "totalTickets": } } }, The final ok field holds the return status for the serverStatus command: "ok":1 5.3.5 Journaling Mechanics When running with journaling, MongoDB stores and applies write operations (page 75) in memory and in the on- disk journal before the changes are present in the data files on disk. Writes to the journal are atomic, ensuring the consistency of the on-disk journal files. This document discusses the implementation and mechanics of journaling in MongoDB systems. See Manage Journaling (page 238) for information on configuring, tuning, and managing journaling. Journal Files With journaling enabled, MongoDB creates a journal subdirectory within the directory defined by dbPath, which is /data/db by default. The journal directory holds journal files, which contain write-ahead redo logs. The directory also holds a last-sequence-number file. A clean shutdown removes all the files in the journal directory. A dirty shut- down (crash) leaves files in the journal directory; these are used to automatically recover the database to a consistent state when the mongod process is restarted. Journal files are append-only files and have file names prefixed with j._. When a journal file holds 1 gigabyte of data, MongoDB creates a new journal file. Once MongoDB applies all the write operations in a particular journal file to the database data files, it deletes the file, as it is no longer needed for recovery purposes. Unless you write many bytes of data per second, the journal directory should contain only two or three journal files. You can use the storage.smallFiles run time option when starting mongod to limit the size of each journal file to 128 megabytes, if you prefer. To speed the frequent sequential writes that occur to the current journal file, you can ensure that the journal directory is on a different filesystem from the database data files. Important: If you place the journal on a different filesystem from your data files you cannot use a filesystem snapshot alone to capture valid backups of a dbPath directory. In this case, use fsyncLock() to ensure that database files are consistent before the snapshot and fsyncUnlock() once the snapshot is complete. Note: Depending on your filesystem, you might experience a preallocation lag the first time you start a mongod instance with journaling enabled. MongoDB may preallocate journal files if the mongod process determines that it is more efficient to preallocate journal files than create new journal files as needed. The amount of time required to pre-allocate lag might last several minutes, during which you will not be able to connect to the database. This is a one-time preallocation and does not occur with future invocations. To avoid preallocation lag, see Avoid Preallocation Lag (page 239). 314 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 Storage Views used in Journaling With journaling, MongoDB’s storage layer has two internal views of the data set. The shared view stores modified data for upload to the MongoDB data files. The shared view is the only view with direct access to the MongoDB data files. When running with journaling, mongod asks the operating system to map your existing on-disk data files to the shared view virtual memory view. The operating system maps the files but does not load them. MongoDB later loads data files into the shared view as needed. The private view stores data for use with read operations (page 62). The private view is the first place MongoDB applies new write operations (page 75). Upon a journal commit, MongoDB copies the changes made in the private view to the shared view, where they are then available for uploading to the database data files. The journal is an on-disk view that stores new write operations after MongoDB applies the operation to the private view but before applying them to the data files. The journal provides durability. If the mongod instance were to crash without having applied the writes to the data files, the journal could replay the writes to the shared view for eventual upload to the data files. How Journaling Records Write Operations MongoDB copies the write operations to the journal in batches called group commits. These “group commits” help minimize the performance impact of journaling, since a group commit must block all writers during the commit. See commitIntervalMs for information on the default commit interval. Journaling stores raw operations that allow MongoDB to reconstruct the following: • document insertion/updates • index modifications • metadata changes to the namespace files • creation and dropping of databases and their associated data files As write operations (page 75) occur, MongoDB writes the data to the private view in RAM and then copies the write operations in batches to the journal. The journal stores the operations on disk to ensure durability. Each journal entry describes the bytes the write operation changed in the data files. MongoDB next applies the journal’s write operations to the shared view. At this point, the shared view becomes inconsistent with the data files. At default intervals of 60 seconds, MongoDB asks the operating system to flush the shared view to disk. This brings the data files up-to-date with the latest write operations. The operating system may choose to flush the shared view to disk at a higher frequency than 60 seconds, particularly if the system is low on free memory. When MongoDB flushes write operations to the data files, MongoDB notes which journal writes have been flushed. Once a journal file contains only flushed writes, it is no longer needed for recovery, and MongoDB either deletes it or recycles it for a new journal file. As part of journaling, MongoDB routinely asks the operating system to remap the shared view to the private view, in order to save physical RAM. Upon a new remapping, the operating system knows that physical memory pages can be shared between the shared view and the private view mappings. Note: The interaction between the shared view and the on-disk data files is similar to how MongoDB works without journaling, which is that MongoDB asks the operating system to flush in-memory changes back to the data files every 60 seconds. 5.3. Administration Reference 315 MongoDB Documentation, Release 3.0.7 5.3.6 Exit Codes and Statuses MongoDB will return one of the following codes and statuses when exiting. Use this guide to interpret logs and when troubleshooting issues with mongod and mongos instances. 0 Returned by MongoDB applications upon successful exit. 2 The specified options are in error or are incompatible with other options. 3 Returned by mongod if there is a mismatch between hostnames specified on the command line and in the local.sources (page 654) collection. mongod may also return this status if oplog collection in the local database is not readable. 4 The version of the database is different from the version supported by the mongod (or mongod.exe) instance. The instance exits cleanly. Restart mongod with the --upgrade option to upgrade the database to the version supported by this mongod instance. 5 Returned by mongod if a moveChunk operation fails to confirm a commit. 12 Returned by the mongod.exe process on Windows when it receives a Control-C, Close, Break or Shutdown event. 14 Returned by MongoDB applications which encounter an unrecoverable error, an uncaught exception or uncaught signal. The system exits without performing a clean shut down. 20 Message: ERROR: wsastartup failed Returned by MongoDB applications on Windows following an error in the WSAStartup function. Message: NT Service Error Returned by MongoDB applications for Windows due to failures installing, starting or removing the NT Service for the application. 45 Returned when a MongoDB application cannot open a file or cannot obtain a lock on a file. 47 MongoDB applications exit cleanly following a large clock skew (32768 milliseconds) event. 48 mongod exits cleanly if the server socket closes. The server socket is on port 27017 by default, or as specified to the --port run-time option. 49 Returned by mongod.exe or mongos.exe on Windows when either receives a shutdown message from the Windows Service Control Manager. 100 Returned by mongod when the process throws an uncaught exception. 316 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 5.4 Production Checklist The following checklists provide recommendations that will help you avoid issues in your production MongoDB deployment. 5.4.1 Operations Checklist The following checklist, along with the Development (page 320) list, provides recommendations to help you avoid issues in your production MongoDB deployment. Filesystem • Align your disk partitions with your RAID configuration. • Avoid using NFS drives for your dbPath. Using NFS drives can result in degraded and unstable performance. See: Remote Filesystems (page 205) for more information. – VMWare users should use VMWare virtual drives over NFS. • Linux/Unix: format your drives into XFS or EXT4. If possible, use XFS as it generally performs better with MongoDB. – With the WiredTiger storage engine, use of XFS is strongly recommended to avoid performance issues found when using EXT4 with WiredTiger. – If using RAID, you may need to configure XFS with your RAID geometry. • Windows: use the NTFS file system. Do not use any FAT file system (i.e. FAT 16/32/exFAT). Replication • Verify that all non-hidden replica set members are identically provisioned in terms of their RAM, CPU, disk, network setup, etc. • Configure the oplog size (page 628) to suit your use case: – The replication oplog window should cover normal maintenance and downtime windows to avoid the need for a full resync. – The replication oplog window should cover the time needed to restore a replica set member, either by an initial sync or by restoring from the last backup. • Ensure that your replica set includes at least three data-bearing nodes with w:majority write concern (page 133). Three data-bearing nodes are required for replica set-wide data durability. • Use hostnames when configuring replica set members, rather than IP addresses. • Ensure full bidirectional network connectivity between all mongod instances. • Ensure that each host can resolve itself. • Ensure that your replica set contains an odd number of voting members. • Ensure that mongod instances have 0 or 1 votes. • For high availability, deploy your replica set into a minimum of three data centers. 5.4. Production Checklist 317 MongoDB Documentation, Release 3.0.7 Sharding • Place your config servers (page 670) on dedicated hardware for optimal performance in large clusters. Ensure that the hardware has enough RAM to hold the data files entirely in memory and that it has dedicated storage. • Use NTP to synchronize the clocks on all components of your sharded cluster. • Ensure full bidirectional network connectivity between mongod, mongos and config servers. • Use CNAMEs to identify your config servers to the cluster so that you can rename and renumber your config servers without downtime. Journaling: MMAPv1 Storage Engine • Ensure that all instances use journaling (page 314). • Place the journal on its own low-latency disk for write-intensive workloads. Note that this will affect snapshot- style backups as the files constituting the state of the database will reside on separate volumes. Hardware • Use RAID10 and SSD drives for optimal performance. • SAN and Virtualization: – Ensure that each mongod has provisioned IOPS for its dbPath, or has its own physical drive or LUN. – Avoid dynamic memory features, such as memory ballooning, when running in virtual environments. – Avoid placing all replica set members on the same SAN, as the SAN can be a single point of failure. Deployments to Cloud Hardware • Windows Azure: Adjust the TCP keepalive (tcp_keepalive_time) to 100-120. The default TTL for TCP connections on Windows Azure load balancers is too slow for MongoDB’s connection pooling behavior. • Use MongoDB version 2.6.4 or later on systems with high-latency storage, such as Windows Azure, as these versions include performance improvements for those systems. See: Azure Deployment Recommendations126 for more information. Operating System Configuration Linux • Turn off transparent hugepages and defrag. See Transparent Huge Pages Settings (page 225) for more informa- tion. • Adjust the readahead settings (page 207) on the devices storing your database files to suit your use case. If your working set is bigger that the available RAM, and the document access pattern is random, consider lowering the readahead to 32 or 16. Evaluate different settings to find an optimal value that maximizes the resident memory and lowers the number of page faults. • Use the noop or deadline disk schedulers for SSD drives. • Use the noop disk scheduler for virtualized drives in guest VMs. 126https://docs.mongodb.org/ecosystem/platforms/windows-azure 318 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 • Disable NUMA or set vm.zone_reclaim_mode to 0 and run mongod instances with node interleaving. See: MongoDB and NUMA Hardware (page 204) for more information. • Adjust the ulimit values on your hardware to suit your use case. If multiple mongod or mongos instances are running under the same user, scale the ulimit values accordingly. See: UNIX ulimit Settings (page 293) for more information. • Use noatime for the dbPath mount point. • Configure sufficient file handles (fs.file-max), kernel pid limit (kernel.pid_max), and maximum threads per process (kernel.threads-max) for your deployment. For large systems, values of 98000, 32768, and 64000 are a good starting point. • Ensure that your system has swap space configured. Refer to your operating system’s documentation for details on appropriate sizing. • Ensure that the system default TCP keepalive is set correctly. A value of 300 often provides better performance for replica sets and sharded clusters. See: Does TCP keepalive time affect MongoDB Deployments? (page 779) in the Frequently Asked Questions for more information. Windows • Consider disabling NTFS “last access time” updates. This is analogous to disabling atime on Unix-like sys- tems. Backups • Schedule periodic tests of your back up and restore process to have time estimates on hand, and to verify its functionality. Monitoring • Use MongoDB Cloud Manager127 or Ops Manager, an on-premise solution available in MongoDB Enterprise Advanced128 or another monitoring system to monitor key database metrics and set up alerts for them. Include alerts for the following metrics: – lock percent (for the MMAPv1 storage engine (page 93)) – replication lag – replication oplog window – assertions – queues – page faults • Monitor hardware statistics for your servers. In particular, pay attention to the disk use, CPU, and available disk space. In the absence of disk space monitoring, or as a precaution: – Create a dummy 4GB file on the storage.dbPath drive to ensure available space if the disk becomes full. 127https://cloud.mongodb.com/?jmp=docs 128https://www.mongodb.com/products/mongodb-enterprise-advanced?jmp=docs 5.4. Production Checklist 319 MongoDB Documentation, Release 3.0.7 – A combination of cron+df can alert when disk space hits a high-water mark, if no other monitoring tool is available. Load Balancing • Configure load balancers to enable “sticky sessions” or “client affinity”, with a sufficient timeout for existing connections. • Avoid placing load balancers between MongoDB cluster or replica set components. 5.4.2 Development The following checklist, along with the Operations Checklist (page 317), provides recommendations to help you avoid issues in your production MongoDB deployment. Data Durability • Ensure that your replica set includes at least three data-bearing nodes with w:majority write concern (page 133). Three data-bearing nodes are required for replica-set wide data durability. • Ensure that all instances use journaling (page 314). Schema Design • Ensure that your schema design does not rely on indexed arrays that grow in length without bound. Typically, best performance can be achieved when such indexed arrays have fewer than 1000 elements. Replication • Do not use secondary reads to scale overall read throughput. See: Can I use more replica nodes to scale129 for an overview of read scaling. For information about secondary reads, see: Read Preference (page 588). Sharding • Ensure that your shard key distributes the load evenly on your shards. See: Considerations for Selecting Shard Keys (page 694) for more information. • Use targeted queries (page 678) for workloads that need to scale with the number of shards. • Always read from primary nodes for non-targeted queries that may be sensitive to stale or orphaned data130. • Pre-split and manually balance chunks (page 722) when inserting large data sets into a new non-hashed sharded collection. Pre-splitting and manually balancing enables the insert load to be distributed among the shards, increasing performance for the initial load. 129http://askasya.com/post/canreplicashelpscaling 130http://blog.mongodb.org/post/74730554385/background-indexing-on-secondaries-and-orphaned 320 Chapter 5. Administration MongoDB Documentation, Release 3.0.7 Drivers • Make use of connection pooling. Most MongoDB drivers support connection pooling. Adjust the connection pool size to suit your use case, beginning at 110-115% of the typical number of concurrent database requests. • Ensure that your applications handle transient write and read errors during replica set elections. • Ensure that your applications handle failed requests and retry them if applicable. Drivers do not automatically retry failed requests. • Use exponential backoff logic for database request retries. • Use cursor.maxTimeMS() for reads and wtimeout (page 134) for writes if you need to cap execution time for database operations. 5.4.3 Additional Resources • MongoDB Production Readiness Consulting Package131 • MongoDB Ops Optimization Consulting Package132 131https://www.mongodb.com/products/consulting?jmp=docs#s_product_readiness 132https://www.mongodb.com/products/consulting?jmp=docs#ops_optimization 5.4. Production Checklist 321 MongoDB Documentation, Release 3.0.7 322 Chapter 5. Administration CHAPTER 6 Security This section outlines basic security and risk management strategies and access control. The included tutorials outline specific tasks for configuring firewalls, authentication, and system privileges. Security Introduction (page 323) A high-level introduction to security and MongoDB deployments. Network Security (page 326) Documentation on authentication, authorization, and encryption in MongoDB. Access Control (page 334) Documentation on users and roles in MongoDB. Auditing (page 337) Documentation on the auditing feature available with MongoDB Enterprise. External Environment (page 337) Discusses potential risks related to MongoDB’s JavaScript, HTTP and REST in- terfaces, including strategies to control those risks. Security Tutorials (page 339) Tutorials for enabling and configuring security features for MongoDB. Network Security Tutorials (page 340) Ensure that the underlying network configuration supports a secure op- erating environment for MongoDB deployments, and appropriately limits access to MongoDB deploy- ments. Authentication Tutorials (page 360) These tutorials describe procedures relevant for the configuration, opera- tion, and maintenance of MongoDB’s access control system. User and Role Management Tutorials (page 387) MongoDB’s access control system provides a flexible role- based access control system that you can use to limit access to MongoDB deployments. The tutorials in this section describe the configuration an setup of the authorization system. Continue reading from Security Tutorials (page 339) for additional tutorials that address the use and management of secure MongoDB deployments. Create a Vulnerability Report (page 403) Report a vulnerability in MongoDB. Security Reference (page 405) Reference for security related functions. Security Checklist (page 432) A high level overview of global security consideration for administrators of MongoDB deployments. Use this checklist if you are new to deploying MongoDB in production and want to implement high quality security practices. 6.1 Security Introduction Maintaining a secure MongoDB deployment requires administrators to implement controls to ensure that users and applications have access to only the data that they require. MongoDB provides features that allow administrators to implement these controls and restrictions for any MongoDB deployment. 323 MongoDB Documentation, Release 3.0.7 If you are already familiar with security and MongoDB security practices, consider the Security Checklist (page 432) for a collection of recommended actions to protect a MongoDB deployment. 6.1.1 Authentication Before gaining access to a system all clients should identify themselves to MongoDB. This ensures that no client can access the data stored in MongoDB without being explicitly allowed. MongoDB supports a number of authentication mechanisms (page 326) that clients can use to verify their identity. MongoDB supports two mechanisms: a password-based challenge and response protocol and x.509 certificates. Ad- ditionally, MongoDB Enterprise1 also provides support for LDAP proxy authentication (page 328) and Kerberos au- thentication (page 328). See Authentication (page 326) for more information. 6.1.2 Role Based Access Control Access control, i.e. authorization (page 334), determines a user’s access to resources and operations. Clients should only be able to perform the operations required to fulfill their approved functions. This is the “principle of least privilege” and limits the potential risk of a compromised application. MongoDB’s role-based access control system allows administrators to control all access and ensure that all granted access applies as narrowly as possible. MongoDB does not enable authorization by default. When you enable autho- rization (page 334), MongoDB will require authentication for all connections. When authorization is enabled, MongoDB controls a user’s access through the roles assigned to the user. A role consists of a set of privileges, where a privilege consists of actions, or a set of operations, and a resource upon which the actions are allowed. Users may have one or more role that describes their access. MongoDB provides several built-in roles (page 406) and users can construct specific roles tailored to clients’ actual requirements. See Authorization (page 334) for more information. 6.1.3 Auditing Auditing provides administrators with the ability to verify that the implemented security policies are controlling activ- ity in the system. Retaining audit information ensures that administrators have enough information to perform forensic investigations and comply with regulations and polices that require audit data. See Auditing (page 337) for more information. 6.1.4 Encryption Transport Encryption You can use TLS/SSL (Transport Layer Security/Secure Sockets Layer) to encrypt all of MongoDB’s network traffic. TLS/SSL ensures that MongoDB network traffic is only readable by the intended client. See Configure mongod and mongos for TLS/SSL (page 347) for more information. 1http://www.mongodb.com/products/mongodb-enterprise?jmp=docs 324 Chapter 6. Security MongoDB Documentation, Release 3.0.7 Encryption at Rest There are two broad classes of approaches to encrypting data at rest with MongoDB: Application Level Encryption (page 325) and Storage Encryption (page 325). You can use these solutions together or independently. Application Level Encryption provides encryption on a per-field or per-document basis within the application layer. To encrypt document or field level data, write custom encryption and decryption routines or use a commercial solution such as the Vormetric Data Security Platform2. Storage Encryption encrypts all MongoDB data on the storage or operating system to ensure that only authorized processes can access protected data. A number of third-party libraries can integrate with the operating system to provide transparent disk-level encryption. For example: • Linux Unified Key Setup (LUKS) LUKS is available for most Linux distributions. For configuration expla- nation, see the LUKS documentation from Red Hat3. • IBM Guardium Data Encryption IBM Guardium Data Encryption4 provides support for disk-level encryp- tion for Linux and Windows operating systems. • Vormetric Data Security Platform The Vormetric Data Security Platform5 provides disk and file-level en- cryption in addition to application level encryption. • Bitlocker Drive Encryption Bitlocker Drive Encryption6 is a feature available on Windows Server 2008 and 2012 that provides disk encryption. Properly configured disk encryption, when used alongside good security policies that protect relevant accounts, pass- words, and encryption keys, can help ensure compliance with standards, including HIPAA, PCI-DSS, and FERPA. 6.1.5 Hardening Deployments and Environments In addition to implementing controls within MongoDB, you should also place controls around MongoDB to reduce the risk exposure of the entire MongoDB system. This is a defense in depth strategy. Hardening MongoDB extends the ideas of least privilege, auditing, and encryption outside of MongoDB. Reducing risk includes: configuring the network rules to ensure that only trusted hosts have access to MongoDB, and that the MongoDB processes only have access to the parts of the filesystem required for operation. 6.1.6 Additional Resources • Making HIPAA Compliant MongoDB Applications7 • Security Architecture White Paper8 • Webinar: Securing Your MongoDB Deployment9 6.2 Security Concepts These documents introduce and address concepts and strategies related to security practices in MongoDB deployments. Network Security (page 326) Documentation on authentication, authorization, and encryption in MongoDB. 2http://www.vormetric.com/sites/default/files/sb-MongoDB-Letter-2014-0611.pdf 3https://access.redhat.com/documentation/en-US/Red_Hat_Enterprise_Linux/7/html/Security_Guide/sec-Encryption.html 4http://www-03.ibm.com/software/products/en/infosphere-guardium-data-encryption 5http://www.vormetric.com/sites/default/files/sb-MongoDB-Letter-2014-0611.pdf 6http://technet.microsoft.com/en-us/library/hh831713.aspx 7https://www.mongodb.com/blog/post/making-hipaa-compliant-applications-mongodb?jmp=docs 8https://www.mongodb.com/lp/white-paper/mongodb-security-architecture?jmp=docs 9http://www.mongodb.com/presentations/webinar-securing-your-mongodb-deployment?jmp=docs 6.2. Security Concepts 325 MongoDB Documentation, Release 3.0.7 Access Control (page 334) Documentation on users and roles in MongoDB. Auditing (page 337) Documentation on the auditing feature available with MongoDB Enterprise. External Environment (page 337) Discusses potential risks related to MongoDB’s JavaScript, HTTP and REST in- terfaces, including strategies to control those risks. 6.2.1 Network Security These documents introduce and address concepts and strategies related to authentication, authorization, and encryp- tion. Authentication (page 326) Mechanisms for verifying user and instance access to MongoDB. Network Exposure and Security (page 330) Discusses potential security risks related to the network and strategies for decreasing possible network-based attack vectors for MongoDB. Kerberos Authentication (page 331) Kerberos authentication and MongoDB. Authentication Authentication is the process of verifying the identity of a client. When access control, i.e. authorization (page 334), is enabled, MongoDB requires all clients to authenticate themselves first in order to determine the access for the client. Although authentication and authorization (page 334) are closely connected, authentication is distinct from authoriza- tion. Authentication verifies the identity of a user; authorization determines the verified user’s access to resources and operations. MongoDB supports a number of authentication mechanisms (page 326) that clients can use to verify their identity. These mechanisms allow MongoDB to integrate into your existing authentication system. See Authentication Mecha- nisms (page 326) for details. In addition to verifying the identity of a client, MongoDB can require members of replica sets and sharded clusters to authenticate their membership (page 329) to their respective replica set or sharded cluster. See Authentication Between MongoDB Instances (page 329) for more information. Client Users To authenticate a client in MongoDB, you must add a corresponding user to MongoDB. When adding a user, you create the user in a specific database. This database is the authentication database for the user. Together, the user’s name and database serve as a unique identifier for that user. That is, if two users have the same name but are created in different databases, they are two separate users. To authenticate, the client must authenticate the user against the user’s authentication database. For instance, if using the mongo shell as a client, you can specify the authentication database for the user with the –authenticationDatabase option. To add and manage user information, MongoDB provides the db.createUser() method as well as other user management methods. For examples of user management in MongoDB, see Manage User and Roles (page 389). MongoDB stores all user information, including name (page 417), password (page 417), and the user’s database (page 417), in the system.users (page 416) collection in the admin database. Authentication Mechanisms Changed in version 3.0. 326 Chapter 6. Security MongoDB Documentation, Release 3.0.7 MongoDB supports multiple authentication mechanisms. MongoDB’s default authentication method is a challenge and response mechanism (SCRAM-SHA-1) (page 327). Previously, MongoDB used MongoDB Challenge and Re- sponse (MONGODB-CR) (page 328) as the default. MongoDB also supports x509 certificate authentication (page 328), LDAP proxy authentication (page 328), and Ker- beros authentication (page 328). This section introduces the mechanisms available in MongoDB. To specify the authentication mechanism to use, see authenticationMechanisms. SCRAM-SHA-1 Authentication New in version 3.0. SCRAM-SHA-1 is an IETF standard, RFC 580210, that defines best practice methods for implementation of challenge- response mechanisms for authenticating users with passwords. SCRAM-SHA-1 verifies supplied user credentials against the user’s name (page 417), password (page 417) and database (page 417). The user’s database is the database where the user was created, and the user’s database and the user’s name together serves to identify the user. Note: A driver upgrade is necessary to use the SCRAM-SHA-1 authentication mechanism if your current driver version does not support SCRAM-SHA-1. See required driver versions (page 829) for details. See also: • Blog Post: Improved Password-Based Authentication in MongoDB 3.0: SCRAM Explained (Part 1)11 • Blog Post: Improved Password-Based Authentication in MongoDB 3.0: SCRAM Explained (Part 2)12 SCRAM-SHA-1 Advantages MongoDB’s implementation of SCRAM-SHA-1 represents an improvement in secu- rity over the previously-used MONGODB-CR, providing: • A tunable work factor (iterationCount), • Per-user random salts rather than server-wide salts, • A cryptographically stronger hash function (SHA-1 rather than MD5), and • Authentication of the server to the client as well as the client to the server. SCRAM-SHA-1 and Existing User Credentials SCRAM-SHA-1 is the default mechanism for MongoDB versions beginning with the 3.0 series. However, if you are upgrading a MongoDB 2.6 instances that already have users credentials, MongoDB will continue to use MONGODB-CR for challenge-response authentication until you upgrade the authentication schema. Even when using the MONGODB-CR authentication mechanism, clients and drivers that support MongoDB 3.0 features (see Driver Compatibility Changes (page 817)) will use the SCRAM communication protocol. For details on upgrading the authentication schema model to SCRAM-SHA-1, see Upgrade to SCRAM-SHA-1 (page 827). Warning: The procedure to upgrade to SCRAM-SHA-1 discards the MONGODB-CR credentials used by 2.6. As such, the procedure is irreversible, short of restoring from backups. The procedure also disables MONGODB-CR as an authentication mechanism. 10https://tools.ietf.org/html/rfc5802 11https://www.mongodb.com/blog/post/improved-password-based-authentication-mongodb-30-scram-explained-part-1?jmp=docs 12https://www.mongodb.com/blog/post/improved-password-based-authentication-mongodb-30-scram-explained-part-2?jmp=docs 6.2. Security Concepts 327 MongoDB Documentation, Release 3.0.7 MONGODB-CR Authentication MONGODB-CR is a challenge-response mechanism that authenticates users through passwords. Changed in version 3.0: As of version 3.0, MongoDB no longer defaults to MONGODB-CR and instead uses SCRAM-SHA-1 as the default authentication mechanism. MONGODB-CR verifies supplied user credentials against the user’s name (page 417), password (page 417) and database (page 417). The user’s database is the database where the user was created, and the user’s database and the user’s name together serve to identify the user. Using key files, you can also use MONGODB-CR authentication for the internal member authentication (page 329) of replica set members and sharded cluster members. The contents of the key files serve as the shared password for the members. You must store the key file on each mongod or mongos instance for that replica set or sharded cluster. The content of the key file is arbitrary but must be the same on all mongod and mongos instances that connect to each other. See Generate a Key File (page 383) for instructions on generating a key file and turning on key file authentication for members. x.509 Certificate Authentication New in version 2.6. MongoDB supports x.509 certificate authentication for use with a secure TLS/SSL connection (page 347). To authenticate to servers, clients can use x.509 certificates instead of usernames and passwords. See Client x.509 Certificate (page 365) for more information. For membership authentication, members of sharded clusters and replica sets can use x.509 certificates instead of key files. See Use x.509 Certificate for Membership Authentication (page 367) for more information. Kerberos Authentication MongoDB Enterprise13 supports authentication using a Kerberos service. Kerberos is an industry standard authentication protocol for large client/server systems. To use MongoDB with Kerberos, you must have a properly configured Kerberos deployment, configured Kerberos service principals (page 332) for MongoDB, and added Kerberos user principal (page 332) to MongoDB. See Kerberos Authentication (page 331) for more information on Kerberos and MongoDB. To configure MongoDB to use Kerberos authentication, see Configure MongoDB with Kerberos Authentication on Linux (page 376) and Configure MongoDB with Kerberos Authentication on Windows (page 379). LDAP Proxy Authority Authentication MongoDB Enterprise14 supports proxy authentication through a Lightweight Directory Access Protocol (LDAP) service. See Authenticate Using SASL and LDAP with OpenLDAP (page 373) and Authenticate Using SASL and LDAP with ActiveDirectory (page 370). MongoDB Enterprise for Windows does not include LDAP support for authentication. However, MongoDB Enterprise for Linux supports using LDAP authentication with an ActiveDirectory server. MongoDB does not support LDAP authentication in mixed sharded cluster deployments that contain both version 2.4 and version 2.6 shards. Authentication Behavior Client Authentication Clients can authenticate using the challenge and response (page 328), x.509 (page 328), LDAP Proxy (page 328) and Kerberos (page 328) mechanisms. 13http://www.mongodb.com/products/mongodb-enterprise?jmp=docs 14http://www.mongodb.com/products/mongodb-enterprise?jmp=docs 328 Chapter 6. Security MongoDB Documentation, Release 3.0.7 Each client connection should authenticate as exactly one user. If a client authenticates to a database as one user and later authenticates to the same database as a different user, the second authentication invalidates the first. While clients can authenticate as multiple users if the users are defined on different databases, we recommend authenticating as one user at a time, providing the user with appropriate privileges on the databases required by the user. See Authenticate to a MongoDB Instance or Cluster (page 381) for more information. Authentication Between MongoDB Instances You can authenticate members of replica sets and sharded clusters. To authenticate members of a single MongoDB deployment to each other, MongoDB can use the keyFile and x.509 (page 328) mechanisms. Using keyFile authentication for members also enables authorization. Always run replica sets and sharded clusters in a trusted networking environment. Ensure that the network permits only trusted traffic to reach each mongod and mongos instance. Use your environment’s firewall and network routing to ensure that traffic only from clients and other members can reach your mongod and mongos instances. If needed, use virtual private networks (VPNs) to ensure secure connec- tions over wide area networks (WANs). Always ensure that: • Your network configuration will allow every member of the replica set or sharded cluster to contact every other member. • If you use MongoDB’s authentication system to limit access to your infrastructure, ensure that you configure a keyFile on all members to permit authentication. See Generate a Key File (page 383) for instructions on generating a key file and turning on key file authentication for members. For an example of using key files for sharded cluster authentication, see Enable Authentication in a Sharded Cluster (page 362). Authentication on Sharded Clusters In sharded clusters, applications authenticate to directly to mongos instances, using credentials stored in the admin database of the config servers. The shards in the sharded cluster also have credentials, and clients can authenticate directly to the shards to perform maintenance directly on the shards. In general, applications and clients should connect to the sharded cluster through the mongos. Changed in version 2.6: Previously, the credentials for authenticating to a database on a cluster resided on the primary shard (page 669) for that database. Some maintenance operations, such as cleanupOrphaned, compact, rs.reconfig(), require direct connec- tions to specific shards in a sharded cluster. To perform these operations with authentication enabled, you must connect directly to the shard and authenticate as a shard local administrative user. To create a shard local administrative user, connect directly to the shard and create the user. MongoDB stores shard local users in the admin database of the shard itself. These shard local users are completely independent from the users added to the sharded cluster via mongos. Shard local users are local to the shard and are inaccessible by mongos. Direct connections to a shard should only be for shard-specific maintenance and configuration. Localhost Exception The localhost exception allows you to enable authorization before creating the first user in the system. When active, the localhost exception allows connections from the localhost interface to create the first user on the admin database. The exception applies only when there are no users created in the MongoDB instance. Changed in version 3.0: The localhost exception changed so that these connections only have access to create the first user on the admin database. In previous versions, connections that gained access using the localhost exception had unrestricted access to the MongoDB instance. If you use the localhost exception when deploying a new MongoDB system, the first user you create must be in the admin database with privileges to create other users, such as a user with the userAdmin (page 408) or 6.2. Security Concepts 329 MongoDB Documentation, Release 3.0.7 userAdminAnyDatabase (page 412) role. See Enable Client Access Control (page 360) and Create a User Ad- ministrator (page 387) for more information. In the case of a sharded cluster, the localhost exception applies to each shard individually as well as to the cluster as a whole. Once you create a sharded cluster and add an administrator to the mongos instance, you must still prevent unauthorized access to the individual shards. Follow one of the following steps for each shard in your cluster: • Create an administrative user, or • Disable the localhost exception at startup. To disable the localhost exception, use setParameter in your configuration file, or --setParameter on the command line to set the enableLocalhostAuthBypass parameter to 0. Network Exposure and Security By default, MongoDB programs (i.e. mongos and mongod) will bind to all available network interfaces (i.e. IP addresses) on a system. This page outlines various runtime options that allow you to limit access to MongoDB programs. Configuration Options You can limit the network exposure with the following mongod and mongos configuration options: enabled, net.http.RESTInterfaceEnabled, bindIp, and port. You can use a configuration file to specify these settings. nohttpinterface The enabled setting for mongod and mongos instances disables the “home” status page. Changed in version 2.6: The mongod and mongos instances run with the http interface disabled by default. The status interface is read-only by default, and the default port for the status page is 28017. Authentication does not control or affect access to this interface. Warning: Disable this interface for production deployments. If you enable this interface, you should only allow trusted clients to access this port. See Firewalls (page 331). rest The net.http.RESTInterfaceEnabled setting for mongod enables a fully interactive admin- istrative REST interface, which is disabled by default. The net.http.RESTInterfaceEnabled con- figuration makes the http status interface 15, which is read-only by default, fully interactive. Use the net.http.RESTInterfaceEnabled setting with the enabled setting. The REST interface does not support any authentication and you should always restrict access to this interface to only allow trusted clients to connect to this port. You may also enable this interface on the command line as mongod --rest --httpinterface. Warning: Disable this option for production deployments. If do you leave this interface enabled, you should only allow trusted clients to access this port. 15 Starting in version 2.6, http interface is disabled by default. 330 Chapter 6. Security MongoDB Documentation, Release 3.0.7 bind_ip The bindIp setting for mongod and mongos instances limits the network interfaces on which Mon- goDB programs will listen for incoming connections. You can also specify a number of interfaces by passing bindIp a comma separated list of IP addresses. You can use the mongod --bind_ip and mongos --bind_ip option on the command line at run time to limit the network accessibility of a MongoDB program. Important: Make sure that your mongod and mongos instances are only accessible on trusted networks. If your system has more than one network interface, bind MongoDB programs to the private or internal network interface. port The port setting for mongod and mongos instances changes the main port on which the mongod or mongos instance listens for connections. The default port is 27017. Changing the port does not meaningfully reduce risk or limit exposure. You may also specify this option on the command line as mongod --port or mongos --port. Setting port also indirectly sets the port for the HTTP status interface, which is always available on the port numbered 1000 greater than the primary mongod port. Only allow trusted clients to connect to the port for the mongod and mongos instances. See Firewalls (page 331). See also Security Considerations (page 198) and Default MongoDB Port (page 425). Firewalls Firewalls allow administrators to filter and control access to a system by providing granular control over what network communications. For administrators of MongoDB, the following capabilities are important: limiting incoming traffic on a specific port to specific systems, and limiting incoming traffic from untrusted hosts. On Linux systems, the iptables interface provides access to the underlying netfilter firewall. On Windows systems, netsh command line interface provides access to the underlying Windows Firewall. For additional infor- mation about firewall configuration, see Configure Linux iptables Firewall for MongoDB (page 340) and Configure Windows netsh Firewall for MongoDB (page 343). For best results and to minimize overall exposure, ensure that only traffic from trusted sources can reach mongod and mongos instances and that the mongod and mongos instances can only connect to trusted outputs. See also: For MongoDB deployments on Amazon’s web services, see the Amazon EC216 page, which addresses Amazon’s Security Groups and other EC2-specific security features. Virtual Private Networks Virtual private networks, or VPNs, make it possible to link two networks over an encrypted and limited-access trusted network. Typically, MongoDB users who use VPNs use TLS/SSL rather than IPSEC VPNs for performance issues. Depending on configuration and implementation, VPNs provide for certificate validation and a choice of encryption protocols, which requires a rigorous level of authentication and identification of all clients. Furthermore, because VPNs provide a secure tunnel, by using a VPN connection to control access to your MongoDB instance, you can prevent tampering and “man-in-the-middle” attacks. Kerberos Authentication New in version 2.4. 16https://docs.mongodb.org/ecosystem/platforms/amazon-ec2 6.2. Security Concepts 331 MongoDB Documentation, Release 3.0.7 Overview MongoDB Enterprise provides support for Kerberos authentication of MongoDB clients to mongod and mongos. Kerberos is an industry standard authentication protocol for large client/server systems. Kerberos allows MongoDB and applications to take advantage of existing authentication infrastructure and processes. Kerberos Components and MongoDB Principals In a Kerberos-based system, every participant in the authenticated communication is known as a “princi- pal”, and every principal must have a unique name. Principals belong to administrative units called realms. For each realm, the Kerberos Key Distribution Center (KDC) maintains a database of the realm’s principal and the principals’ associated “secret keys”. For a client-server authentication, the client requests from the KDC a “ticket” for access to a specific asset. KDC uses the client’s secret and the server’s secret to construct the ticket which allows the client and server to mutually authenticate each other, while keeping the secrets hidden. For the configuration of MongoDB for Kerberos support, two kinds of principal names are of interest: user principals (page 332) and service principals (page 332). User Principal To authenticate using Kerberos, you must add the Kerberos user principals to MongoDB to the $external database. User principal names have the form: @ For every user you want to authenticate using Kerberos, you must create a corresponding user in MongoDB in the $external database. For examples of adding a user to MongoDB as well as authenticating as that user, see Configure MongoDB with Kerberos Authentication on Linux (page 376) and Configure MongoDB with Kerberos Authentication on Windows (page 379). See also: User and Role Management Tutorials (page 387) for general information regarding creating and managing users in MongoDB. Service Principal Every MongoDB mongod and mongos instance (or mongod.exe or mongos.exe on Win- dows) must have an associated service principal. Service principal names have the form: /@ For MongoDB, the defaults to mongodb. For example, if m1.example.com is a MongoDB server, and example.com maintains the EXAMPLE.COM Kerberos realm, then m1 should have the service principal name mongodb/m1.example.com@EXAMPLE.COM. To specify a different value for , use serviceName during the start up of mongod or mongos (or mongod.exe or mongos.exe). mongo shell or other clients may also specify a different service principal name using serviceName. Service principal names must be reachable over the network using the fully qualified domain name (FQDN) part of its service principal name. By default, Kerberos attempts to identify hosts using the /etc/kerb5.conf file before using DNS to resolve hosts. On Windows, if running MongoDB as a service, see Assign Service Principal Name to MongoDB Windows Service (page 381). 332 Chapter 6. Security MongoDB Documentation, Release 3.0.7 Linux Keytab Files Linux systems can store Kerberos authentication keys for a service principal (page 332) in keytab files. Each Kerberized mongod and mongos instance running on Linux must have access to a keytab file containing keys for its service principal (page 332). To keep keytab files secure, use file permissions that restrict access to only the user that runs the mongod or mongos process. Tickets On Linux, MongoDB clients can use Kerberos’s kinit program to initialize a credential cache for authen- ticating the user principal to servers. Windows Active Directory Unlike on Linux systems, mongod and mongos instances running on Windows do not require access to keytab files. Instead, the mongod and mongos instances read their server credentials from a credential store specific to the operating system. However, from the Windows Active Directory, you can export a keytab file for use on Linux systems. See Ktpass17 for more information. Authenticate With Kerberos To configure MongoDB for Kerberos support and authenticate, see Configure Mon- goDB with Kerberos Authentication on Linux (page 376) and Configure MongoDB with Kerberos Authentication on Windows (page 379). Operational Considerations The HTTP Console The MongoDB HTTP Console18 interface does not support Kerberos authentication. DNS Each host that runs a mongod or mongos instance must have both A and PTR DNS records to provide forward and reverse lookup. Without A and PTR DNS records, the host cannot resolve the components of the Kerberos domain or the Key Distri- bution Center (KDC). System Time Synchronization To successfully authenticate, the system time for each mongod and mongos in- stance must be within 5 minutes of the system time of the other hosts in the Kerberos infrastructure. Kerberized MongoDB Environments Driver Support The following MongoDB drivers support Kerberos authentication: •C 19 • C++20 • Java21 •C# 22 • Node.js23 17http://technet.microsoft.com/en-us/library/cc753771.aspx 18https://docs.mongodb.org/ecosystem/tools/http-interfaces/#http-console 19https://api.mongodb.org/c/current/authentication.html#kerberos 20https://docs.mongodb.org/ecosystem/tutorial/authenticate-with-cpp-driver/ 21https://docs.mongodb.org/ecosystem/tutorial/authenticate-with-java-driver/ 22http://mongodb.github.io/mongo-csharp-driver/2.0/reference/driver/authentication/#gssapi-kerberos 23http://mongodb.github.io/node-mongodb-native/2.0/tutorials/enterprise_features/ 6.2. Security Concepts 333 MongoDB Documentation, Release 3.0.7 • PHP24 • Python25 • Ruby26 Use with Additional MongoDB Authentication Mechanism Although MongoDB supports the use of Ker- beros authentication with other authentication mechanisms, only add the other mechanisms as necessary. See the Incorporate Additional Authentication Mechanisms section in Configure MongoDB with Ker- beros Authentication on Linux (page 376) and Configure MongoDB with Kerberos Authentication on Windows (page 379) for details. Additional Resources • MongoDB LDAP and Kerberos Authentication with Dell (Quest) Authentication Services27 • MongoDB with Red Hat Enterprise Linux Identity Management and Kerberos28 6.2.2 Access Control These documents introduce and address concepts and strategies related to Role Based Access Control in MongoDB. Authorization (page 334) Introduction to Role Based Access Control used in MongoDB Collection-Level Access Control (page 336) Specify collection-level access control. Authorization MongoDB employs Role-Based Access Control (RBAC) to govern access to a MongoDB system. A user is granted one or more roles (page 334) that determine the user’s access to database resources and operations. Outside of role assignments, the user has no access to the system. MongoDB does not enable authorization by default. You can enable authorization using the --auth or the --keyFile options, or if using a configuration file, with the security.authorization or the security.keyFile settings. MongoDB provides built-in roles (page 406), each with a dedicated purpose for a common use case. Examples include the read (page 406), readWrite (page 406), dbAdmin (page 407), and root (page 413) roles. Administrators also can create new roles and privileges to cater to operational needs. Administrators can assign privileges scoped as granularly as the collection level. When granted a role, a user receives all the privileges of that role. A user can have several roles concurrently, in which case the user receives the union of all the privileges of the respective roles. Roles A role consists of privileges that pair resources with allowed operations. Each privilege is specified explicitly in the role or inherited from another role or both. 24http://php.net/manual/en/mongoclient.construct.php 25http://api.mongodb.org/python/current/examples/authentication.html 26https://docs.mongodb.org/ecosystem/tutorial/ruby-driver-tutorial/#gssapi-kerberos-mechanism 27https://www.mongodb.com/blog/post/mongodb-ldap-and-kerberos-authentication-dell-quest-authentication-services?jmp=docs 28http://docs.mongodb.org/ecosystem/tutorial/manage-red-hat-enterprise-linux-identity-management?jmp=docs 334 Chapter 6. Security MongoDB Documentation, Release 3.0.7 Except for roles created in the admin database, a role can only include privileges that apply to its database and can only inherit from other roles in its database. A role created in the admin database can include privileges that apply to the admin database, other databases or to the cluster (page 419) resource, and can inherit from roles in other databases as well as the admin database. A user assigned a role receives all the privileges of that role. The user can have multiple roles and can have different roles on different databases. Roles always grant privileges and never limit access. For example, if a user has both read (page 406) and readWriteAnyDatabase (page 412) roles on a database, the greater access prevails. Privileges A privilege consists of a specified resource and the actions permitted on the resource. A privilege resource (page 418) is either a database, collection, set of collections, or the cluster. If the cluster, the affiliated actions affect the state of the system rather than a specific database or collection. An action (page 419) is a command or method the user is allowed to perform on the resource. A resource can have multiple allowed actions. For available actions see Privilege Actions (page 419). For example, a privilege that includes the update (page 420) action allows a user to modify existing documents on the resource. To additionally grant the user permission to create documents on the resource, the administrator would add the insert (page 420) action to the privilege. For privilege syntax, see admin.system.roles.privileges (page 414). Inherited Privileges A role can include one or more existing roles in its definition, in which case the role inherits all the privileges of the included roles. A role can inherit privileges from other roles in its database. A role created on the admin database can inherit privileges from roles in any database. User-Defined Roles New in version 2.6. User administrators can create custom roles to ensure collection-level and command-level granularity and to adhere to the policy of least privilege. Administrators create and edit roles using the role management commands. MongoDB scopes a user-defined role to the database in which it is created and uniquely identifies the role by the pairing of its name and its database. MongoDB stores the roles in the admin database’s system.roles (page 414) collection. Do not access this collection directly but instead use the role management commands to view and edit custom roles. Collection-Level Access Control By creating a role with privileges (page 335) that are scoped to a specific collec- tion in a particular database, administrators can implement collection-level access control. See Collection-Level Access Control (page 336) for more information. Users MongoDB stores user credentials in the protected admin.system.users (page 297). Use the user management methods to view and edit user credentials. 6.2. Security Concepts 335 MongoDB Documentation, Release 3.0.7 Role Assignment to Users User administrators create the users that access the system’s databases. MongoDB’s user management commands let administrators create users and assign them roles. MongoDB scopes a user to the database in which the user is created. MongoDB stores all user definitions in the admin database, no matter which database the user is scoped to. MongoDB stores users in the admin database’s system.users collection (page 416). Do not access this collection directly but instead use the user management commands. The first role assigned in a database should be either userAdmin (page 408) or userAdminAnyDatabase (page 412). This user can then create all other users in the system. See Create a User Administrator (page 387). Protect the User and Role Collections MongoDB stores role and user data in the protected admin.system.roles (page 297) and admin.system.users (page 297) collections, which are only accessible using the user management methods. If you disable access control, do not modify the admin.system.roles (page 297) and admin.system.users (page 297) collections using normal insert() and update() operations. Additional Information See the reference section for documentation of all built-in-roles (page 406) and all available privilege actions (page 419). Also consider the reference for the form of the resource documents (page 418). To create users see the Create a User Administrator (page 387) and Manage User and Roles (page 389) tutorials. Collection-Level Access Control Collection-level access control allows administrators to grant users privileges that are scoped to specific collections. Administrators can implement collection-level access control through user-defined roles (page 335). By creating a role with privileges (page 335) that are scoped to a specific collection in a particular database, administrators can provision users with roles that grant privileges on a collection level. Privileges and Scope A privilege consists of actions (page 419) and the resources (page 418) upon which the actions are permissible; i.e. the resources define the scope of the actions for that privilege. By specifying both the database and the collection in the resource document (page 418) for a privilege, administrator can limit the privilege actions just to a specific collection in a specific database. Each privilege action in a role can be scoped to a different collection. For example, a user defined role can contain the following privileges: privileges:[ { resource: { db: "products", collection: "inventory" }, actions:[ "find", "update", "insert"]}, { resource: { db: "products", collection: "orders" }, actions:[ "find"]} ] The first privilege scopes its actions to the inventory collection of the products database. The second privilege scopes its actions to the orders collection of the products database. Additional Information For more information on user-defined roles and MongoDB authorization model, see Authorization (page 334). For a tutorial on creating user-defined roles, see Manage User and Roles (page 389). 336 Chapter 6. Security MongoDB Documentation, Release 3.0.7 6.2.3 Auditing New in version 2.6. MongoDB Enterprise includes an auditing capability for mongod and mongos instances. The auditing facility allows administrators and users to track system activity for deployments with multiple users and applications. The auditing facility can write audit events to the console, the syslog, a JSON file, or a BSON file. Audit Events and Filter To enable auditing for MongoDB Enterprise, see Configure System Events Auditing (page 398). Once enabled, the auditing system can record the following operations: • schema (DDL), • replica set, • authentication and authorization, and • general operations. For details on the audit log messages, see System Event Audit Messages (page 425). By default, the auditing system records all these operations; however, you can set up filters (page 400) to restrict the events captured. To set up filters, see Configure Audit Filters (page 400). Audit Guarantee The auditing system writes every audit event 29 to an in-memory buffer of audit events. MongoDB writes this buffer to disk periodically. For events collected from any single connection, the events have a total order: if MongoDB writes one event to disk, the system guarantees that it has written all prior events for that connection to disk. If an audit event entry corresponds to an operation that affects the durable state of the database, such as a modification to data, MongoDB will always write the audit event to disk before writing to the journal for that entry. That is, before adding an operation to the journal, MongoDB writes all audit events on the connection that triggered the operation, up to and including the entry for the operation. These auditing guarantees require that MongoDB run with journaling enabled. Warning: MongoDB may lose events if the server terminates before it commits the events to the audit log. The client may receive confirmation of the event before MongoDB commits to the audit log. For example, while auditing an aggregation operation, the server might crash after returning the result but before the audit log flushes. 6.2.4 External Environment These documents introduce and address concepts and strategies related to security practices in MongoDB deployments. Security and MongoDB API Interfaces (page 338) Discusses potential risks related to MongoDB’s JavaScript, HTTP and REST interfaces, including strategies to control those risks. 29 Audit configuration can include a filter (page 400) to limit events to audit. 6.2. Security Concepts 337 MongoDB Documentation, Release 3.0.7 Security and MongoDB API Interfaces The following section contains strategies to limit risks related to MongoDB’s available interfaces including JavaScript, HTTP, and REST interfaces. JavaScript and the Security of the mongo Shell The following JavaScript evaluation behaviors of the mongo shell represents risk exposures. JavaScript Expression or JavaScript File The mongo program can evaluate JavaScript expressions using the com- mand line --eval option. Also, the mongo program can evaluate a JavaScript file (.js) passed directly to it (e.g. mongo someFile.js). Because the mongo program evaluates the JavaScript directly, inputs should only come from trusted sources. .mongorc.js File If a .mongorc.js file exists 30, the mongo shell will evaluate a .mongorc.js file before starting. You can disable this behavior by passing the mongo --norc option. HTTP Status Interface Warning: Ensure that the HTTP status interface, the REST API, and the JSON API are all disabled in production environments to prevent potential data exposure and vulnerability to attackers. The HTTP status interface provides a web-based interface that includes a variety of operational data, logs, and status reports regarding the mongod or mongos instance. The HTTP interface is always available on the port numbered 1000 greater than the primary mongod port. By default, the HTTP interface port is 28017, but is indirectly set using the port option which allows you to configure the primary mongod port. Without the net.http.RESTInterfaceEnabled setting, this interface is entirely read-only, and limited in scope; nevertheless, this interface may represent an exposure. To disable the HTTP interface, set the enabled run time option or the --nohttpinterface command line option. See also Configuration Options (page 330). Note: While MongoDB Enterprise does support Kerberos authentication, Kerberos is not supported in HTTP status interface in any version of MongoDB. Changed in version 3.0. Neither the HTTP status interface nor the REST API support the SCRAM-SHA-1 (page 327) challenge-response user authentication mechanism introduced in version 3.0. REST API The REST API to MongoDB provides additional information and write access on top of the HTTP status interface. While the REST API does not provide any support for insert, update, or remove operations, it does provide adminis- trative access, and its accessibility represents a vulnerability in a secure environment. The REST interface is disabled by default, and is not recommended for production use. If you must use the REST API, please control and limit access to the REST API. The REST API does not include any support for authentication, even when running with authorization enabled. 30 On Linux and Unix systems, mongo reads the .mongorc.js file from $HOME/.mongorc.js (i.e. ~/.mongorc.js). On Windows, mongo.exe reads the .mongorc.js file from %HOME%.mongorc.js or %HOMEDRIVE%%HOMEPATH%.mongorc.js. 338 Chapter 6. Security MongoDB Documentation, Release 3.0.7 See the following documents for instructions on restricting access to the REST API interface: • Configure Linux iptables Firewall for MongoDB (page 340) • Configure Windows netsh Firewall for MongoDB (page 343) 6.3 Security Tutorials The following tutorials provide instructions for enabling and using the security features available in MongoDB. Network Security Tutorials (page 340) Ensure that the underlying network configuration supports a secure operating environment for MongoDB deployments, and appropriately limits access to MongoDB deployments. Configure Linux iptables Firewall for MongoDB (page 340) Basic firewall configuration patterns and exam- ples for iptables on Linux systems. Configure Windows netsh Firewall for MongoDB (page 343) Basic firewall configuration patterns and exam- ples for netsh on Windows systems. Configure mongod and mongos for TLS/SSL (page 347) TLS/SSL allows MongoDB clients to support en- crypted connections to mongod instances. Continue reading from Network Security Tutorials (page 340) for more information on running MongoDB in secure environments. Security Deployment Tutorials (page 356) These tutorials describe procedures for deploying MongoDB using au- thentication and authorization. Authentication Tutorials (page 360) These tutorials describe procedures relevant for the configuration, operation, and maintenance of MongoDB’s access control system. Enable Client Access Control (page 360) Describes the process for enabling authentication for MongoDB de- ployments. Use x.509 Certificates to Authenticate Clients (page 364) Use x.509 for client authentication. Use x.509 Certificate for Membership Authentication (page 367) Use x.509 for internal member authentica- tion for replica sets and sharded clusters. Configure MongoDB with Kerberos Authentication on Linux (page 376) For MongoDB Enterprise Linux, describes the process to enable Kerberos-based authentication for MongoDB deployments. Continue reading from Authentication Tutorials (page 360) for additional tutorials on configuring MongoDB’s authentication systems. Enable Authentication after Creating the User Administrator (page 363) Describes an alternative process for enabling authentication for MongoDB deployments. User and Role Management Tutorials (page 387) MongoDB’s access control system provides a flexible role-based access control system that you can use to limit access to MongoDB deployments. The tutorials in this section describe the configuration an setup of the authorization system. Manage User and Roles (page 389) Manage users by creating new users, creating new roles, and modifying existing users. Continue reading from User and Role Management Tutorials (page 387) for additional tutorials on managing users and privileges in MongoDB’s authorization system. Auditing Tutorials (page 398) MongoDB Enterprise provides auditing of operations. The tutorials in this section describe procedures to enable and configure the auditing feature. Create a Vulnerability Report (page 403) Report a vulnerability in MongoDB. 6.3. Security Tutorials 339 MongoDB Documentation, Release 3.0.7 6.3.1 Network Security Tutorials The following tutorials provide information on handling network security for MongoDB. Configure Linux iptables Firewall for MongoDB (page 340) Basic firewall configuration patterns and examples for iptables on Linux systems. Configure Windows netsh Firewall for MongoDB (page 343) Basic firewall configuration patterns and examples for netsh on Windows systems. Configure mongod and mongos for TLS/SSL (page 347) TLS/SSL allows MongoDB clients to support encrypted connections to mongod instances. TLS/SSL Configuration for Clients (page 351) Configure clients to connect to MongoDB instances that use TLS/SSL. Upgrade a Cluster to Use TLS/SSL (page 354) Rolling upgrade process to use TLS/SSL. Configure MongoDB for FIPS (page 355) Configure for Federal Information Processing Standard (FIPS). Configure Linux iptables Firewall for MongoDB On contemporary Linux systems, the iptables program provides methods for managing the Linux Kernel’s netfilter or network packet filtering capabilities. These firewall rules make it possible for administrators to control what hosts can connect to the system, and limit risk exposure by limiting the hosts that can connect to a system. This document outlines basic firewall configurations for iptables firewalls on Linux. Use these approaches as a starting point for your larger networking organization. For a detailed overview of security practices and risk manage- ment for MongoDB, see Security Concepts (page 325). See also: For MongoDB deployments on Amazon’s web services, see the Amazon EC231 page, which addresses Amazon’s Security Groups and other EC2-specific security features. Overview Rules in iptables configurations fall into chains, which describe the process for filtering and processing specific streams of traffic. Chains have an order, and packets must pass through earlier rules in a chain to reach later rules. This document addresses only the following two chains: INPUT Controls all incoming traffic. OUTPUT Controls all outgoing traffic. Given the default ports (page 330) of all MongoDB processes, you must configure networking rules that permit only required communication between your application and the appropriate mongod and mongos instances. Be aware that, by default, the default policy of iptables is to allow all connections and traffic unless explicitly disabled. The configuration changes outlined in this document will create rules that explicitly allow traffic from specific addresses and on specific ports, using a default policy that drops all traffic that is not explicitly allowed. When you have properly configured your iptables rules to allow only the traffic that you want to permit, you can Change Default Policy to DROP (page 342). 31https://docs.mongodb.org/ecosystem/platforms/amazon-ec2 340 Chapter 6. Security MongoDB Documentation, Release 3.0.7 Patterns This section contains a number of patterns and examples for configuring iptables for use with MongoDB deploy- ments. If you have configured different ports using the port configuration setting, you will need to modify the rules accordingly. Traffic to and from mongod Instances This pattern is applicable to all mongod instances running as standalone instances or as part of a replica set. The goal of this pattern is to explicitly allow traffic to the mongod instance from the application server. In the following examples, replace with the IP address of the application server: iptables -A INPUT -s -p tcp --destination-port 27017 -m state --state NEW,ESTABLISHED -j ACCEPT iptables -A OUTPUT -d -p tcp --source-port 27017 -m state --state ESTABLISHED -j ACCEPT The first rule allows all incoming traffic from on port 27017, which allows the application server to connect to the mongod instance. The second rule, allows outgoing traffic from the mongod to reach the application server. Optional If you have only one application server, you can replace with either the IP address itself, such as: 198.51.100.55. You can also express this using CIDR notation as 198.51.100.55/32. If you want to permit a larger block of possible IP addresses you can allow traffic from a /24 using one of the following specifications for the , as follows: 10.10.10.10/24 10.10.10.10/255.255.255.0 Traffic to and from mongos Instances mongos instances provide query routing for sharded clusters. Clients connect to mongos instances, which behave from the client’s perspective as mongod instances. In turn, the mongos connects to all mongod instances that are components of the sharded cluster. Use the same iptables command to allow traffic to and from these instances as you would from the mongod instances that are members of the replica set. Take the configuration outlined in the Traffic to and from mongod Instances (page 341) section as an example. Traffic to and from a MongoDB Config Server Config servers, host the config database that stores metadata for sharded clusters. Each production cluster has three config servers, initiated using the mongod --configsvr option. 32 Config servers listen for connections on port 27019. As a result, add the following iptables rules to the config server to allow incoming and outgoing connection on port 27019, for connection to the other config servers. iptables -A INPUT -s -p tcp --destination-port 27019 -m state --state NEW,ESTABLISHED -j ACCEPT iptables -A OUTPUT -d -p tcp --source-port 27019 -m state --state ESTABLISHED -j ACCEPT Replace with the address or address space of all the mongod that provide config servers. Additionally, config servers need to allow incoming connections from all of the mongos instances in the cluster and all mongod instances in the cluster. Add rules that resemble the following: iptables -A INPUT -s -p tcp --destination-port 27019 -m state --state NEW,ESTABLISHED -j ACCEPT Replace with the address of the mongos instances and the shard mongod instances. 32 You also can run a config server by using the configsvr value for the clusterRole setting in a configuration file. 6.3. Security Tutorials 341 MongoDB Documentation, Release 3.0.7 Traffic to and from a MongoDB Shard Server For shard servers, running as mongod --shardsvr 33 Because the default port number is 27018 when running with the shardsvr value for the clusterRole setting, you must configure the following iptables rules to allow traffic to and from each shard: iptables -A INPUT -s -p tcp --destination-port 27018 -m state --state NEW,ESTABLISHED -j ACCEPT iptables -A OUTPUT -d -p tcp --source-port 27018 -m state --state ESTABLISHED -j ACCEPT Replace the specification with the IP address of all mongod. This allows you to permit incoming and outgoing traffic between all shards including constituent replica set members, to: • all mongod instances in the shard’s replica sets. • all mongod instances in other shards. 34 Furthermore, shards need to be able make outgoing connections to: • all mongos instances. • all mongod instances in the config servers. Create a rule that resembles the following, and replace the with the address of the config servers and the mongos instances: iptables -A OUTPUT -d -p tcp --source-port 27018 -m state --state ESTABLISHED -j ACCEPT Provide Access For Monitoring Systems 1. The mongostat diagnostic tool, when running with the --discover needs to be able to reach all compo- nents of a cluster, including the config servers, the shard servers, and the mongos instances. 2. If your monitoring system needs access the HTTP interface, insert the following rule to the chain: iptables -A INPUT -s -p tcp --destination-port 28017 -m state --state NEW,ESTABLISHED -j ACCEPT Replace with the address of the instance that needs access to the HTTP or REST interface. For all deployments, you should restrict access to this port to only the monitoring instance. Optional For config server mongod instances running with the shardsvr value for the clusterRole setting, the rule would resemble the following: iptables -A INPUT -s -p tcp --destination-port 28018 -m state --state NEW,ESTABLISHED -j ACCEPT For config server mongod instances running with the configsvr value for the clusterRole setting, the rule would resemble the following: iptables -A INPUT -s -p tcp --destination-port 28019 -m state --state NEW,ESTABLISHED -j ACCEPT Change Default Policy to DROP The default policy for iptables chains is to allow all traffic. After completing all iptables configuration changes, you must change the default policy to DROP so that all traffic that isn’t explicitly allowed as above will not be able to reach components of the MongoDB deployment. Issue the following commands to change this policy: 33 You can also specify the shard server option with the shardsvr value for the clusterRole setting in the configuration file. Shard members are also often conventional replica sets using the default port. 34 All shards in a cluster need to be able to communicate with all other shards to facilitate chunk and balancing operations. 342 Chapter 6. Security MongoDB Documentation, Release 3.0.7 iptables -P INPUT DROP iptables -P OUTPUT DROP Manage and Maintain iptables Configuration This section contains a number of basic operations for managing and using iptables. There are various front end tools that automate some aspects of iptables configuration, but at the core all iptables front ends provide the same basic functionality: Make all iptables Rules Persistent By default all iptables rules are only stored in memory. When your system restarts, your firewall rules will revert to their defaults. When you have tested a rule set and have guaranteed that it effectively controls traffic you can use the following operations to you should make the rule set persistent. On Red Hat Enterprise Linux, Fedora Linux, and related distributions you can issue the following command: service iptables save On Debian, Ubuntu, and related distributions, you can use the following command to dump the iptables rules to the /etc/iptables.conf file: iptables-save > /etc/iptables.conf Run the following operation to restore the network rules: iptables-restore < /etc/iptables.conf Place this command in your rc.local file, or in the /etc/network/if-up.d/iptables file with other similar operations. List all iptables Rules To list all of currently applied iptables rules, use the following operation at the system shell. iptables -L Flush all iptables Rules If you make a configuration mistake when entering iptables rules or simply need to revert to the default rule set, you can use the following operation at the system shell to flush all rules: iptables -F If you’ve already made your iptables rules persistent, you will need to repeat the appropriate procedure in the Make all iptables Rules Persistent (page 343) section. Configure Windows netsh Firewall for MongoDB On Windows Server systems, the netsh program provides methods for managing the Windows Firewall. These firewall rules make it possible for administrators to control what hosts can connect to the system, and limit risk exposure by limiting the hosts that can connect to a system. This document outlines basic Windows Firewall configurations. Use these approaches as a starting point for your larger networking organization. For a detailed over view of security practices and risk management for MongoDB, see Security Concepts (page 325). See also: 6.3. Security Tutorials 343 MongoDB Documentation, Release 3.0.7 Windows Firewall35 documentation from Microsoft. Overview Windows Firewall processes rules in an ordered determined by rule type, and parsed in the following order: 1. Windows Service Hardening 2. Connection security rules 3. Authenticated Bypass Rules 4. Block Rules 5. Allow Rules 6. Default Rules By default, the policy in Windows Firewall allows all outbound connections and blocks all incoming connections. Given the default ports (page 330) of all MongoDB processes, you must configure networking rules that permit only required communication between your application and the appropriate mongod.exe and mongos.exe instances. The configuration changes outlined in this document will create rules which explicitly allow traffic from specific addresses and on specific ports, using a default policy that drops all traffic that is not explicitly allowed. You can configure the Windows Firewall with using the netsh command line tool or through a windows application. On Windows Server 2008 this application is Windows Firewall With Advanced Security in Administrative Tools. On previous versions of Windows Server, access the Windows Firewall application in the System and Security control panel. The procedures in this document use the netsh command line tool. Patterns This section contains a number of patterns and examples for configuring Windows Firewall for use with MongoDB deployments. If you have configured different ports using the port configuration setting, you will need to modify the rules accordingly. Traffic to and from mongod.exe Instances This pattern is applicable to all mongod.exe instances running as standalone instances or as part of a replica set. The goal of this pattern is to explicitly allow traffic to the mongod.exe instance from the application server. netsh advfirewall firewall add rule name="Open mongod port 27017" dir=in action=allow protocol=TCP localport=27017 This rule allows all incoming traffic to port 27017, which allows the application server to connect to the mongod.exe instance. Windows Firewall also allows enabling network access for an entire application rather than to a specific port, as in the following example: netsh advfirewall firewall add rule name="Allowing mongod" dir=in action=allow program=" C:\mongodb\bin\mongod.exe" You can allow all access for a mongos.exe server, with the following invocation: netsh advfirewall firewall add rule name="Allowing mongos" dir=in action=allow program=" C:\mongodb\bin\mongos.exe" 35http://technet.microsoft.com/en-us/network/bb545423.aspx 344 Chapter 6. Security MongoDB Documentation, Release 3.0.7 Traffic to and from mongos.exe Instances mongos.exe instances provide query routing for sharded clusters. Clients connect to mongos.exe instances, which behave from the client’s perspective as mongod.exe instances. In turn, the mongos.exe connects to all mongod.exe instances that are components of the sharded cluster. Use the same Windows Firewall command to allow traffic to and from these instances as you would from the mongod.exe instances that are members of the replica set. netsh advfirewall firewall add rule name="Open mongod shard port 27018" dir=in action=allow protocol=TCP localport=27018 Traffic to and from a MongoDB Config Server Configuration servers, host the config database that stores meta- data for sharded clusters. Each production cluster has three configuration servers, initiated using the mongod --configsvr option. 36 Configuration servers listen for connections on port 27019. As a result, add the fol- lowing Windows Firewall rules to the config server to allow incoming and outgoing connection on port 27019, for connection to the other config servers. netsh advfirewall firewall add rule name="Open mongod config svr port 27019" dir=in action=allow protocol=TCP localport=27019 Additionally, config servers need to allow incoming connections from all of the mongos.exe instances in the cluster and all mongod.exe instances in the cluster. Add rules that resemble the following: netsh advfirewall firewall add rule name="Open mongod config svr inbound" dir=in action=allow protocol=TCP remoteip= localport=27019 Replace with the addresses of the mongos.exe instances and the shard mongod.exe instances. Traffic to and from a MongoDB Shard Server For shard servers, running as mongod --shardsvr 37 Because the default port number is 27018 when running with the shardsvr value for the clusterRole setting, you must configure the following Windows Firewall rules to allow traffic to and from each shard: netsh advfirewall firewall add rule name="Open mongod shardsvr inbound" dir=in action=allow protocol=TCP remoteip= localport=27018 netsh advfirewall firewall add rule name="Open mongod shardsvr outbound" dir=out action=allow protocol=TCP remoteip= localport=27018 Replace the specification with the IP address of all mongod.exe instances. This allows you to permit incoming and outgoing traffic between all shards including constituent replica set members to: • all mongod.exe instances in the shard’s replica sets. • all mongod.exe instances in other shards. 38 Furthermore, shards need to be able make outgoing connections to: • all mongos.exe instances. • all mongod.exe instances in the config servers. Create a rule that resembles the following, and replace the with the address of the config servers and the mongos.exe instances: netsh advfirewall firewall add rule name="Open mongod config svr outbound" dir=out action=allow protocol=TCP remoteip= localport=27018 Provide Access For Monitoring Systems 1. The mongostat diagnostic tool, when running with the --discover needs to be able to reach all compo- nents of a cluster, including the config servers, the shard servers, and the mongos.exe instances. 36 You also can run a config server by using the configsrv value for the clusterRole setting in a configuration file. 37 You can also specify the shard server option with the shardsvr value for the clusterRole setting in the configuration file. Shard members are also often conventional replica sets using the default port. 38 All shards in a cluster need to be able to communicate with all other shards to facilitate chunk and balancing operations. 6.3. Security Tutorials 345 MongoDB Documentation, Release 3.0.7 2. If your monitoring system needs access the HTTP interface, insert the following rule to the chain: netsh advfirewall firewall add rule name="Open mongod HTTP monitoring inbound" dir=in action=allow protocol=TCP remoteip= localport=28017 Replace with the address of the instance that needs access to the HTTP or REST interface. For all deployments, you should restrict access to this port to only the monitoring instance. Optional For config server mongod instances running with the shardsvr value for the clusterRole setting, the rule would resemble the following: netsh advfirewall firewall add rule name="Open mongos HTTP monitoring inbound" dir=in action=allow protocol=TCP remoteip= localport=28018 For config server mongod instances running with the configsvr value for the clusterRole setting, the rule would resemble the following: netsh advfirewall firewall add rule name="Open mongod configsvr HTTP monitoring inbound" dir=in action=allow protocol=TCP remoteip= localport=28019 Manage and Maintain Windows Firewall Configurations This section contains a number of basic operations for managing and using netsh. While you can use the GUI front ends to manage the Windows Firewall, all core functionality is accessible is accessible from netsh. Delete all Windows Firewall Rules To delete the firewall rule allowing mongod.exe traffic: netsh advfirewall firewall delete rule name="Open mongod port 27017" protocol=tcp localport=27017 netsh advfirewall firewall delete rule name="Open mongod shard port 27018" protocol=tcp localport=27018 List All Windows Firewall Rules To return a list of all Windows Firewall rules: netsh advfirewall firewall show rule name=all Reset Windows Firewall To reset the Windows Firewall rules: netsh advfirewall reset Backup and Restore Windows Firewall Rules To simplify administration of larger collection of systems, you can export or import firewall systems from different servers) rules very easily on Windows: Export all firewall rules with the following command: netsh advfirewall export "C:\temp\MongoDBfw.wfw" Replace "C:\temp\MongoDBfw.wfw" with a path of your choosing. You can use a command in the following form to import a file created using this operation: netsh advfirewall import "C:\temp\MongoDBfw.wfw" 346 Chapter 6. Security MongoDB Documentation, Release 3.0.7 Configure mongod and mongos for TLS/SSL Overview This document helps you to configure MongoDB to support TLS/SSL. MongoDB clients can use TLS/SSL to encrypt connections to mongod and mongos instances. MongoDB TLS/SSL implementation uses OpenSSL libraries. Note: Although TLS is the successor to SSL, this page uses the more familiar term SSL to refer to TLS/SSL. These instructions assume that you have already installed a build of MongoDB that includes SSL support and that your client driver supports SSL. For instructions on upgrading a cluster currently not using SSL to using SSL, see Upgrade a Cluster to Use TLS/SSL (page 354). Changed in version 2.6: MongoDB’s SSL encryption only allows use of strong SSL ciphers with a minimum of 128-bit key length for all connections. Prerequisites Important: A full description of TLS/SSL, PKI (Public Key Infrastructure) certificates, and Certificate Authority is beyond the scope of this document. This page assumes prior knowledge of TLS/SSL as well as access to valid certificates. MongoDB Support New in version 3.0: Most MongoDB distributions now include support for SSL. Certain distributions of MongoDB39 do not contain support for SSL. To use SSL, be sure to choose a package that supports SSL. All MongoDB Enterprise40 supported platforms include SSL support. Client Support See TLS/SSL Configuration for Clients (page 351) to learn about SSL support for Python, Java, Ruby, and other clients. Certificate Authorities For production use, your MongoDB deployment should use valid certificates generated and signed by a single certificate authority. You or your organization can generate and maintain an independent certificate authority, or use certificates generated by a third-party SSL vendor. Obtaining and managing certificates is beyond the scope of this documentation. .pem File Before you can use SSL, you must have a .pem file containing a public key certificate and its associated private key. MongoDB can use any valid SSL certificate issued by a certificate authority, or a self-signed certificate. If you use a self-signed certificate, although the communications channel will be encrypted, there will be no validation of server identity. Although such a situation will prevent eavesdropping on the connection, it leaves you vulnerable to a man-in- the-middle attack. Using a certificate signed by a trusted certificate authority will permit MongoDB drivers to verify the server’s identity. In general, avoid using self-signed certificates unless the network is trusted. Additionally, with regards to authentication among replica set/sharded cluster members (page 329), in order to mini- mize exposure of the private key and allow hostname validation, it is advisable to use different certificates on different servers. 39http://www.mongodb.org/downloads?jmp=docs 40http://www.mongodb.com/products/mongodb-enterprise?jmp=docs 6.3. Security Tutorials 347 MongoDB Documentation, Release 3.0.7 For testing purposes, you can generate a self-signed certificate and private key on a Unix system with a command that resembles the following: cd /etc/ssl/ openssl req -newkey rsa:2048 -new -x509 -days 365 -nodes -out mongodb-cert.crt -keyout mongodb-cert.key This operation generates a new, self-signed certificate with no passphrase that is valid for 365 days. Once you have the certificate, concatenate the certificate and private key to a .pem file, as in the following example: cat mongodb-cert.key mongodb-cert.crt > mongodb.pem See also: Use x.509 Certificates to Authenticate Clients (page 364) Procedures Set Up mongod and mongos with SSL Certificate and Key To use SSL in your MongoDB deployment, include the following run-time options with mongod and mongos: • net.ssl.mode set to requireSSL. This setting restricts each server to use only SSL encrypted connections. You can also specify either the value allowSSL or preferSSL to set up the use of mixed SSL modes on a port. See net.ssl.mode for details. • PEMKeyfile with the .pem file that contains the SSL certificate and key. Consider the following syntax for mongod: mongod --sslMode requireSSL --sslPEMKeyFile For example, given an SSL certificate located at /etc/ssl/mongodb.pem, configure mongod to use SSL encryp- tion for all connections with the following command: mongod --sslMode requireSSL --sslPEMKeyFile /etc/ssl/mongodb.pem Note: • Specify with the full path name to the certificate. • If the private key portion of the is encrypted, specify the passphrase. See SSL Certificate Passphrase (page 350). You may also specify these options in the configuration file, as in the following examples: If using the YAML configuration file format: net: ssl: mode: requireSSL PEMKeyFile: /etc/ssl/mongodb.pem Or, if using the older older configuration file format41: sslMode= requireSSL sslPEMKeyFile= /etc/ssl/mongodb.pem To connect, to mongod and mongos instances using SSL, the mongo shell and MongoDB tools must include the --ssl option. See TLS/SSL Configuration for Clients (page 351) for more information on connecting to mongod and mongos running with SSL. 41https://docs.mongodb.org/v2.4/reference/configuration-options 348 Chapter 6. Security MongoDB Documentation, Release 3.0.7 See also: Upgrade a Cluster to Use TLS/SSL (page 354) Set Up mongod and mongos with Certificate Validation To set up mongod or mongos for SSL encryption using an SSL certificate signed by a certificate authority, include the following run-time options during startup: • net.ssl.mode set to requireSSL. This setting restricts each server to use only SSL encrypted connections. You can also specify either the value allowSSL or preferSSL to set up the use of mixed SSL modes on a port. See net.ssl.mode for details. • PEMKeyfile with the name of the .pem file that contains the signed SSL certificate and key. • CAFile with the name of the .pem file that contains the root certificate chain from the Certificate Authority. Consider the following syntax for mongod: mongod --sslMode requireSSL --sslPEMKeyFile --sslCAFile For example, given a signed SSL certificate located at /etc/ssl/mongodb.pem and the certificate authority file at /etc/ssl/ca.pem, you can configure mongod for SSL encryption as follows: mongod --sslMode requireSSL --sslPEMKeyFile /etc/ssl/mongodb.pem --sslCAFile /etc/ssl/ca.pem Note: • Specify the file and the file with either the full path name or the relative path name. • If the is encrypted, specify the passphrase. See SSL Certificate Passphrase (page 350). You may also specify these options in the configuration file, as in the following examples: If using the YAML configuration file format: net: ssl: mode: requireSSL PEMKeyFile: /etc/ssl/mongodb.pem CAFile: /etc/ssl/ca.pem Or, if using the older older configuration file format42: sslMode= requireSSL sslPEMKeyFile= /etc/ssl/mongodb.pem sslCAFile= /etc/ssl/ca.pem To connect, to mongod and mongos instances using SSL, the mongo tools must include the both the --ssl and --sslPEMKeyFile option. See TLS/SSL Configuration for Clients (page 351) for more information on connecting to mongod and mongos running with SSL. See also: Upgrade a Cluster to Use TLS/SSL (page 354) Block Revoked Certificates for Clients To prevent clients with revoked certificates from connecting, include the sslCRLFile to specify a .pem file that contains revoked certificates. For example, the following mongod with SSL configuration includes the sslCRLFile setting: 42https://docs.mongodb.org/v2.4/reference/configuration-options 6.3. Security Tutorials 349 MongoDB Documentation, Release 3.0.7 mongod --sslMode requireSSL --sslCRLFile /etc/ssl/ca-crl.pem --sslPEMKeyFile /etc/ssl/mongodb.pem --sslCAFile /etc/ssl/ca.pem Clients with revoked certificates in the /etc/ssl/ca-crl.pem will not be able to connect to this mongod in- stance. Validate Only if a Client Presents a Certificate In most cases it is important to ensure that clients present valid certificates. However, if you have clients that cannot present a client certificate, or are transitioning to using a certificate authority you may only want to validate certificates from clients that present a certificate. If you want to bypass validation for clients that don’t present certificates, include the allowConnectionsWithoutCertificates run-time option with mongod and mongos. If the client does not present a certificate, no validation occurs. These connections, though not validated, are still encrypted using SSL. For example, consider the following mongod with an SSL configuration that includes the allowConnectionsWithoutCertificates setting: mongod --sslMode requireSSL --sslAllowConnectionsWithoutCertificates --sslPEMKeyFile /etc/ssl/mongodb.pem --sslCAFile /etc/ssl/ca.pem Then, clients can connect either with the option --ssl and no certificate or with the option --ssl and a valid certificate. See TLS/SSL Configuration for Clients (page 351) for more information on SSL connections for clients. Note: If the client presents a certificate, the certificate must be a valid certificate. All connections, including those that have not presented certificates are encrypted using SSL. Disallow Protocols New in version 3.0.7. To prevent MongoDB servers from accepting incoming connections that use sepcific protocols, in- clude the --sslDisabledProtocols option, or if using the configuration file the net.ssl.disabledProtocols setting. For example, the following configuration uses --sslDisabledProtocols option to prevent mongod from ac- cepting incoming connections that use either TLS1_0 or TLS1_1: mongod --sslMode requireSSL --sslDisabledProtocols TLS1_0,TLS1_1 --sslPEMKeyFile /etc/ssl/mongodb.pem --sslCAFile /etc/ssl/ca.pem If using the YAML configuration file format: net: ssl: mode: requireSSL PEMKeyFile: /etc/ssl/mongodb.pem CAFile: /etc/ssl/ca.pem disabledProtocols: TLS1_0,TLS1_1 For more information, including the protocols recognized by the option, see net.ssl.disabledProtocols or the --sslDisabledProtocols option for mongod and mongos. SSL Certificate Passphrase The PEM files for PEMKeyfile and ClusterFile may be encrypted. With en- crypted PEM files, you must specify the passphrase at startup with a command-line or a configuration file option or enter the passphrase when prompted. Changed in version 2.6: In previous versions, you can only specify the passphrase with a command-line or a configu- ration file option. 350 Chapter 6. Security MongoDB Documentation, Release 3.0.7 To specify the passphrase in clear text on the command line or in a configuration file, use the PEMKeyPassword and/or the ClusterPassword option. To have MongoDB prompt for the passphrase at the start of mongod or mongos and avoid specifying the passphrase in clear text, omit the PEMKeyPassword and/or the ClusterPassword option. MongoDB will prompt for each passphrase as necessary. Important: The passphrase prompt option is available if you run the MongoDB instance in the foreground with a connected terminal. If you run mongod or mongos in a non-interactive session (e.g. without a terminal or as a service on Windows), you cannot use the passphrase prompt option. Run in FIPS Mode Note: FIPS-compatible SSL is available only in MongoDB Enterprise43. See Configure MongoDB for FIPS (page 355) for more information. See Configure MongoDB for FIPS (page 355) for more details. TLS/SSL Configuration for Clients Clients must have support for TLS/SSL to work with a mongod or a mongos instance that has TLS/SSL support enabled. Important: A full description of TLS/SSL, PKI (Public Key Infrastructure) certificates, and Certificate Authority is beyond the scope of this document. This page assumes prior knowledge of TLS/SSL as well as access to valid certificates. Note: Although TLS is the successor to SSL, this page uses the more familiar term SSL to refer to TLS/SSL. See also: Configure mongod and mongos for TLS/SSL (page 347). mongo Shell SSL Configuration For SSL connections, you must use the mongo shell built with SSL support or distributed with MongoDB Enterprise. New in version 3.0: Most MongoDB distributions now include support for SSL. The mongo shell provides various mongo-shell-ssl settings, including: •--ssl •--sslPEMKeyFile with the name of the .pem file that contains the SSL certificate and key. •--sslCAFile with the name of the .pem file that contains the certificate from the Certificate Authority (CA). Changed in version 3.0: When running mongo with the --ssl option, you must include either --sslCAFile or --sslAllowInvalidCertificates. This restriction does not apply to the MongoDB tools. However, running the tools without -sslCAFile creates the same vulnerability to invalid certificates. 43http://www.mongodb.com/products/mongodb-enterprise?jmp=docs 6.3. Security Tutorials 351 MongoDB Documentation, Release 3.0.7 Warning: For SSL connections (--ssl) to mongod and mongos, if the mongo shell (or Mon- goDB tools (page 353)) runs without the --sslCAFile option (i.e. specifies the --sslAllowInvalidCertificates instead), the mongo shell (or MongoDB tools (page 353)) will not attempt to validate the server certificates. This creates a vulnerability to expired mongod and mongos certificates as well as to foreign processes posing as valid mongod or mongos instances. Ensure that you always specify the CA file to validate the server certificates in cases where intrusion is a possibility. •--sslPEMKeyPassword option if the client certificate-key file is encrypted. For a complete list of the mongo shell’s SSL settings, see mongo-shell-ssl. Connect to MongoDB Instance with SSL Encryption To connect to a mongod or mongos instance that requires only a SSL encryption mode (page 348), start mongo shell with --ssl and include the --sslCAFile to validate the server certificates. mongo --ssl --sslCAFile /etc/ssl/ca.pem Changed in version 3.0: When running mongo with the --ssl option, you must include either --sslCAFile or --sslAllowInvalidCertificates. This restriction does not apply to the MongoDB tools. However, running the tools without -sslCAFile creates the same vulnerability to invalid certificates. Connect to MongoDB Instance that Requires Client Certificates To connect to a mongod or mongos that re- quires CA-signed client certificates (page 349), start the mongo shell with --ssl, the --sslPEMKeyFile option to specify the signed certificate-key file, and the --sslCAFile to validate the server certificates. mongo --ssl --sslPEMKeyFile /etc/ssl/client.pem --sslCAFile /etc/ssl/ca.pem Changed in version 3.0: When running mongo with the --ssl option, you must include either --sslCAFile or --sslAllowInvalidCertificates. This restriction does not apply to the MongoDB tools. However, running the tools without -sslCAFile creates the same vulnerability to invalid certificates. Connect to MongoDB Instance that Validates when Presented with a Certificate To connect to a mongod or mongos instance that only requires valid certificates when the client presents a certificate (page 350), start mongo shell either: • with the --ssl,--sslCAFile, and no certificate or • with the --ssl,--sslCAFile, and a valid signed certificate. Changed in version 3.0: When running mongo with the --ssl option, you must include either --sslCAFile or --sslAllowInvalidCertificates. This restriction does not apply to the MongoDB tools. However, running the tools without -sslCAFile creates the same vulnerability to invalid certificates. For example, if mongod is running with weak certificate validation, both of the following mongo shell clients can connect to that mongod: mongo --ssl --sslCAFile /etc/ssl/ca.pem mongo --ssl --sslPEMKeyFile /etc/ssl/client.pem --sslCAFile /etc/ssl/ca.pem Important: If the client presents a certificate, the certificate must be valid. 352 Chapter 6. Security MongoDB Documentation, Release 3.0.7 MongoDB Cloud Manager and Ops Manager Monitoring Agent The MongoDB Cloud Manager Monitoring agent will also have to connect via SSL in order to gather its statistics. Because the agent already utilizes SSL for its communications to the MongoDB Cloud Manager servers, this is just a matter of enabling SSL support in MongoDB Cloud Manager itself on a per host basis. å See the MongoDB Cloud Manager documentation44 for more information about SSL configuration. For Ops Manager, see Ops Manager documentation45. MongoDB Drivers The MongoDB Drivers support for connection to SSL enabled MongoDB. See: • C Driver46 • C++ Driver47 • C# Driver48 • Java Driver49 • Node.js Driver50 • Perl Driver51 • PHP Driver52 • Python Driver53 • Ruby Driver54 • Scala Driver55 MongoDB Tools Changed in version 2.6. Various MongoDB utility programs supports SSL. These tools include: • mongodump • mongoexport • mongofiles • mongoimport • mongooplog • mongorestore 44https://docs.cloud.mongodb.com/ 45https://docs.opsmanager.mongodb.com/current/ 46http://api.mongodb.org/c/current/advanced-connections.html 47https://github.com/mongodb/mongo-cxx-driver/wiki/Configuring%20the%20Legacy%20Driver 48http://mongodb.github.io/mongo-csharp-driver/2.0/reference/driver/ssl/ 49http://mongodb.github.io/mongo-java-driver/3.0/driver/reference/connecting/ssl/ 50http://mongodb.github.io/node-mongodb-native/2.0/tutorials/enterprise_features/ 51https://metacpan.org/pod/MongoDB::MongoClient#ssl 52http://php.net/manual/en/mongo.connecting.ssl.php 53http://api.mongodb.org/python/current/examples/tls.html 54http://docs.mongodb.org/ecosystem/tutorial/ruby-driver-tutorial/#mongodb-x509-mechanism 55http://mongodb.github.io/casbah/guide/connecting.html#ssl-connections 6.3. Security Tutorials 353 MongoDB Documentation, Release 3.0.7 • mongostat • mongotop To use SSL connections with these tools, use the same SSL options as the mongo shell. See mongo Shell SSL Configuration (page 351). Upgrade a Cluster to Use TLS/SSL Changed in version 3.0: Most MongoDB distributions now include support for TLS/SSL. See Configure mongod and mongos for TLS/SSL (page 347) and TLS/SSL Configuration for Clients (page 351) for more information about TLS/SSL and MongoDB. Important: A full description of TLS/SSL, PKI (Public Key Infrastructure) certificates, and Certificate Authority is beyond the scope of this document. This page assumes prior knowledge of TLS/SSL as well as access to valid certificates. Changed in version 2.6. The MongoDB server supports listening for both TLS/SSL encrypted and unencrypted connections on the same TCP port. This allows upgrades of MongoDB clusters to use TLS/SSL encrypted connections. To upgrade from a MongoDB cluster using no TLS/SSL encryption to one using only TLS/SSL encryption, use the following rolling upgrade process: 1. For each node of a cluster, start the node with the option --sslMode set to allowSSL. The --sslMode allowSSL setting allows the node to accept both TLS/SSL and non-TLS/non-SSL incoming connections. Its connections to other servers do not use TLS/SSL. Include other TLS/SSL options (page 347) as well as any other options that are required for your specific configuration. For example: mongod --replSet --sslMode allowSSL --sslPEMKeyFile --sslCAFile Upgrade all nodes of the cluster to these settings. You may also specify these options in the configuration file. If using a YAML format configuration file, specify the following settings in the file: net: ssl: mode: PEMKeyFile: CAFile: Or, if using the older configuration file format56: sslMode= sslPEMKeyFile= sslCAFile= 2. Switch all clients to use TLS/SSL. See TLS/SSL Configuration for Clients (page 351). 3. For each node of a cluster, use the setParameter command to update the sslMode to preferSSL. 57 With preferSSL as its net.ssl.mode, the node accepts both TLS/SSL and non-TLS/non-SSL incoming connections, and its connections to other servers use TLS/SSL. For example: db.getSiblingDB('admin').runCommand({ setParameter: 1, sslMode: "preferSSL"}) 56https://docs.mongodb.org/v2.4/reference/configuration-options 57 As an alternative to using the setParameter command, you can also restart the nodes with the appropriate TLS/SSL options and values. 354 Chapter 6. Security MongoDB Documentation, Release 3.0.7 Upgrade all nodes of the cluster to these settings. At this point, all connections should be using TLS/SSL. 4. For each node of the cluster, use the setParameter command to update the sslMode to requireSSL. 1 With requireSSL as its net.ssl.mode, the node will reject any non-TLS/non-SSL connections. For example: db.getSiblingDB('admin').runCommand({ setParameter: 1, sslMode: "requireSSL"}) 5. After the upgrade of all nodes, edit the configuration file with the appropriate TLS/SSL settings to ensure that upon subsequent restarts, the cluster uses TLS/SSL. Configure MongoDB for FIPS New in version 2.6. Overview The Federal Information Processing Standard (FIPS) is a U.S. government computer security standard used to certify software modules and libraries that encrypt and decrypt data securely. You can configure MongoDB to run with a FIPS 140-2 certified library for OpenSSL. Configure FIPS to run by default or as needed from the command line. Prerequisites Important: A full description of FIPS and TLS/SSL is beyond the scope of this document. This tutorial assumes prior knowledge of FIPS and TLS/SSL. Only the MongoDB Enterprise58 version supports FIPS mode. See Install MongoDB Enterprise (page 33) to download and install MongoDB Enterprise59 to use FIPS mode. Your system must have an OpenSSL library configured with the FIPS 140-2 module. At the command line, type openssl version to confirm your OpenSSL software includes FIPS support. For Red Hat Enterprise Linux 6.x (RHEL 6.x) or its derivatives such as CentOS 6.x, the OpenSSL toolkit must be at least openssl-1.0.1e-16.el6_5 to use FIPS mode. To upgrade the toolkit for these platforms, issue the following command: sudo yum update openssl Some versions of Linux periodically execute a process to prelink dynamic libraries with pre-assigned addresses. This process modifies the OpenSSL libraries, specifically libcrypto. The OpenSSL FIPS mode will subsequently fail the signature check performed upon startup to ensure libcrypto has not been modified since compilation. To configure the Linux prelink process to not prelink libcrypto: sudo bash -c "echo '-b /usr/lib64/libcrypto.so.*' >>/etc/prelink.conf.d/openssl-prelink.conf" 58http://www.mongodb.com/products/mongodb-enterprise?jmp=docs 59http://www.mongodb.com/products/mongodb-enterprise?jmp=docs 6.3. Security Tutorials 355 MongoDB Documentation, Release 3.0.7 Considerations FIPS is property of the encryption system and not the access control system. However, if your environment re- quires FIPS compliant encryption and access control, you must ensure that the access control system uses only FIPS- compliant encryption. MongoDB’s FIPS support covers the way that MongoDB uses OpenSSL for network encryption and X509 authen- tication. If you use Kerberos or LDAP Proxy authentication, you muse ensure that these external mechanisms are FIPS-compliant. MONGODB-CR authentication is not FIPS compliant. Procedure Configure MongoDB to use TLS/SSL See Configure mongod and mongos for TLS/SSL (page 347) for details about configuring OpenSSL. Run mongod or mongos instance in FIPS mode Perform these steps after you Configure mongod and mongos for TLS/SSL (page 347). Step 1: Change configuration file. To configure your mongod or mongos instance to use FIPS mode, shut down the instance and update the configuration file with the following setting: net: ssl: FIPSMode: true Step 2: Start mongod or mongos instance with configuration file. For example, run this command to start the mongod instance with its configuration file: mongod--config/etc/mongod.conf Confirm FIPS mode is running Check the server log file for a message FIPS is active: FIPS 140-2 mode activated 6.3.2 Security Deployment Tutorials The following tutorials provide information in deploying MongoDB using authentication and authorization. Deploy Replica Set and Configure Authentication and Authorization (page 356) Configure a replica set that has au- thentication enabled. Deploy Replica Set and Configure Authentication and Authorization Overview With authentication (page 326) enabled, MongoDB forces all clients to identify themselves before granting access to the server. Authorization (page 334), in turn, allows administrators to define and limit the resources and operations that a user can access. Using authentication and authorization is a key part of a complete security strategy. 356 Chapter 6. Security MongoDB Documentation, Release 3.0.7 All MongoDB deployments support authentication. By default, MongoDB does not require authorization checking. You can enforce authorization checking when deploying MongoDB, or on an existing deployment; however, you cannot enable authorization checking on a running deployment without downtime. This tutorial provides a procedure for creating a MongoDB replica set (page 559) that uses the challenge-response au- thentication mechanism. The tutorial includes creation of a minimal authorization system to support basic operations. Considerations Authentication In this procedure, you will configure MongoDB using the default challenge-response authentication mechanism, using the keyFile to supply the password for inter-process authentication (page 329). The content of the key file is the shared secret used for all internal authentication. All deployments that enforce authorization checking should have one user administrator user that can create new users and modify existing users. During this procedure you will create a user administrator that you will use to administer this deployment. Architecture In a production, deploy each member of the replica set to its own machine and if possible bind to the standard MongoDB port of 27017. Use the bind_ip option to ensure that MongoDB listens for connections from applications on configured addresses. For a geographically distributed replica sets, ensure that the majority of the set’s mongod instances reside in the primary site. See Replica Set Deployment Architectures (page 572) for more information. Connectivity Ensure that network traffic can pass between all members of the set and all clients in the network securely and efficiently. Consider the following: • Establish a virtual private network. Ensure that your network topology routes all traffic between members within a single site over the local area network. • Configure access control to prevent connections from unknown clients to the replica set. • Configure networking and firewall rules so that incoming and outgoing packets are permitted only on the default MongoDB port and only from within your deployment. Finally ensure that each member of a replica set is accessible by way of resolvable DNS or hostnames. You should either configure your DNS names appropriately or set up your systems’ /etc/hosts file to reflect this configuration. Configuration Specify the run time configuration on each system in a configuration file stored in /etc/mongod.conf or a related location. Create the directory where MongoDB stores data files before deploying MongoDB. For more information about the run time options used above and other configuration options, see https://docs.mongodb.org/manual/reference/configuration-options. Procedure This procedure deploys a replica set in which all members use the same key file. Step 1: Start one member of the replica set. This mongod should not enable auth. 6.3. Security Tutorials 357 MongoDB Documentation, Release 3.0.7 Step 2: Create administrative users. The following operations will create two users: a user administrator that will be able to create and modify users (siteUserAdmin), and a root (page 413) user (siteRootAdmin) that you will use to complete the remainder of the tutorial: use admin db.createUser( { user: "siteUserAdmin", pwd: "", roles: [ { role: "userAdminAnyDatabase", db: "admin"}] }); db.createUser( { user: "siteRootAdmin", pwd: "", roles: [ { role: "root", db: "admin"}] }); Step 3: Stop the mongod instance. Step 4: Create the key file to be used by each member of the replica set. Create the key file your deployment will use to authenticate servers to each other. To generate pseudo-random data to use for a keyfile, issue the following openssl command: openssl rand -base64 741 > mongodb-keyfile chmod 600 mongodb-keyfile You may generate a key file using any method you choose. Always ensure that the password stored in the key file is both long and contains a high amount of entropy. Using openssl in this manner helps generate such a key. Step 5: Copy the key file to each member of the replica set. Copy the mongodb-keyfile to all hosts where components of a MongoDB deployment run. Set the permissions of these files to 600 so that only the owner of the file can read or write this file to prevent other users on the system from accessing the shared secret. Step 6: Start each member of the replica set with the appropriate options. For each member, start a mongod and specify the key file and the name of the replica set. Also specify other parameters as needed for your deployment. For replication-specific parameters, see cli-mongod-replica-set required by your deployment. If your application connects to more than one replica set, each set should have a distinct name. Some drivers group replica set connections by replica set name. The following example specifies parameters through the --keyFile and --replSet command-line options: mongod--keyFile/mysecretdirectory/mongodb-keyfile--replSet "rs0" The following example specifies parameters through a configuration file: mongod--config $HOME/.mongodb/config In production deployments, you can configure a init script to manage this process. Init scripts are beyond the scope of this document. Step 7: Connect to the member of the replica set where you created the administrative users. Connect to the replica set member you started and authenticate as the siteRootAdmin user. From the mongo shell, use the following operation to authenticate: 358 Chapter 6. Security MongoDB Documentation, Release 3.0.7 use admin db.auth("siteRootAdmin", ""); Step 8: Initiate the replica set. Use rs.initiate() on the replica set member: rs.initiate() MongoDB initiates a set that consists of the current member and that uses the default replica set configuration. Step 9: Verify the initial replica set configuration. Use rs.conf() to display the replica set configuration object (page 652): rs.conf() The replica set configuration object resembles the following: { "_id": "rs0", "version":1, "members":[ { "_id":1, "host": "mongodb0.example.net:27017" } ] } Step 10: Add the remaining members to the replica set. Add the remaining members with the rs.add() method. The following example adds two members: rs.add("mongodb1.example.net") rs.add("mongodb2.example.net") When complete, you have a fully functional replica set. The new replica set will elect a primary. Step 11: Check the status of the replica set. Use the rs.status() operation: rs.status() Step 12: Create additional users to address operational requirements. You can use built-in roles (page 406) to create common types of database users, such as the dbOwner (page 408) role to create a database administrator, the readWrite (page 406) role to create a user who can update data, or the read (page 406) role to create user who can search data but no more. You also can define custom roles (page 335). For example, the following creates a database administrator for the products database: use products db.createUser( { user: "productsDBAdmin", pwd: "password", roles: [ 6.3. Security Tutorials 359 MongoDB Documentation, Release 3.0.7 { role: "dbOwner", db: "products" } ] } ) For an overview of roles and privileges, see Authorization (page 334). For more information on adding users, see Manage User and Roles (page 389). 6.3.3 Authentication Tutorials The following tutorials provide instructions for MongoDB”s authentication related features. Enable Client Access Control (page 360) Describes the process for enabling authentication for MongoDB deploy- ments. Enable Authentication in a Sharded Cluster (page 362) Control access to a sharded cluster through a key file and the keyFile setting on each of the cluster’s components. Enable Authentication after Creating the User Administrator (page 363) Describes an alternative process for en- abling authentication for MongoDB deployments. Use x.509 Certificates to Authenticate Clients (page 364) Use x.509 for client authentication. Use x.509 Certificate for Membership Authentication (page 367) Use x.509 for internal member authentication for replica sets and sharded clusters. Authenticate Using SASL and LDAP with ActiveDirectory (page 370) Describes the process for authentication us- ing SASL/LDAP with ActiveDirectory. Authenticate Using SASL and LDAP with OpenLDAP (page 373) Describes the process for authentication using SASL/LDAP with OpenLDAP. Configure MongoDB with Kerberos Authentication on Linux (page 376) For MongoDB Enterprise Linux, de- scribes the process to enable Kerberos-based authentication for MongoDB deployments. Configure MongoDB with Kerberos Authentication on Windows (page 379) For MongoDB Enterprise for Win- dows, describes the process to enable Kerberos-based authentication for MongoDB deployments. Authenticate to a MongoDB Instance or Cluster (page 381) Describes the process for authenticating to MongoDB systems using the mongo shell. Generate a Key File (page 383) Use key file to allow the components of MongoDB sharded cluster or replica set to mutually authenticate. Troubleshoot Kerberos Authentication on Linux (page 383) Steps to troubleshoot Kerberos-based authentication for MongoDB deployments. Implement Field Level Redaction (page 385) Describes the process to set up and access document content that can have different access levels for the same data. Enable Client Access Control Overview Enabling access control on a MongoDB instance restricts access to the instance by requiring that users identify them- selves when connecting. In this procedure, you enable access control and then create the instance’s first user, which 360 Chapter 6. Security MongoDB Documentation, Release 3.0.7 must be a user administrator. The user administrator grants further access to the instance by creating additional users. Considerations If you create the user administrator before enabling access control, MongoDB disables the localhost exception (page 329). In that case, you must use the “Enable Authentication after Creating the User Administrator (page 363)” procedure to enable access control. This procedure uses the localhost exception (page 329) to allow you to create the first user after enabling authentication. See Localhost Exception (page 329) and Authentication (page 326) for more information. Procedure Step 1: Start the MongoDB instance with authentication enabled. Start the mongod or mongos instance with the authorization or keyFile setting. Use authorization on a standalone instance. Use keyFile on an instance in a replica set or sharded cluster. For example, to start a mongod with authentication enabled and a key file stored in /private/var, first set the following option in the mongod‘s configuration file: security: keyFile: /private/var/key.pem Then start the mongod and specify the config file. For example: mongod --config /etc/mongodb/mongodb.conf After you enable authentication, only the user administrator can connect to the MongoDB instance. The user admin- istrator must log in and grant further access to the instance by creating additional users. Step 2: Connect to the MongoDB instance via the localhost exception. Connect to the MongoDB instance from a client running on the same system. This access is made possible by the localhost exception (page 329). Step 3: Create the system user administrator. Add the user with the userAdminAnyDatabase (page 412) role, and only that role. The following example creates the user siteUserAdmin user on the admin database: use admin db.createUser( { user: "siteUserAdmin", pwd: "password", roles: [ { role: "userAdminAnyDatabase", db: "admin"}] } ) After you create the user administrator, the localhost exception (page 329) is no longer available. The mongo shell executes a number of commands at start up. As a result, when you log in as the user administrator, you may see authentication errors from one or more commands. You may ignore these errors, which are expected, because the userAdminAnyDatabase (page 412) role does not have permissions to run some of the start up commands. 6.3. Security Tutorials 361 MongoDB Documentation, Release 3.0.7 Step 4: Create additional users. Login in with the user administrator’s credentials and create additional users. See Manage User and Roles (page 389). Next Steps If you need to disable access control for any reason, restart the process without the authorization or keyFile setting. Enable Authentication in a Sharded Cluster New in version 2.0: Support for authentication with sharded clusters. Overview When authentication is enabled on a sharded cluster, every client that accesses the cluster must provide credentials. This includes MongoDB instances that access each other within the cluster. To enable authentication on a sharded cluster, you must enable authentication individually on each component of the cluster. This means enabling authentication on each mongos and each mongod, including each config server, and all members of a shard’s replica set. Authentication requires an authentication mechanism and, in most cases, a keyfile. The content of the key file must be the same on all cluster members. Considerations It is not possible to convert an existing sharded cluster that does not enforce access control to require authentication without taking all components of the cluster offline for a short period of time. As described in Localhost Exception (page 329), the localhost exception will apply to the individual shards unless you either create an administrative user or disable the localhost exception on each shard. Procedure Step 1: Create a key file. Create the key file your deployment will use to authenticate servers to each other. To generate pseudo-random data to use for a keyfile, issue the following openssl command: openssl rand -base64 741 > mongodb-keyfile chmod 600 mongodb-keyfile You may generate a key file using any method you choose. Always ensure that the password stored in the key file is both long and contains a high amount of entropy. Using openssl in this manner helps generate such a key. Step 2: Enable authentication on each component in the cluster. On each mongos and mongod in the cluster, including all config servers and shards, specify the key file using one of the following approaches: Specify the key file in the configuration file. In the configuration file, set the keyFile option to the key file’s path and then start the component, as in the following example: 362 Chapter 6. Security MongoDB Documentation, Release 3.0.7 security: keyFile: /srv/mongodb/keyfile Specify the key file at runtime. When starting the component, set the --keyFile option, which is an option for both mongos instances and mongod instances. Set the --keyFile to the key file’s path. The keyFile setting implies the authorization setting, which means in most cases you do not need to set authorization explicitly. Step 3: Add users. While connected to a mongos, add the first administrative user and then add subsequent users. See Create a User Administrator (page 387). Related Documents • Authentication (page 326) • Security (page 323) • Use x.509 Certificate for Membership Authentication (page 367) Enable Authentication after Creating the User Administrator Overview Enabling authentication on a MongoDB instance restricts access to the instance by requiring that users identify them- selves when connecting. In this procedure, you will create the instance’s first user, which must be a user administrator and then enable authentication. Then, you can authenticate as the user administrator to create additional users and grant additional access to the instance. This procedures outlines how enable authentication after creating the user administrator. The approach requires a restart. To enable authentication without restarting, see Enable Client Access Control (page 360). Considerations This document outlines a procedure for enabling authentication for MongoDB instance where you create the first user on an existing MongoDB system that does not require authentication before restarting the instance and requiring au- thentication. You can use the localhost exception (page 329) to gain access to a system with no users and authentication enabled. See Enable Client Access Control (page 360) for the description of that procedure. Procedure Step 1: Start the MongoDB instance without authentication. Start the mongod or mongos instance without the authorization or keyFile setting. For example: mongod--port 27017--dbpath/data/db1 For details on starting a mongod or mongos, see Manage mongod Processes (page 229) or Deploy a Sharded Cluster (page 691). 6.3. Security Tutorials 363 MongoDB Documentation, Release 3.0.7 Step 2: Create the system user administrator. Add the user with the userAdminAnyDatabase (page 412) role, and only that role. The following example creates the user siteUserAdmin user on the admin database: use admin db.createUser( { user: "siteUserAdmin", pwd: "password", roles: [ { role: "userAdminAnyDatabase", db: "admin"}] } ) Step 3: Re-start the MongoDB instance with authentication enabled. Re-start the mongod or mongos instance with the authorization or keyFile setting. Use authorization on a standalone instance. Use keyFile on an instance in a replica set or sharded cluster. The following example enables authentication on a standalone mongod using the authorization command-line option: mongod--auth--config/etc/mongodb/mongodb.conf Step 4: Create additional users. Log in with the user administrator’s credentials and create additional users. See Manage User and Roles (page 389). Next Steps If you need to disable authentication for any reason, restart the process without the authorization or keyFile option. Use x.509 Certificates to Authenticate Clients New in version 2.6. MongoDB supports x.509 certificate authentication for use with a secure TLS/SSL connection (page 347). The x.509 client authentication allows clients to authenticate to servers with certificates (page 365) rather than with a username and password. To use x.509 authentication for the internal authentication of replica set/sharded cluster members, see Use x.509 Certificate for Membership Authentication (page 367). Prerequisites Important: A full description of TLS/SSL, PKI (Public Key Infrastructure) certificates, in particular x.509 cer- tificates, and Certificate Authority is beyond the scope of this document. This tutorial assumes prior knowledge of TLS/SSL as well as access to valid x.509 certificates. Certificate Authority For production use, your MongoDB deployment should use valid certificates generated and signed by a single certificate authority. You or your organization can generate and maintain an independent certificate authority, or use certificates generated by a third-party SSL vendor. Obtaining and managing certificates is beyond the scope of this documentation. 364 Chapter 6. Security MongoDB Documentation, Release 3.0.7 Client x.509 Certificate The client certificate must have the following properties: • A single Certificate Authority (CA) must issue the certificates for both the client and the server. • Client certificates must contain the following fields: keyUsage = digitalSignature extendedKeyUsage = clientAuth • Each unique MongoDB user must have a unique certificate. • A client x.509 certificate’s subject, which contains the Distinguished Name (DN), must differ from that of a Member x.509 Certificate (page 367). Specifically, the subjects must differ with regards to at least one of the following attributes: Organization (O), the Organizational Unit (OU) or the Domain Component (DC). Warning: If a client x.509 certificate’s subject has the same O, OU, and DC combination as the Member x.509 Certificate (page 367), the client will be identified as a cluster member and granted full permission on the system. Procedures Configure MongoDB Server Use Command-line Options You can configure the MongoDB server from the command line, e.g.: mongod --clusterAuthMode x509 --sslMode requireSSL --sslPEMKeyFile --sslCAFile Warning: If the --sslCAFile option and its target file are not specified, x.509 client and member authenti- cation will not function. mongod, and mongos in sharded systems, will not be able to verify the certificates of processes connecting to it against the trusted certificate authority (CA) that issued them, breaking the certificate chain. As of version 2.6.4, mongod will not start with x.509 authentication enabled if the CA file is not specified. Use Configuration File You may also specify these options in the configuration file. Starting in MongoDB 2.6, you can specify the configuration for MongoDB in YAML format, e.g.: security: clusterAuthMode: x509 net: ssl: mode: requireSSL PEMKeyFile: CAFile: For backwards compatibility, you can also specify the configuration using the older configuration file format60, e.g.: clusterAuthMode = x509 sslMode = requireSSL sslPEMKeyFile = sslCAFile = Include any additional options, TLS/SSL or otherwise, that are required for your specific configuration. 60https://docs.mongodb.org/v2.4/reference/configuration-options 6.3. Security Tutorials 365 MongoDB Documentation, Release 3.0.7 Add x.509 Certificate subject as a User To authenticate with a client certificate, you must first add the value of the subject from the client certificate as a MongoDB user. Each unique x.509 client certificate corresponds to a single MongoDB user; i.e. you cannot use a single client certificate to authenticate more than one MongoDB user. 1. You can retrieve the subject from the client certificate with the following command: openssl x509 -in -inform PEM -subject -nameopt RFC2253 The command returns the subject string as well as certificate: subject=CN=myName,OU=myOrgUnit,O=myOrg,L=myLocality,ST=myState,C=myCountry -----BEGIN CERTIFICATE----- # ... -----END CERTIFICATE----- 2. Add the value of the subject, omitting the spaces, from the certificate as a user. For example, in the mongo shell, to add the user with both the readWrite role in the test database and the userAdminAnyDatabase role which is defined only in the admin database: db.getSiblingDB("$external").runCommand( { createUser: "CN=myName,OU=myOrgUnit,O=myOrg,L=myLocality,ST=myState,C=myCountry", roles:[ { role: 'readWrite', db: 'test'}, { role: 'userAdminAnyDatabase', db: 'admin'} ], writeConcern:{w: "majority" , wtimeout: 5000} } ) In the above example, to add the user with the readWrite role in the test database, the role specification document specified ’test’ in the db field. To add userAdminAnyDatabase role for the user, the above example specified ’admin’ in the db field. Note: Some roles are defined only in the admin database, including: clusterAdmin, readAnyDatabase, readWriteAnyDatabase, dbAdminAnyDatabase, and userAdminAnyDatabase. To add a user with these roles, specify ’admin’ in the db. See Manage User and Roles (page 389) for details on adding a user with roles. Authenticate with a x.509 Certificate To authenticate with a client certificate, you must first add a MongoDB user that corresponds to the client certificate. See Add x.509 Certificate subject as a User (page 366). To authenticate, use the db.auth() method in the $external database, specifying "MONGODB-X509" for the mechanism field, and the user that corresponds to the client certificate (page 366) for the user field. For example, if using the mongo shell, 1. Connect mongo shell to the mongod set up for SSL: mongo --ssl --sslPEMKeyFile --sslCAFile 2. To perform the authentication, use the db.auth() method in the $external database. For the mechanism field, specify "MONGODB-X509", and for the user field, specify the user, or the subject, that corresponds to the client certificate. db.getSiblingDB("$external").auth( { mechanism: "MONGODB-X509", 366 Chapter 6. Security MongoDB Documentation, Release 3.0.7 user: "CN=myName,OU=myOrgUnit,O=myOrg,L=myLocality,ST=myState,C=myCountry" } ) Use x.509 Certificate for Membership Authentication New in version 2.6. MongoDB supports x.509 certificate authentication for use with a secure TLS/SSL connection (page 347). Sharded cluster members and replica set members can use x.509 certificates to verify their membership to the cluster or the replica set instead of using keyfiles (page 326). The membership authentication is an internal process. For client authentication with x.509, see Use x.509 Certificates to Authenticate Clients (page 364). Important: A full description of TLS/SSL, PKI (Public Key Infrastructure) certificates, in particular x.509 cer- tificates, and Certificate Authority is beyond the scope of this document. This tutorial assumes prior knowledge of TLS/SSL as well as access to valid x.509 certificates. Member x.509 Certificate The member certificate, used for internal authentication to verify membership to the sharded cluster or a replica set, must have the following properties: • A single Certificate Authority (CA) must issue all the x.509 certificates for the members of a sharded cluster or a replica set. • The Distinguished Name (DN), found in the member certificate’s subject, must specify a non-empty value for at least one of the following attributes: Organization (O), the Organizational Unit (OU) or the Domain Component (DC). • The Organization attributes (O‘s), the Organizational Unit attributes (OU‘s), and the Domain Components (DC‘s) must match those from the certificates for the other cluster members. To match, the certificate must match all specifications of these attributes, or even the non-specification of these attributes. The order of the attributes does not matter. In the following example, the two DN‘s contain matching specifications for O, OU as well as the non-specification of the DC attribute. CN=host1,OU=Dept1,O=MongoDB,ST=NY,C=US C=US, ST=CA, O=MongoDB, OU=Dept1, CN=host2 However, the following two DN‘s contain a mismatch for the OU attribute since one contains two OU specifica- tions and the other, only one specification. CN=host1,OU=Dept1,OU=Sales,O=MongoDB CN=host2,OU=Dept1,O=MongoDB • Either the Common Name (CN) or one of the Subject Alternative Name (SAN) entries must match the hostname of the server, used by the other members of the cluster. For example, the certificates for a cluster could have the following subjects: subject=CN=,OU=Dept1,O=MongoDB,ST=NY,C=US subject=CN=,OU=Dept1,O=MongoDB,ST=NY,C=US subject=CN=,OU=Dept1,O=MongoDB,ST=NY,C=US 6.3. Security Tutorials 367 MongoDB Documentation, Release 3.0.7 You can use an x509 certificate that does not have Extended Key Usage (EKU) attributes set. If you use EKU attribute in the PEMKeyFile certificate, then specify the clientAuth and/or serverAuth attributes (i.e. “TLS Web Client Authentication” and “TLS Web Server Authentication,”) as needed. The certificate that you specify for the PEMKeyFile option requires the serverAuth attribute, and the certificate you specify to clusterFile requires the clientAuth attribute. If you omit ClusterFile, mongod will use the certificate specified to PEMKeyFile for member authentication. Configure Replica Set/Sharded Cluster Use Command-line Options To specify the x.509 certificate for internal cluster member authentication, append the additional TLS/SSL options --clusterAuthMode and --sslClusterFile, as in the following example for a member of a replica set: mongod --replSet --sslMode requireSSL --clusterAuthMode x509 --sslClusterFile --sslPEMKeyFile --sslCAFile Include any additional options, TLS/SSL or otherwise, that are required for your specific configuration. For instance, if the membership key is encrypted, set the --sslClusterPassword to the passphrase to decrypt the key or have MongoDB prompt for the passphrase. See SSL Certificate Passphrase (page 350) for details. Warning: If the --sslCAFile option and its target file are not specified, x.509 client and member authenti- cation will not function. mongod, and mongos in sharded systems, will not be able to verify the certificates of processes connecting to it against the trusted certificate authority (CA) that issued them, breaking the certificate chain. As of version 2.6.4, mongod will not start with x.509 authentication enabled if the CA file is not specified. Use Configuration File You can specify the configuration for MongoDB in a YAML formatted configuration file, as in the following example: security: clusterAuthMode: x509 net: ssl: mode: requireSSL PEMKeyFile: CAFile: clusterFile: See security.clusterAuthMode, net.ssl.mode, net.ssl.PEMKeyFile, net.ssl.CAFile, and net.ssl.clusterFile for more information on the settings. Upgrade from Keyfile Authentication to x.509 Authentication To upgrade clusters that are currently using keyfile authentication to x.509 authentication, use a rolling upgrade pro- cess. Clusters Currently Using TLS/SSL For clusters using TLS/SSL and keyfile authentication, to upgrade to x.509 cluster authentication, use the following rolling upgrade process: 1. For each node of a cluster, start the node with the option --clusterAuthMode set to sendKeyFile and the option --sslClusterFile set to the appropriate path of the node’s certificate. Include other TLS/SSL options (page 347) as well as any other options that are required for your specific configuration. For example: 368 Chapter 6. Security MongoDB Documentation, Release 3.0.7 mongod --replSet --sslMode requireSSL --clusterAuthMode sendKeyFile --sslClusterFile --sslPEMKeyFile --sslCAFile With this setting, each node continues to use its keyfile to authenticate itself as a member. However, each node can now accept either a keyfile or an x.509 certificate from other members to authenticate those members. Upgrade all nodes of the cluster to this setting. 2. Then, for each node of a cluster, connect to the node and use the setParameter command to update the clusterAuthMode to sendX509. 61 For example, db.getSiblingDB('admin').runCommand({ setParameter: 1, clusterAuthMode: "sendX509"}) With this setting, each node uses its x.509 certificate, specified with the --sslClusterFile option in the previous step, to authenticate itself as a member. However, each node continues to accept either a keyfile or an x.509 certificate from other members to authenticate those members. Upgrade all nodes of the cluster to this setting. 3. Optional but recommended. Finally, for each node of the cluster, connect to the node and use the setParameter command to update the clusterAuthMode to x509 to only use the x.509 certificate for authentication. 1 For example: db.getSiblingDB('admin').runCommand({ setParameter: 1, clusterAuthMode: "x509"}) 4. After the upgrade of all nodes, edit the configuration file with the appropriate x.509 settings to ensure that upon subsequent restarts, the cluster uses x.509 authentication. See --clusterAuthMode for the various modes and their descriptions. Clusters Currently Not Using TLS/SSL For clusters using keyfile authentication but not TLS/SSL, to upgrade to x.509 authentication, use the following rolling upgrade process: 1. For each node of a cluster, start the node with the option --sslMode set to allowSSL, the option --clusterAuthMode set to sendKeyFile and the option --sslClusterFile set to the appropri- ate path of the node’s certificate. Include other TLS/SSL options (page 347) as well as any other options that are required for your specific configuration. For example: mongod --replSet --sslMode allowSSL --clusterAuthMode sendKeyFile --sslClusterFile --sslPEMKeyFile --sslCAFile The --sslMode allowSSL setting allows the node to accept both TLS/SSL and non-TLS/non-SSL incom- ing connections. Its outgoing connections do not use TLS/SSL. The --clusterAuthMode sendKeyFile setting allows each node continues to use its keyfile to authen- ticate itself as a member. However, each node can now accept either a keyfile or an x.509 certificate from other members to authenticate those members. Upgrade all nodes of the cluster to these settings. 2. Then, for each node of a cluster, connect to the node and use the setParameter command to update the sslMode to preferSSL and the clusterAuthMode to sendX509. 1 For example: db.getSiblingDB('admin').runCommand({ setParameter: 1, sslMode: "preferSSL", clusterAuthMode: "sendX509"}) With the sslMode set to preferSSL, the node accepts both TLS/SSL and non-TLS/non-SSL incoming con- nections, and its outgoing connections use TLS/SSL. With the clusterAuthMode set to sendX509, each node uses its x.509 certificate, specified with the --sslClusterFile option in the previous step, to authenticate itself as a member. However, each node continues to accept either a keyfile or an x.509 certificate from other members to authenticate those members. 61 As an alternative to using the setParameter command, you can also restart the nodes with the appropriate TLS/SSL and x509 options and values. 6.3. Security Tutorials 369 MongoDB Documentation, Release 3.0.7 Upgrade all nodes of the cluster to these settings. 3. Optional but recommended. Finally, for each node of the cluster, connect to the node and use the setParameter command to update the sslMode to requireSSL and the clusterAuthMode to x509. 1 For example: db.getSiblingDB('admin').runCommand({ setParameter: 1, sslMode: "requireSSL", clusterAuthMode: "x509"}) With the sslMode set to requireSSL, the node only uses TLS/SSLs connections. With the clusterAuthMode set to x509, the node only uses the x.509 certificate for authentication. 4. After the upgrade of all nodes, edit the configuration file with the appropriate TLS/SSL and x.509 settings to ensure that upon subsequent restarts, the cluster uses x.509 authentication. See --clusterAuthMode for the various modes and their descriptions. Authenticate Using SASL and LDAP with ActiveDirectory MongoDB Enterprise provides support for proxy authentication of users. This allows administrators to configure a MongoDB cluster to authenticate users by proxying authentication requests to a specified Lightweight Directory Access Protocol (LDAP) service. Considerations MongoDB Enterprise for Windows does not include LDAP support for authentication. However, MongoDB Enterprise for Linux supports using LDAP authentication with an ActiveDirectory server. MongoDB does not support LDAP authentication in mixed sharded cluster deployments that contain both version 2.4 and version 2.6 shards. See Upgrade MongoDB to 2.6 (page 877) for upgrade instructions. Use secure encrypted or trusted connections between clients and the server, as well as between saslauthd and the LDAP server. The LDAP server uses the SASL PLAIN mechanism, sending and receiving data in plain text. You should use only a trusted channel such as a VPN, a connection encrypted with TLS/SSL, or a trusted wired network. Configure saslauthd LDAP support for user authentication requires proper configuration of the saslauthd daemon process as well as the MongoDB server. Step 1: Specify the mechanism. On systems that configure saslauthd with the /etc/sysconfig/saslauthd file, such as Red Hat Enterprise Linux, Fedora, CentOS, and Amazon Linux AMI, set the mechanism MECH to ldap: MECH=ldap On systems that configure saslauthd with the /etc/default/saslauthd file, such as Ubuntu, set the MECHANISMS option to ldap: MECHANISMS="ldap" 370 Chapter 6. Security MongoDB Documentation, Release 3.0.7 Step 2: Adjust caching behavior. On certain Linux distributions, saslauthd starts with the caching of authenti- cation credentials enabled. Until restarted or until the cache expires, saslauthd will not contact the LDAP server to re-authenticate users in its authentication cache. This allows saslauthd to successfully authenticate users in its cache, even in the LDAP server is down or if the cached users’ credentials are revoked. To set the expiration time (in seconds) for the authentication cache, see the -t option62 of saslauthd. Step 3: Configure LDAP Options with ActiveDirectory. If the saslauthd.conf file does not exist, create it. The saslauthd.conf file usually resides in the /etc folder. If specifying a different file path, see the -O option63 of saslauthd. To use with ActiveDirectory, start saslauthd with the following configuration options set in the saslauthd.conf file: ldap_servers: ldap_use_sasl: yes ldap_mech: DIGEST-MD5 ldap_auth_method: fastbind For the , specify the uri of the ldap server. For example, ldap_servers: ldaps://ad.example.net. For more information on saslauthd configuration, see http://www.openldap.org/doc/admin24/guide.html#Configuringsaslauthd. Step 4: Test the saslauthd configuration. Use testsaslauthd utility to test the saslauthd configuration. For example: testsaslauthd -u testuser -p testpassword -f /var/run/saslauthd/mux Note: /var/run/saslauthd directory must have permissions set to 755 for MongoDB to successfully authen- ticate. Configure MongoDB Step 1: Add user to MongoDB for authentication. Add the user to the $external database in MongoDB. To specify the user’s privileges, assign roles (page 334) to the user. For example, the following adds a user with read-only access to the records database. db.getSiblingDB("$external").createUser( { user : , roles:[{ role: "read", db: "records"}] } ) Add additional principals as needed. For more information about creating and managing users, see https://docs.mongodb.org/manual/reference/command/nav-user-management. Step 2: Configure MongoDB server. To configure the MongoDB server to use the saslauthd instance for proxy authentication, start the mongod with the following options: •--auth, 62http://www.linuxcommand.org/man_pages/saslauthd8.html 63http://www.linuxcommand.org/man_pages/saslauthd8.html 6.3. Security Tutorials 371 MongoDB Documentation, Release 3.0.7 • authenticationMechanisms parameter set to PLAIN, and • saslauthdPath parameter set to the path to the Unix-domain Socket of the saslauthd instance. Configure the MongoDB server using either the command line option --setParameter or the configuration file. Specify additional configurations as appropriate for your configuration. If you use the authorization option to enforce authentication, you will need privileges to create a user. Use specific saslauthd socket path. For socket path of ///saslauthd, set the saslauthdPath to ///saslauthd/mux, as in the following command line example: mongod --auth --setParameter saslauthdPath=///saslauthd/mux --setParameter authenticationMechanisms=PLAIN Or if using a YAML format configuration file, specify the following settings in the file: security: authorization: enabled setParameter: saslauthdPath: ///saslauthd/mux authenticationMechanisms: PLAIN Or, if using the older configuration file format64: auth=true setParameter=saslauthdPath=///saslauthd/mux setParameter=authenticationMechanisms=PLAIN Use default Unix-domain socket path. To use the default Unix-domain socket path, set the saslauthdPath to the empty string "", as in the following command line example: mongod --auth --setParameter saslauthdPath="" --setParameter authenticationMechanisms=PLAIN Or if using a YAML format configuration file, specify the following settings in the file: security: authorization: enabled setParameter: saslauthdPath:"" authenticationMechanisms: PLAIN Or, if using the older configuration file format65: auth=true setParameter=saslauthdPath="" setParameter=authenticationMechanisms=PLAIN Step 3: Authenticate the user in the mongo shell. To perform the authentication in the mongo shell, use the db.auth() method in the $external database. Specify the value "PLAIN" in the mechanism field, the user and password in the user and pwd fields respectively, and the value false in the digestPassword field. You must specify false for digestPassword since the server must receive an undigested password to forward on to saslauthd, as in the following example: 64https://docs.mongodb.org/v2.4/reference/configuration-options 65https://docs.mongodb.org/v2.4/reference/configuration-options 372 Chapter 6. Security MongoDB Documentation, Release 3.0.7 db.getSiblingDB("$external").auth( { mechanism: "PLAIN", user:, pwd:, digestPassword: false } ) The server forwards the password in plain text. In general, use only on a trusted channel (VPN, TLS/SSL, trusted wired network). See Considerations. Authenticate Using SASL and LDAP with OpenLDAP MongoDB Enterprise provides support for proxy authentication of users. This allows administrators to configure a MongoDB cluster to authenticate users by proxying authentication requests to a specified Lightweight Directory Access Protocol (LDAP) service. Considerations MongoDB Enterprise for Windows does not include LDAP support for authentication. However, MongoDB Enterprise for Linux supports using LDAP authentication with an ActiveDirectory server. MongoDB does not support LDAP authentication in mixed sharded cluster deployments that contain both version 2.4 and version 2.6 shards. See Upgrade MongoDB to 2.6 (page 877) for upgrade instructions. Use secure encrypted or trusted connections between clients and the server, as well as between saslauthd and the LDAP server. The LDAP server uses the SASL PLAIN mechanism, sending and receiving data in plain text. You should use only a trusted channel such as a VPN, a connection encrypted with TLS/SSL, or a trusted wired network. Configure saslauthd LDAP support for user authentication requires proper configuration of the saslauthd daemon process as well as the MongoDB server. Step 1: Specify the mechanism. On systems that configure saslauthd with the /etc/sysconfig/saslauthd file, such as Red Hat Enterprise Linux, Fedora, CentOS, and Amazon Linux AMI, set the mechanism MECH to ldap: MECH=ldap On systems that configure saslauthd with the /etc/default/saslauthd file, such as Ubuntu, set the MECHANISMS option to ldap: MECHANISMS="ldap" Step 2: Adjust caching behavior. On certain Linux distributions, saslauthd starts with the caching of authenti- cation credentials enabled. Until restarted or until the cache expires, saslauthd will not contact the LDAP server to re-authenticate users in its authentication cache. This allows saslauthd to successfully authenticate users in its cache, even in the LDAP server is down or if the cached users’ credentials are revoked. To set the expiration time (in seconds) for the authentication cache, see the -t option66 of saslauthd. 66http://www.linuxcommand.org/man_pages/saslauthd8.html 6.3. Security Tutorials 373 MongoDB Documentation, Release 3.0.7 Step 3: Configure LDAP Options with OpenLDAP. If the saslauthd.conf file does not exist, create it. The saslauthd.conf file usually resides in the /etc folder. If specifying a different file path, see the -O option67 of saslauthd. To connect to an OpenLDAP server, update the saslauthd.conf file with the following configuration options: ldap_servers: ldap_search_base: ldap_filter: The ldap_servers specifies the uri of the LDAP server used for authentication. In general, for OpenLDAP installed on the local machine, you can specify the value ldap://localhost:389 or if using LDAP over TLS/SSL, you can specify the value ldaps://localhost:636. The ldap_search_base specifies distinguished name to which the search is relative. The search includes the base or objects below. The ldap_filter specifies the search filter. The values for these configuration options should correspond to the values specific for your test. For example, to filter on email, specify ldap_filter: (mail=%n) instead. OpenLDAP Example A sample saslauthd.conf file for OpenLDAP includes the following content: ldap_servers: ldaps://ad.example.net ldap_search_base: ou=Users,dc=example,dc=com ldap_filter: (uid=%u) To use this sample OpenLDAP configuration, create users with a uid attribute (login name) and place under the Users organizational unit (ou) under the domain components (dc) example and com. For more information on saslauthd configuration, see http://www.openldap.org/doc/admin24/guide.html#Configuringsaslauthd. Step 4: Test the saslauthd configuration. Use testsaslauthd utility to test the saslauthd configuration. For example: testsaslauthd -u testuser -p testpassword -f /var/run/saslauthd/mux Note: /var/run/saslauthd directory must have permissions set to 755 for MongoDB to successfully authen- ticate. Configure MongoDB Step 1: Add user to MongoDB for authentication. Add the user to the $external database in MongoDB. To specify the user’s privileges, assign roles (page 334) to the user. For example, the following adds a user with read-only access to the records database. db.getSiblingDB("$external").createUser( { user : , roles:[{ role: "read", db: "records"}] } ) 67http://www.linuxcommand.org/man_pages/saslauthd8.html 374 Chapter 6. Security MongoDB Documentation, Release 3.0.7 Add additional principals as needed. For more information about creating and managing users, see https://docs.mongodb.org/manual/reference/command/nav-user-management. Step 2: Configure MongoDB server. To configure the MongoDB server to use the saslauthd instance for proxy authentication, start the mongod with the following options: •--auth, • authenticationMechanisms parameter set to PLAIN, and • saslauthdPath parameter set to the path to the Unix-domain Socket of the saslauthd instance. Configure the MongoDB server using either the command line option --setParameter or the configuration file. Specify additional configurations as appropriate for your configuration. If you use the authorization option to enforce authentication, you will need privileges to create a user. Use specific saslauthd socket path. For socket path of ///saslauthd, set the saslauthdPath to ///saslauthd/mux, as in the following command line example: mongod --auth --setParameter saslauthdPath=///saslauthd/mux --setParameter authenticationMechanisms=PLAIN Or if using a YAML format configuration file, specify the following settings in the file: security: authorization: enabled setParameter: saslauthdPath: ///saslauthd/mux authenticationMechanisms: PLAIN Or, if using the older configuration file format68: auth=true setParameter=saslauthdPath=///saslauthd/mux setParameter=authenticationMechanisms=PLAIN Use default Unix-domain socket path. To use the default Unix-domain socket path, set the saslauthdPath to the empty string "", as in the following command line example: mongod --auth --setParameter saslauthdPath="" --setParameter authenticationMechanisms=PLAIN Or if using a YAML format configuration file, specify the following settings in the file: security: authorization: enabled setParameter: saslauthdPath:"" authenticationMechanisms: PLAIN Or, if using the older configuration file format69: auth=true setParameter=saslauthdPath="" setParameter=authenticationMechanisms=PLAIN 68https://docs.mongodb.org/v2.4/reference/configuration-options 69https://docs.mongodb.org/v2.4/reference/configuration-options 6.3. Security Tutorials 375 MongoDB Documentation, Release 3.0.7 Step 3: Authenticate the user in the mongo shell. To perform the authentication in the mongo shell, use the db.auth() method in the $external database. Specify the value "PLAIN" in the mechanism field, the user and password in the user and pwd fields respectively, and the value false in the digestPassword field. You must specify false for digestPassword since the server must receive an undigested password to forward on to saslauthd, as in the following example: db.getSiblingDB("$external").auth( { mechanism: "PLAIN", user:, pwd:, digestPassword: false } ) The server forwards the password in plain text. In general, use only on a trusted channel (VPN, TLS/SSL, trusted wired network). See Considerations. Configure MongoDB with Kerberos Authentication on Linux New in version 2.4. Overview MongoDB Enterprise supports authentication using a Kerberos service (page 331). Kerberos is an industry standard authentication protocol for large client/server system. Prerequisites Setting up and configuring a Kerberos deployment is beyond the scope of this document. This tutorial assumes you have configured a Kerberos service principal (page 332) for each mongod and mongos instance in your MongoDB deployment, and you have a valid keytab file (page 333) for for each mongod and mongos instance. To verify MongoDB Enterprise binaries: mongod --version In the output from this command, look for the string modules: subscription or modules: enterprise to confirm your system has MongoDB Enterprise. Procedure The following procedure outlines the steps to add a Kerberos user principal to MongoDB, configure a standalone mongod instance for Kerberos support, and connect using the mongo shell and authenticate the user principal. Step 1: Start mongod without Kerberos. For the initial addition of Kerberos users, start mongod without Kerberos support. If a Kerberos user is already in MongoDB and has the privileges required to create a user, you can start mongod with Kerberos support. 376 Chapter 6. Security MongoDB Documentation, Release 3.0.7 Step 2: Connect to mongod. Connect via the mongo shell to the mongod instance. If mongod has --auth enabled, ensure you connect with the privileges required to create a user. Step 3: Add Kerberos Principal(s) to MongoDB. Add a Kerberos principal, @ or /@, to MongoDB in the $external database. Specify the Kerberos realm in all uppercase. The $external database allows mongod to consult an external source (e.g. Kerberos) to authenticate. To specify the user’s privileges, assign roles (page 334) to the user. The following example adds the Kerberos principal application/reporting@EXAMPLE.NET with read-only access to the records database: use $external db.createUser( { user: "application/reporting@EXAMPLE.NET", roles: [ { role: "read", db: "records"}] } ) Add additional principals as needed. For every user you want to authenticate using Kerberos, you must create a corresponding user in MongoDB. For more information about creating and managing users, see https://docs.mongodb.org/manual/reference/command/nav-user-management. Step 4: Start mongod with Kerberos support. To start mongod with Kerberos support, set the environmental variable KRB5_KTNAME to the path of the keytab file and the mongod parameter authenticationMechanisms to GSSAPI in the following form: env KRB5_KTNAME= \ mongod \ --setParameter authenticationMechanisms=GSSAPI For example, the following starts a standalone mongod instance with Kerberos support: env KRB5_KTNAME=/opt/mongodb/mongod.keytab \ /opt/mongodb/bin/mongod --auth \ --setParameter authenticationMechanisms=GSSAPI \ --dbpath /opt/mongodb/data The path to your mongod as well as your keytab file (page 333) may differ. Modify or include additional mongod options as required for your configuration. The keytab file (page 333) must be only accessible to the owner of the mongod process. With the official .deb or .rpm packages, you can set the KRB5_KTNAME in a environment settings file. See KRB5_KTNAME (page 378) for details. Step 5: Connect mongo shell to mongod and authenticate. Connect the mongo shell client as the Kerberos prin- cipal application/reporting@EXAMPLE.NET. Before connecting, you must have used Kerberos’s kinit program to get credentials for application/reporting@EXAMPLE.NET. You can connect and authenticate from the command line. mongo --authenticationMechanism=GSSAPI --authenticationDatabase='$external' \ --username application/reporting@EXAMPLE.NET Or, alternatively, you can first connect mongo to the mongod, and then from the mongo shell, use the db.auth() method to authenticate in the $external database. 6.3. Security Tutorials 377 MongoDB Documentation, Release 3.0.7 use $external db.auth( { mechanism: "GSSAPI", user: "application/reporting@EXAMPLE.NET"}) Additional Considerations KRB5_KTNAME If you installed MongoDB Enterprise using one of the official .deb or .rpm packages, and you use the included init/upstart scripts to control the mongod instance, you can set the KR5_KTNAME variable in the default environment settings file instead of setting the variable each time. For .rpm packages, the default environment settings file is /etc/sysconfig/mongod. For .deb packages, the file is /etc/default/mongodb. Set the KRB5_KTNAME value in a line that resembles the following: export KRB5_KTNAME="" Configure mongos for Kerberos To start mongos with Kerberos support, set the environmen- tal variable KRB5_KTNAME to the path of its keytab file (page 333) and the mongos parameter authenticationMechanisms to GSSAPI in the following form: env KRB5_KTNAME= \ mongos \ --setParameter authenticationMechanisms=GSSAPI \ For example, the following starts a mongos instance with Kerberos support: env KRB5_KTNAME=/opt/mongodb/mongos.keytab \ mongos \ --setParameter authenticationMechanisms=GSSAPI \ --configdb shard0.example.net, shard1.example.net,shard2.example.net \ --keyFile /opt/mongodb/mongos.keyfile The path to your mongos as well as your keytab file (page 333) may differ. The keytab file (page 333) must be only accessible to the owner of the mongos process. Modify or include any additional mongos options as required for your configuration. For example, instead of us- ing --keyFile for internal authentication of sharded cluster members, you can use x.509 member authentication (page 367) instead. Use a Config File To configure mongod or mongos for Kerberos support using a configuration file, specify the authenticationMechanisms setting in the configuration file: If using the YAML configuration file format: setParameter: authenticationMechanisms: GSSAPI Or, if using the older .ini configuration file format: setParameter=authenticationMechanisms=GSSAPI Modify or include any additional mongod options as required for your configuration. For example, if /opt/mongodb/mongod.conf contains the following configuration settings for a standalone mongod: 378 Chapter 6. Security MongoDB Documentation, Release 3.0.7 security: authorization: enabled setParameter: authenticationMechanisms: GSSAPI storage: dbPath: /opt/mongodb/data Or, if using the older configuration file format70: auth= true setParameter=authenticationMechanisms=GSSAPI dbpath=/opt/mongodb/data To start mongod with Kerberos support, use the following form: env KRB5_KTNAME=/opt/mongodb/mongod.keytab \ /opt/mongodb/bin/mongod --config /opt/mongodb/mongod.conf The path to your mongod, keytab file (page 333), and configuration file may differ. The keytab file (page 333) must be only accessible to the owner of the mongod process. Troubleshoot Kerberos Setup for MongoDB If you encounter problems when starting mongod or mongos with Kerberos authentication, see Troubleshoot Kerberos Authentication on Linux (page 383). Incorporate Additional Authentication Mechanisms Kerberos authentication (GSSAPI (page 328) (Kerberos)) can work alongside MongoDB’s challenge/response authentication mechanisms (SCRAM-SHA-1 (page 327) and MONGODB-CR (page 328)), MongoDB’s authentication mechanism for LDAP (PLAIN (page 328) (LDAP SASL)), and MongoDB’s authentication mechanism for x.509 ( MONGODB-X509 (page 328)). Specify the mechanisms as follows: --setParameter authenticationMechanisms=GSSAPI,SCRAM-SHA-1 Only add the other mechanisms if in use. This parameter setting does not affect MongoDB’s internal authentication of cluster members. Additional Resources • MongoDB LDAP and Kerberos Authentication with Dell (Quest) Authentication Services71 • MongoDB with Red Hat Enterprise Linux Identity Management and Kerberos72 Configure MongoDB with Kerberos Authentication on Windows New in version 2.6. Overview MongoDB Enterprise supports authentication using a Kerberos service (page 331). Kerberos is an industry standard authentication protocol for large client/server system. Kerberos allows MongoDB and applications to take advantage of existing authentication infrastructure and processes. 70https://docs.mongodb.org/v2.4/reference/configuration-options 71https://www.mongodb.com/blog/post/mongodb-ldap-and-kerberos-authentication-dell-quest-authentication-services?jmp=docs 72http://docs.mongodb.org/ecosystem/tutorial/manage-red-hat-enterprise-linux-identity-management?jmp=docs 6.3. Security Tutorials 379 MongoDB Documentation, Release 3.0.7 Prerequisites Setting up and configuring a Kerberos deployment is beyond the scope of this document. This tutorial assumes have configured a Kerberos service principal (page 332) for each mongod.exe and mongos.exe instance. Procedures Step 1: Start mongod.exe without Kerberos. For the initial addition of Kerberos users, start mongod.exe without Kerberos support. If a Kerberos user is already in MongoDB and has the privileges required to create a user, you can start mongod.exe with Kerberos support. Step 2: Connect to mongod. Connect via the mongo.exe shell to the mongod.exe instance. If mongod.exe has --auth enabled, ensure you connect with the privileges required to create a user. Step 3: Add Kerberos Principal(s) to MongoDB. Add a Kerberos principal, @, to MongoDB in the $external database. Specify the Kerberos realm in ALL UPPERCASE. The $external database allows mongod.exe to consult an external source (e.g. Kerberos) to authenticate. To specify the user’s privileges, assign roles (page 334) to the user. The following example adds the Kerberos principal reportingapp@EXAMPLE.NET with read-only access to the records database: use $external db.createUser( { user: "reportingapp@EXAMPLE.NET", roles: [ { role: "read", db: "records"}] } ) Add additional principals as needed. For every user you want to authenticate using Kerberos, you must create a corresponding user in MongoDB. For more information about creating and managing users, see https://docs.mongodb.org/manual/reference/command/nav-user-management. Step 4: Start mongod.exe with Kerberos support. You must start mongod.exe as the service principal ac- count (page 381). To start mongod.exe with Kerberos support, set the mongod.exe parameter authenticationMechanisms to GSSAPI: mongod.exe --setParameter authenticationMechanisms=GSSAPI For example, the following starts a standalone mongod.exe instance with Kerberos support: mongod.exe --auth --setParameter authenticationMechanisms=GSSAPI Modify or include additional mongod.exe options as required for your configuration. Step 5: Connect mongo.exe shell to mongod.exe and authenticate. Connect the mongo.exe shell client as the Kerberos principal application@EXAMPLE.NET. You can connect and authenticate from the command line. 380 Chapter 6. Security MongoDB Documentation, Release 3.0.7 mongo.exe --authenticationMechanism=GSSAPI --authenticationDatabase='$external' \ --username reportingapp@EXAMPLE.NET Or, alternatively, you can first connect mongo.exe to the mongod.exe, and then from the mongo.exe shell, use the db.auth() method to authenticate in the $external database. use $external db.auth( { mechanism: "GSSAPI", user: "reportingapp@EXAMPLE.NET"}) Additional Considerations Configure mongos.exe for Kerberos To start mongos.exe with Kerberos support, set the mongos.exe pa- rameter authenticationMechanisms to GSSAPI. You must start mongos.exe as the service principal ac- count (page 381).: mongos.exe --setParameter authenticationMechanisms=GSSAPI For example, the following starts a mongos instance with Kerberos support: mongos.exe --setParameter authenticationMechanisms=GSSAPI --configdb shard0.example.net, shard1.example.net,shard2.example.net --keyFile C:\\mongos.keyfile Modify or include any additional mongos.exe options as required for your configuration. For example, instead of using --keyFile for internal authentication of sharded cluster members, you can use x.509 member authentication (page 367) instead. Assign Service Principal Name to MongoDB Windows Service Use setspn.exe to assign the service principal name (SPN) to the account running the mongod.exe and the mongos.exe service: setspn.exe -A / For example, if mongod.exe runs as a service named mongodb on testserver.mongodb.com with the ser- vice account name mongodtest, assign the SPN as follows: setspn.exe -A mongodb/testserver.mongodb.com mongodtest Incorporate Additional Authentication Mechanisms Kerberos authentication (GSSAPI (page 328) (Kerberos)) can work alongside MongoDB’s challenge/response authentication mechanisms (SCRAM-SHA-1 (page 327) and MONGODB-CR (page 328)), MongoDB’s authentication mechanism for LDAP (PLAIN (page 328) (LDAP SASL)), and MongoDB’s authentication mechanism for x.509 ( MONGODB-X509 (page 328)). Specify the mechanisms as follows: --setParameter authenticationMechanisms=GSSAPI,SCRAM-SHA-1 Only add the other mechanisms if in use. This parameter setting does not affect MongoDB’s internal authentication of cluster members. Authenticate to a MongoDB Instance or Cluster Overview To authenticate to a running mongod or mongos instance, you must have user credentials for a resource on that instance. When you authenticate to MongoDB, you authenticate either to a database or to a cluster. Your user privileges determine the resource you can authenticate to. 6.3. Security Tutorials 381 MongoDB Documentation, Release 3.0.7 You authenticate to a resource either by: • using the authentication options when connecting to the mongod or mongos instance, or • connecting first and then authenticating to the resource with the authenticate command or the db.auth() method. This section describes both approaches. In general, always use a trusted channel (VPN, TLS/SSL, trusted wired network) for connecting to a MongoDB instance. Prerequisites You must have user credentials on the database or cluster to which you are authenticating. Procedures Authenticate When First Connecting to MongoDB Step 1: Specify your credentials when starting the mongo instance. When using mongo to connect to a mongod or mongos, enter your username, password, and authenticationDatabase. For example: mongo--username "prodManager"--password "cleartextPassword"--authenticationDatabase "products" Step 2: Close the session when your work is complete. To close an authenticated session, use the logout com- mand.: db.runCommand( { logout:1}) Authenticate After Connecting to MongoDB Step 1: Connect to a MongoDB instance. Connect to a mongod or mongos instance. Step 2: Switch to the database to which to authenticate. use Step 3: Authenticate. Use either the authenticate command or the db.auth() method to provide your username and password to the database. For example: db.auth( "prodManager", "cleartextPassword") Step 4: Close the session when your work is complete. To close an authenticated session, use the logout com- mand.: db.runCommand( { logout:1}) 382 Chapter 6. Security MongoDB Documentation, Release 3.0.7 Generate a Key File Overview This section describes how to generate a key file to store authentication information. After generating a key file, specify the key file using the keyFile option when starting a mongod or mongos instance. A key’s length must be between 6 and 1024 characters and may only contain characters in the base64 set. The key file must not have group or world permissions on UNIX systems. Key file permissions are not checked on Windows systems. MongoDB strips whitespace characters (e.g. x0d, x09, and x20) for cross-platform convenience. As a result, the following operations produce identical keys: echo -e "my secret key" > key1 echo -e "my secret key\n" > key2 echo -e "my secret key" > key3 echo -e "my\r\nsecret\r\nkey\r\n" > key4 Procedure Step 1: Create a key file. Create the key file your deployment will use to authenticate servers to each other. To generate pseudo-random data to use for a keyfile, issue the following openssl command: openssl rand -base64 741 > mongodb-keyfile chmod 600 mongodb-keyfile You may generate a key file using any method you choose. Always ensure that the password stored in the key file is both long and contains a high amount of entropy. Using openssl in this manner helps generate such a key. Step 2: Specify the key file when starting a MongoDB instance. Specify the path to the key file with the keyFile option. Troubleshoot Kerberos Authentication on Linux New in version 2.4. Kerberos Configuration Checklist If you have difficulty starting mongod or mongos with Kerberos (page 331) on Linux systems, ensure that: • The mongod and the mongos binaries are from MongoDB Enterprise. To verify MongoDB Enterprise binaries: mongod --version In the output from this command, look for the string modules: subscription or modules: enterprise to confirm your system has MongoDB Enterprise. • You are not using the HTTP Console73. MongoDB Enterprise does not support Kerberos authentication over the HTTP Console interface. 73https://docs.mongodb.org/ecosystem/tools/http-interface/#http-console 6.3. Security Tutorials 383 MongoDB Documentation, Release 3.0.7 • Either the service principal name (SPN) in the keytab file (page 333) matches the SPN for the mongod or mongos instance, or the mongod or the mongos instance use the --setParameter saslHostName= to match the name in the keytab file. • The canonical system hostname of the system that runs the mongod or mongos instance is a resolvable, fully qualified domain for this host. You can test the system hostname resolution with the hostname -f command at the system prompt. • Each host that runs a mongod or mongos instance has both the A and PTR DNS records to provide forward and reverse lookup. The records allow the host to resolve the components of the Kerberos infrastructure. • Both the Kerberos Key Distribution Center (KDC) and the system running mongod instance or mongos must be able to resolve each other using DNS. By default, Kerberos attempts to resolve hosts using the content of the /etc/kerb5.conf before using DNS to resolve hosts. • The time synchronization of the systems running mongod or the mongos instances and the Kerberos infras- tructure are within the maximum time skew (default is 5 minutes) of each other. Time differences greater than the maximum time skew will prevent successful authentication. Debug with More Verbose Logs If you still encounter problems with Kerberos on Linux, you can start both mongod and mongo (or another client) with the environment variable KRB5_TRACE set to different files to produce more verbose logging of the Kerberos process to help further troubleshooting. For example, the following starts a standalone mongod with KRB5_TRACE set: env KRB5_KTNAME=/opt/mongodb/mongod.keytab \ KRB5_TRACE=/opt/mongodb/log/mongodb-kerberos.log \ /opt/mongodb/bin/mongod --dbpath /opt/mongodb/data \ --fork --logpath /opt/mongodb/log/mongod.log \ --auth --setParameter authenticationMechanisms=GSSAPI Common Error Messages In some situations, MongoDB will return error messages from the GSSAPI interface if there is a problem with the Kerberos service. Some common error messages are: GSSAPI error in client while negotiating security context. This error occurs on the client and reflects insufficient credentials or a malicious attempt to authenticate. If you receive this error, ensure that you are using the correct credentials and the correct fully qualified domain name when connecting to the host. GSSAPI error acquiring credentials. This error occurs during the start of the mongod or mongos and reflects improper configuration of the system hostname or a missing or incorrectly configured keytab file. If you encounter this problem, consider the items in the Kerberos Configuration Checklist (page 383), in partic- ular, whether the SPN in the keytab file (page 333) matches the SPN for the mongod or mongos instance. To determine whether the SPNs match: 1. Examine the keytab file, with the following command: klist -k Replace with the path to your keytab file. 2. Check the configured hostname for your system, with the following command: 384 Chapter 6. Security MongoDB Documentation, Release 3.0.7 hostname -f Ensure that this name matches the name in the keytab file, or start mongod or mongos with the --setParameter saslHostName=. See also: • Kerberos Authentication (page 331) • Configure MongoDB with Kerberos Authentication on Linux (page 376) • Configure MongoDB with Kerberos Authentication on Windows (page 379) Implement Field Level Redaction The $redact pipeline operator restricts the contents of the documents based on information stored in the documents themselves. To store the access criteria data, add a field to the documents and embedded documents. To allow for multiple com- binations of access levels for the same data, consider setting the access field to an array of arrays. Each array element contains a required set that allows a user with that set to access the data. Then, include the $redact stage in the db.collection.aggregate() operation to restrict contents of the result set based on the access required to view the data. For more information on the $redact pipeline operator, including its syntax and associated system variables as well as additional examples, see $redact. 6.3. Security Tutorials 385 MongoDB Documentation, Release 3.0.7 Procedure For example, a forecasts collection contains documents of the following form where the tags field determines the access levels required to view the data: { _id:1, title: "123 Department Report", tags:[[ "G"],[ "FDW"]], year: 2014, subsections:[ { subtitle: "Section 1: Overview", tags:[[ "SI", "G"],[ "FDW"]], content: "Section 1: This is the content of section 1." }, { subtitle: "Section 2: Analysis", tags:[[ "STLW"]], content: "Section 2: This is the content of section 2." }, { subtitle: "Section 3: Budgeting", tags:[[ "TK"],[ "FDW", "TGE"]], content:{ text: "Section 3: This is the content of section3.", tags:[[ "HCS"], [ "FDW", "TGE", "BX"]] } } ] } For each document, the tags field contains various access groupings necessary to view the data. For example, the value [ [ "G" ], [ "FDW", "TGE" ] ] can specify that a user requires either access level ["G"] or both [ "FDW", "TGE" ] to view the data. Consider a user who only has access to view information tagged with either "FDW" or "TGE". To run a query on all documents with year 2014 for this user, include a $redact stage as in the following: var userAccess = [ "FDW", "TGE" ]; db.forecasts.aggregate( [ { $match: { year: 2014 } }, { $redact: { $cond: { if: { $anyElementTrue: { $map: { input: "$tags" , as: "fieldTag", in: { $setIsSubset: [ "$$fieldTag", userAccess ] } } } }, then: "$$DESCEND", else: "$$PRUNE" } } 386 Chapter 6. Security MongoDB Documentation, Release 3.0.7 } ] ) The aggregation operation returns the following “redacted” document for the user: { "_id" : 1, "title" : "123 Department Report", "tags" : [ [ "G" ], [ "FDW" ] ], "year" : 2014, "subsections" : [ { "subtitle" : "Section 1: Overview", "tags" : [ [ "SI", "G" ], [ "FDW" ] ], "content" : "Section 1: This is the content of section 1." }, { "subtitle" : "Section 3: Budgeting", "tags" : [ [ "TK" ], [ "FDW", "TGE" ] ] } ] } See also: $map, $setIsSubset, $anyElementTrue 6.3.4 User and Role Management Tutorials The following tutorials provide instructions on how to enable authentication and limit access for users with privilege roles. Create a User Administrator (page 387) Create users with special permissions to create, modify, and remove other users, as well as administer authentication credentials (e.g. passwords). Manage User and Roles (page 389) Manage users by creating new users, creating new roles, and modifying existing users. Change Your Password and Custom Data (page 395) Users with sufficient access can change their own passwords and modify the optional custom data associated with their user credential. Create an Administrative User with Unrestricted Access (page 397) Create a user with unrestricted access. Create such a user only in unique situations. In general, all users in the system should have no more access than needed to perform their required operations. Create a User Administrator Overview User administrators create users and create and assigns roles. A user administrator can grant any privilege in the database and can create new ones. In a MongoDB deployment, create the user administrator as the first user. Then let this user create all other users. To provide user administrators, MongoDB has userAdmin (page 408) and userAdminAnyDatabase (page 412) roles, which grant access to actions (page 419) that support user and role management. Following the policy of least privilege userAdmin (page 408) and userAdminAnyDatabase (page 412) confer no additional privileges. 6.3. Security Tutorials 387 MongoDB Documentation, Release 3.0.7 Carefully control access to these roles. A user with either of these roles can grant itself unlimited additional privileges. Specifically, a user with the userAdmin (page 408) role can grant itself any privilege in the database. A user assigned either the userAdmin (page 408) role on the admin database or the userAdminAnyDatabase (page 412) can grant itself any privilege in the system. Prerequisites Required Access • To create a new user in a database, you must have createUser (page 420) action (page 419) on that database resource (page 418). • To grant roles to a user, you must have the grantRole (page 421) action (page 419) on the role’s database. Built-in roles userAdmin (page 408) and userAdminAnyDatabase (page 412) provide createUser (page 420) and grantRole (page 421) actions on their respective resources (page 418). First User Restrictions If your MongoDB deployment has no users, you must connect to mongod using the local- host exception (page 329) or use the --noauth option when starting mongod to gain full access the system. Once you have access, you can skip to Creating the system user administrator in this procedure. If users exist in the MongoDB database, but none of them has the appropriate prerequisites to create a new user or you do not have access to them, you must restart mongod with the --noauth option. Procedure Step 1: Connect to MongoDB with the appropriate privileges. Connect to mongod or mongos either through the localhost exception (page 329) or as a user with the privileges indicated in the prerequisites section. In the following example, manager has the required privileges specified in Prerequisites (page 388). mongo--port 27017-u manager-p 123456--authenticationDatabase admin Step 2: Create the system user administrator. Add the user with the userAdminAnyDatabase (page 412) role, and only that role. The following example creates the user siteUserAdmin user on the admin database: use admin db.createUser( { user: "siteUserAdmin", pwd: "password", roles: [ { role: "userAdminAnyDatabase", db: "admin"}] } ) Step 3: Create a user administrator for a single database. Optionally, you may want to create user administrators that only have access to administer users in a specific database by way of the userAdmin (page 408) role. The following example creates the user recordsUserAdmin on the records database: 388 Chapter 6. Security MongoDB Documentation, Release 3.0.7 use records db.createUser( { user: "recordsUserAdmin", pwd: "password", roles: [ { role: "userAdmin", db: "records"}] } ) Related Documents • Authentication (page 326) • Security Introduction (page 323) • Enable Client Access Control (page 360) • Authentication Tutorials (page 360) Additional Resources • Security Architecture White Paper74 • Webinar: Securing Your MongoDB Deployment75 • Creating a Single View Part 3: Securing Your Deployment76 Manage User and Roles Overview Changed in version 2.6: MongoDB 2.6 introduces a new authorization model (page 334). MongoDB employs Role-Based Access Control (RBAC) to determine access for users. A user is granted one or more roles (page 334) that determine the user’s access or privileges to MongoDB resources (page 418) and the actions (page 419) that user can perform. A user should have only the minimal set of privileges required to ensure a system of least privilege. Each application and user of a MongoDB system should map to a distinct application or administrator. This access isolation facilitates access revocation and ongoing user maintenance. This tutorial provides examples for user and role management under the MongoDB’s authorization model. Prerequisites Important: If you have enabled authorization (page 334) for your deployment, you must authenticate as a user with the required privileges specified in each section. A user administrator (page 387) with the userAdminAnyDatabase (page 412) role, or userAdmin (page 408) role in the specific databases, provides the required privileges to perform the operations listed in this tutorial. If you have not yet created a user administrator, do so as described in Create a User Administrator (page 387). 74https://www.mongodb.com/lp/white-paper/mongodb-security-architecture?jmp=docs 75http://www.mongodb.com/webinar/securing-your-mongodb-deployment?jmp=docs 76https://www.mongodb.com/presentations/creating-single-view-part-3-securing-your-deployment?jmp=docs 6.3. Security Tutorials 389 MongoDB Documentation, Release 3.0.7 Add a User To create a user, specify the user name, password, and roles (page 334). For users that authenticate using external mechanisms 77, you do not need to provide the password when creating users. When assigning roles, select the roles that have the exact required privileges (page 335). If the correct roles does not exist, you can create new roles (page 391). Prerequisites • To create a new user in a database, you must have createUser (page 420) action (page 419) on that database resource (page 418). • To grant roles to a user, you must have the grantRole (page 421) action (page 419) on the role’s database. Built-in roles userAdmin (page 408) and userAdminAnyDatabase (page 412) provide createUser (page 420) and grantRole (page 421) actions on their respective resources (page 418). Procedure Step 1: Connect to MongoDB with the appropriate privileges. Connect to mongod or mongos as a user with the privileges specified in the prerequisite section. The following procedure uses the siteUserAdmin created in Create a User Administrator (page 387). mongo--port 27017-u siteUserAdmin-p password--authenticationDatabase admin Step 2: Create the new user. Create the user in the database to which the user will belong. Pass a well formed user document to the db.createUser() method. The following operation creates a user in the reporting database with the specified name, password, and roles. use reporting db.createUser( { user: "reportsUser", pwd: "12345678", roles:[ { role: "read", db: "reporting"}, { role: "read", db: "products"}, { role: "read", db: "sales"}, { role: "readWrite", db: "accounts"} ] } ) To authenticate the reportsUser, you must authenticate the user in the reporting database; i.e. specify --authenticationDatabase reporting. You can create a user without assigning roles, choosing instead to assign the roles later. To do so, create the user with an empty roles (page 417) array. 77 See x.509 Certificate Authentication (page 328), Kerberos Authentication (page 328), and LDAP Proxy Authority Authentication (page 328) 390 Chapter 6. Security MongoDB Documentation, Release 3.0.7 Create a User-Defined Role Roles grant users access to MongoDB resources. MongoDB provides a number of built-in roles (page 406) that administrators can use to control access to a MongoDB system. However, if these roles cannot describe the desired set of privileges, you can create new roles in a particular database. Except for roles created in the admin database, a role can only include privileges that apply to its database and can only inherit from other roles in its database. A role created in the admin database can include privileges that apply to the admin database, other databases or to the cluster (page 419) resource, and can inherit from roles in other databases as well as the admin database. To create a new role, use the db.createRole() method, specifying the privileges in the privileges array and the inherited roles in the roles array. MongoDB uses the combination of the database name and the role name to uniquely define a role. Each role is scoped to the database in which you create the role, but MongoDB stores all role information in the admin.system.roles (page 297) collection in the admin database. Prerequisites To create a role in a database, you must have: • the createRole (page 420) action (page 419) on that database resource (page 418). • the grantRole (page 421) action (page 419) on that database to specify privileges for the new role as well as to specify roles to inherit from. Built-in roles userAdmin (page 408) and userAdminAnyDatabase (page 412) provide createRole (page 420) and grantRole (page 421) actions on their respective resources (page 418). Create a Role to Manage Current Operations The following example creates a role named manageOpRole which provides only the privileges to run both db.currentOp() and db.killOp(). 78 Step 1: Connect to MongoDB with the appropriate privileges. Connect to mongod or mongos with the privi- leges specified in the Prerequisites (page 391) section. The following procedure uses the siteUserAdmin created in Create a User Administrator (page 387). mongo--port 27017-u siteUserAdmin-p password--authenticationDatabase admin The siteUserAdmin has privileges to create roles in the admin as well as other databases. Step 2: Create a new role to manage current operations. manageOpRole has privileges that act on multiple databases as well as the cluster resource (page 419). As such, you must create the role in the admin database. use admin db.createRole( { role: "manageOpRole", privileges:[ { resource: { cluster: true }, actions:[ "killop", "inprog"]}, { resource: { db:"", collection:"" }, actions:[ "killCursors"]} ], roles:[] } ) 78 The built-in role clusterMonitor (page 409) also provides the privilege to run db.currentOp() along with other privileges, and the built-in role hostManager (page 410) provides the privilege to run db.killOp() along with other privileges. 6.3. Security Tutorials 391 MongoDB Documentation, Release 3.0.7 The new role grants permissions to kill any operations. Warning: Terminate running operations with extreme caution. Only use db.killOp() to terminate operations initiated by clients and do not terminate internal database operations. Create a Role to Run mongostat The following example creates a role named mongostatRole that provides only the privileges to run mongostat. 79 Step 1: Connect to MongoDB with the appropriate privileges. Connect to mongod or mongos with the privi- leges specified in the Prerequisites (page 391) section. The following procedure uses the siteUserAdmin created in Create a User Administrator (page 387). mongo--port 27017-u siteUserAdmin-p password--authenticationDatabase admin The siteUserAdmin has privileges to create roles in the admin as well as other databases. Step 2: Create a new role to manage current operations. mongostatRole has privileges that act on the cluster resource (page 419). As such, you must create the role in the admin database. use admin db.createRole( { role: "mongostatRole", privileges:[ { resource: { cluster: true }, actions:[ "serverStatus"]} ], roles:[] } ) Modify Access for Existing User Prerequisites • You must have the grantRole (page 421) action (page 419) on a database to grant a role on that database. • You must have the revokeRole (page 421) action (page 419) on a database to revoke a role on that database. • To view a role’s information, you must be either explicitly granted the role or must have the viewRole (page 421) action (page 419) on the role’s database. Procedure Step 1: Connect to MongoDB with the appropriate privileges. Connect to mongod or mongos as a user with the privileges specified in the prerequisite section. The following procedure uses the siteUserAdmin created in Create a User Administrator (page 387). mongo--port 27017-u siteUserAdmin-p password--authenticationDatabase admin 79 The built-in role clusterMonitor (page 409) also provides the privilege to run mongostat along with other privileges. 392 Chapter 6. Security MongoDB Documentation, Release 3.0.7 Step 2: Identify the user’s roles and privileges. To display the roles and privileges of the user to be modified, use the db.getUser() and db.getRole() methods. For example, to view roles for reportsUser created in Add a User (page 390), issue: use reporting db.getUser("reportsUser") To display the privileges granted to the user by the readWrite role on the "accounts" database, issue: use accounts db.getRole( "readWrite", { showPrivileges: true }) Step 3: Identify the privileges to grant or revoke. If the user requires additional privileges, grant to the user the role, or roles, with the required set of privileges. If such a role does not exist, create a new role (page 391) with the appropriate set of privileges. To revoke a subset of privileges provided by an existing role: revoke the original role and grant a role that contains only the required privileges. You may need to create a new role (page 391) if a role does not exist. Step 4: Modify the user’s access. Revoke a Role Revoke a role with the db.revokeRolesFromUser() method. The following example opera- tion removes the readWrite (page 406) role on the accounts database from the reportsUser: use reporting db.revokeRolesFromUser( "reportsUser", [ { role: "readWrite", db: "accounts"} ] ) Grant a Role Grant a role using the db.grantRolesToUser() method. For example, the following operation grants the reportsUser user the read (page 406) role on the accounts database: use reporting db.grantRolesToUser( "reportsUser", [ { role: "read", db: "accounts"} ] ) For sharded clusters, the changes to the user are instant on the mongos on which the command runs. How- ever, for other mongos instances in the cluster, the user cache may wait up to 10 minutes to refresh. See userCacheInvalidationIntervalSecs. Modify Password for Existing User Prerequisites To modify the password of another user on a database, you must have the changeAnyPassword action (page 419) on that database. Procedure 6.3. Security Tutorials 393 MongoDB Documentation, Release 3.0.7 Step 1: Connect to MongoDB with the appropriate privileges. Connect to the mongod or mongos with the privileges specified in the Prerequisites (page 393) section. The following procedure uses the siteUserAdmin created in Create a User Administrator (page 387). mongo--port 27017-u siteUserAdmin-p password--authenticationDatabase admin Step 2: Change the password. Pass the user’s username and the new password to the db.changeUserPassword() method. The following operation changes the reporting user’s password to SOh3TbYhxuLiW8ypJPxmt1oOfL: db.changeUserPassword("reporting", "SOh3TbYhxuLiW8ypJPxmt1oOfL") See also: Change Your Password and Custom Data (page 395) View a User’s Role Prerequisites To view another user’s information, you must have the viewUser (page 421) action (page 419) on the other user’s database. Users can view their own information. Procedure Step 1: Connect to MongoDB with the appropriate privileges. Connect to mongod or mongos as a user with the privileges specified in the prerequisite section. The following procedure uses the siteUserAdmin created in Create a User Administrator (page 387). mongo--port 27017-u siteUserAdmin-p password--authenticationDatabase admin Step 2: Identify the user’s roles. Use the usersInfo command or db.getUser() method to display user information. For example, to view roles for reportsUser created in Add a User (page 390), issue: use reporting db.getUser("reportsUser") In the returned document, the roles (page 417) field displays all roles for reportsUser: ... "roles":[ { "role": "readWrite", "db": "accounts"}, { "role": "read", "db": "reporting"}, { "role": "read", "db": "products"}, { "role": "read", "db": "sales"} ] View Role’s Privileges Prerequisites To view a role’s information, you must be either explicitly granted the role or must have the viewRole (page 421) action (page 419) on the role’s database. 394 Chapter 6. Security MongoDB Documentation, Release 3.0.7 Procedure Step 1: Connect to MongoDB with the appropriate privileges. Connect to mongod or mongos as a user with the privileges specified in the prerequisite section. The following procedure uses the siteUserAdmin created in Create a User Administrator (page 387). mongo--port 27017-u siteUserAdmin-p password--authenticationDatabase admin Step 2: Identify the privileges granted by a role. For a given role, use the db.getRole() method, or the rolesInfo command, with the showPrivileges option: For example, to view the privileges granted by read role on the products database, use the following operation, issue: use products db.getRole( "read", { showPrivileges: true }) In the returned document, the privileges and inheritedPrivileges arrays. The privileges lists the privileges directly specified by the role and excludes those privileges inherited from other roles. The inheritedPrivileges lists all privileges granted by this role, both directly specified and inherited. If the role does not inherit from other roles, the two fields are the same. ... "privileges":[ { "resource":{ "db": "products", "collection":""}, "actions":[ "collStats","dbHash","dbStats","find","killCursors","planCacheRead"] }, { "resource":{ "db": "products", "collection": "system.js"}, "actions":[ "collStats","dbHash","dbStats","find","killCursors","planCacheRead"] } ], "inheritedPrivileges":[ { "resource":{ "db": "products", "collection":""}, "actions":[ "collStats","dbHash","dbStats","find","killCursors","planCacheRead"] }, { "resource":{ "db": "products", "collection": "system.js"}, "actions":[ "collStats","dbHash","dbStats","find","killCursors","planCacheRead"] } ] Change Your Password and Custom Data Changed in version 2.6. Overview Users with appropriate privileges can change their own passwords and custom data. Custom data (page 417) stores optional user information. 6.3. Security Tutorials 395 MongoDB Documentation, Release 3.0.7 Considerations To generate a strong password for use in this procedure, you can use the openssl utility’s rand command. For example, issue openssl rand with the following options to create a base64-encoded string of 48 pseudo-random bytes: openssl rand -base64 48 Prerequisites To modify your own password and custom data, you must have privileges that grant changeOwnPassword (page 420) and changeOwnCustomData (page 420) actions (page 419) respectively on the user’s database. Step 1: Connect as a user with privileges to manage users and roles. Connect to the mongod or mongos with privileges to manage users and roles, such as a user with userAdminAnyDatabase (page 412) role. The following procedure uses the siteUserAdmin created in Create a User Administrator (page 387). mongo--port 27017-u siteUserAdmin-p password--authenticationDatabase admin Step 2: Create a role with appropriate privileges. In the admin database, create a new role with changeOwnPassword (page 420) and changeOwnCustomData (page 420). use admin db.createRole( { role: "changeOwnPasswordCustomDataRole", privileges:[ { resource: { db:"", collection:""}, actions:[ "changeOwnPassword", "changeOwnCustomData"] } ], roles:[] } ) Step 3: Add a user with this role. In the test database, create a new user with the created "changeOwnPasswordCustomDataRole" role. For example, the following operation creates a user with both the built-in role readWrite (page 406) and the user-created "changeOwnPasswordCustomDataRole". use test db.createUser( { user:"user123", pwd:"12345678", roles:[ "readWrite", { role:"changeOwnPasswordCustomDataRole", db:"admin"}] } ) To grant an existing user the new role, use db.grantRolesToUser(). Procedure 396 Chapter 6. Security MongoDB Documentation, Release 3.0.7 Step 1: Connect with the appropriate privileges. Connect to the mongod or mongos as a user with appropriate privileges. For example, the following operation connects to MongoDB as user123 created in the Prerequisites (page 396) section. mongo--port 27017-u user123-p 12345678--authenticationDatabase test To check that you have the privileges specified in the Prerequisites (page 396) section as well as to see user information, use the usersInfo command with the showPrivileges option. Step 2: Change your password and custom data. Use the db.updateUser() method to update the password and custom data. For example, the following operation changes thw user’s password to KNlZmiaNUp0B and custom data to { title: "Senior Manager" }: use test db.updateUser( "user123", { pwd: "KNlZmiaNUp0B", customData: { title: "Senior Manager"} } ) Create an Administrative User with Unrestricted Access Overview Most users should have only the minimal set of privileges required for their operations, in keeping with the policy of least privilege. However, some authorization architectures may require a user with unrestricted access. To support these super users, you can create users with access to all database resources (page 418) and actions (page 419). For many deployments, you may be able to avoid having any users with unrestricted access by having an administrative user with the createUser (page 420) and grantRole (page 421) actions granted as needed to support operations. If users truly need unrestricted access to a MongoDB deployment, MongoDB provides a built-in role (page 406) named root (page 413) that grants the combined privileges of all built-in roles. This document describes how to create an administrative user with the root (page 413) role. For descriptions of the access each built-in role provides, see the section on built-in roles (page 406). Prerequisites Required Access • To create a new user in a database, you must have createUser (page 420) action (page 419) on that database resource (page 418). • To grant roles to a user, you must have the grantRole (page 421) action (page 419) on the role’s database. Built-in roles userAdmin (page 408) and userAdminAnyDatabase (page 412) provide createUser (page 420) and grantRole (page 421) actions on their respective resources (page 418). 6.3. Security Tutorials 397 MongoDB Documentation, Release 3.0.7 First User Restrictions If your MongoDB deployment has no users, you must connect to mongod using the local- host exception (page 329) or use the --noauth option when starting mongod to gain full access the system. Once you have access, you can skip to Creating the system user administrator in this procedure. If users exist in the MongoDB database, but none of them has the appropriate prerequisites to create a new user or you do not have access to them, you must restart mongod with the --noauth option. Procedure Step 1: Connect to MongoDB with the appropriate privileges. Connect to the mongod or mongos as a user with the privileges specified in the Prerequisites (page 397) section. The following procedure uses the siteUserAdmin created in Create a User Administrator (page 387). mongo--port 27017-u siteUserAdmin-p password--authenticationDatabase admin Step 2: Create the administrative user. In the admin database, create a new user using the db.createUser() method. Give the user the built-in root (page 413) role. For example: use admin db.createUser( { user: "superuser", pwd: "12345678", roles:[ "root"] } ) Authenticate against the admin database to test the new user account. Use db.auth() while using the admin database or use the mongo shell with the --authenticationDatabase option. 6.3.5 Auditing Tutorials The following tutorials provide instructions on how to enable auditing for system events and specify which events to audit. Configure System Events Auditing (page 398) Enable and configure MongoDB Enterprise system event auditing fea- ture. Configure Audit Filters (page 400) Specify which events to audit. Configure System Events Auditing New in version 2.6. MongoDB Enterprise80 supports auditing (page 337) of various operations. A complete auditing solution must involve all mongod server and mongos router processes. The audit facility can write audit events to the console, the syslog (option is unavailable on Windows), a JSON file, or a BSON file. For details on the audited operations and the audit log messages, see System Event Audit Messages (page 425). 80https://www.mongodb.com/products/mongodb-enterprise-advanced?jmp=docs 398 Chapter 6. Security MongoDB Documentation, Release 3.0.7 Enable and Configure Audit Output Use the --auditDestination option to enable auditing and specify where to output the audit events. Warning: For sharded clusters, if you enable auditing on mongos instances, you must enable auditing on all mongod instances in the cluster, i.e. shards and config servers. Output to Syslog To enable auditing and print audit events to the syslog (option is unavailable on Windows) in JSON format, specify syslog for the --auditDestination setting. For example: mongod --dbpath data/db --auditDestination syslog Warning: The syslog message limit can result in the truncation of the audit messages. The auditing system will neither detect the truncation nor error upon its occurrence. You may also specify these options in the configuration file: storage: dbPath: data/db auditLog: destination: syslog Output to Console To enable auditing and print the audit events to standard output (i.e. stdout), specify console for the --auditDestination setting. For example: mongod --dbpath data/db --auditDestination console You may also specify these options in the configuration file: storage: dbPath: data/db auditLog: destination: console Output to JSON File To enable auditing and print audit events to a file in JSON format, specify file for the --auditDestination setting, JSON for the --auditFormat setting, and the output filename for the --auditPath. The --auditPath option accepts either full path name or relative path name. For example, the following enables auditing and records audit events to a file with the relative path name of data/db/auditLog.json: mongod --dbpath data/db --auditDestination file --auditFormat JSON --auditPath data/db/auditLog.json The audit file rotates at the same time as the server log file. You may also specify these options in the configuration file: storage: dbPath: data/db auditLog: destination: file format: JSON path: data/db/auditLog.json 6.3. Security Tutorials 399 MongoDB Documentation, Release 3.0.7 Note: Printing audit events to a file in JSON format degrades server performance more than printing to a file in BSON format. Output to BSON File To enable auditing and print audit events to a file in BSON binary format, specify file for the --auditDestination setting, BSON for the --auditFormat setting, and the output filename for the --auditPath. The --auditPath option accepts either full path name or relative path name. For ex- ample, the following enables auditing and records audit events to a BSON file with the relative path name of data/db/auditLog.bson: mongod --dbpath data/db --auditDestination file --auditFormat BSON --auditPath data/db/auditLog.bson The audit file rotates at the same time as the server log file. You may also specify these options in the configuration file: storage: dbPath: data/db auditLog: destination: file format: BSON path: data/db/auditLog.bson To view the contents of the file, pass the file to the MongoDB utility bsondump. For example, the following converts the audit log into a human-readable form and output to the terminal: bsondump data/db/auditLog.bson See also: Configure Audit Filters (page 400), Auditing (page 337), System Event Audit Messages (page 425) Configure Audit Filters MongoDB Enterprise81 supports auditing (page 337) of various operations. When enabled (page 398), the audit facility, by default, records all auditable operations as detailed in Audit Event Actions, Details, and Results (page 426). To specify which events to record, the audit feature includes the --auditFilter option. --auditFilter Option The --auditFilter option takes a string representation of a query document of the form: {:, ... } • The can be any field in the audit message (page 425), including fields returned in the param (page 426) document. • The is a query condition expression. To specify an audit filter, enclose the filter document in single quotes to pass the document as a string. To specify the audit filter in a configuration file, you must use the YAML format of the configuration file. 81https://www.mongodb.com/products/mongodb-enterprise-advanced?jmp=docs 400 Chapter 6. Security MongoDB Documentation, Release 3.0.7 Examples Filter for Multiple Operation Types The following example audits only the createCollection (page 420) and dropCollection (page 420) actions by using the filter: { atype:{ $in:[ "createCollection", "dropCollection"]}} To specify an audit filter, enclose the filter document in single quotes to pass the document as a string. mongod--dbpath data/db--auditDestination file--auditFilter '{ atype: { $in: [ "createCollection", "dropCollection" ] } }'--auditFormat BSON--auditPath data/db/auditLog.bson To specify the audit filter in a configuration file, you must use the YAML format of the configuration file. storage: dbPath: data/db auditLog: destination: file format: BSON path: data/db/auditLog.bson filter:'{ atype:{ $in:[ "createCollection", "dropCollection"]}}' Filter on Authentication Operations on a Single Database The can include any field in the audit message (page 425). For authentication operations (i.e. atype: "authenticate"), the audit messages include a db field in the param document. The following example audits only the authenticate operations that occur against the test database by using the filter: { atype: "authenticate", "param.db": "test"} To specify an audit filter, enclose the filter document in single quotes to pass the document as a string. mongod--dbpath data/db--auth--auditDestination file--auditFilter '{ atype: "authenticate", "param.db": "test" }'--auditFormat BSON--auditPath data/db/auditLog.bson To specify the audit filter in a configuration file, you must use the YAML format of the configuration file. storage: dbPath: data/db security: authorization: enabled auditLog: destination: file format: BSON path: data/db/auditLog.bson filter:'{ atype: "authenticate", "param.db": "test"}' To filter on all authenticate operations across databases, use the filter { atype: "authenticate" }. Filter on Collection Creation and Drop Operations for a Single Database The can include any field in the audit message (page 425). For collection creation and drop operations (i.e. atype: "createCollection" and atype: "dropCollection"), the audit messages include a namespace ns field in the param document. The following example audits only the createCollection and dropCollection operations that occur against the test database by using the filter: Note: The regular expression requires two backslashes (\\) to escape the dot (.). 6.3. Security Tutorials 401 MongoDB Documentation, Release 3.0.7 { atype:{ $in:[ "createCollection", "dropCollection"]}, "param.ns": /^test \\./}} To specify an audit filter, enclose the filter document in single quotes to pass the document as a string. mongod--dbpath data/db--auth--auditDestination file--auditFilter '{ atype: { $in: [ "createCollection", "dropCollection" ] }, "param.ns": /^test\\./ } }'--auditFormat BSON--auditPath data/db/auditLog.bson To specify the audit filter in a configuration file, you must use the YAML format of the configuration file. storage: dbPath: data/db security: authorization: enabled auditLog: destination: file format: BSON path: data/db/auditLog.bson filter:'{ atype:{ $in:[ "createCollection", "dropCollection"]}, "param.ns": /^test\\./}}' Filter by Authorization Role The following example audits operations by users with readWrite (page 406) role on the test database, including users with roles that inherit from readWrite (page 406), by using the filter: { roles:{ role: "readWrite", db: "test"}} To specify an audit filter, enclose the filter document in single quotes to pass the document as a string. mongod--dbpath data/db--auth--auditDestination file--auditFilter '{ roles: { role: "readWrite", db: "test" } }'--auditFormat BSON--auditPath data/db/auditLog.bson To specify the audit filter in a configuration file, you must use the YAML format of the configuration file. storage: dbPath: data/db security: authorization: enabled auditLog: destination: file format: BSON path: data/db/auditLog.bson filter:'{ roles:{ role: "readWrite", db: "test"}}' Filter on Read and Write Operations To capture read and write operations in the audit, you must also enable the audit system to log authorization successes using the auditAuthorizationSuccess parameter. 82 Note: Enabling auditAuthorizationSuccess degrades performance more than logging only the authorization failures. The following example audits the find(), insert(), remove(), update(), save(), and findAndModify() operations by using the filter: { atype: "authCheck", "param.command":{ $in:[ "find", "insert", "delete", "update", "findandmodify"]}} To specify an audit filter, enclose the filter document in single quotes to pass the document as a string. mongod--dbpath data/db--auth--setParameter auditAuthorizationSuccess= true --auditDestination file--auditFilter '{ atype: "authCheck", "param.command": { $in: [ "find", "insert", "delete", "update", "findandmodify" ] } }'--auditFormat BSON--auditPath data/db/auditLog.bson 82 You can enable auditAuthorizationSuccess parameter without enabling --auth; however, all operations will return success for authorization checks. 402 Chapter 6. Security MongoDB Documentation, Release 3.0.7 To specify the audit filter in a configuration file, you must use the YAML format of the configuration file. storage: dbPath: data/db security: authorization: enabled auditLog: destination: file format: BSON path: data/db/auditLog.bson filter:'{ atype: "authCheck", "param.command":{ $in:[ "find", "insert", "delete", "update", "findandmodify"]}}' setParameter: { auditAuthorizationSuccess: true} Filter on Read and Write Operations for a Collection To capture read and write operations in the audit, you must also enable the audit system to log authorization successes using the auditAuthorizationSuccess parameter. 1 Note: Enabling auditAuthorizationSuccess degrades performance more than logging only the authorization failures. The following example audits the find(), insert(), remove(), update(), save(), and findAndModify() operations for the collection orders in the database test by using the filter: { atype: "authCheck", "param.ns": "test.orders", "param.command":{ $in:[ "find", "insert", "delete", "update", "findandmodify"]}} To specify an audit filter, enclose the filter document in single quotes to pass the document as a string. mongod--dbpath data/db--auth--setParameter auditAuthorizationSuccess= true --auditDestination file--auditFilter '{ atype: "authCheck", "param.ns": "test.orders", "param.command": { $in: [ "find", "insert", "delete", "update", "findandmodify" ] } }'--auditFormat BSON--auditPath data/db/auditLog.bson To specify the audit filter in a configuration file, you must use the YAML format of the configuration file. storage: dbPath: data/db security: authorization: enabled auditLog: destination: file format: BSON path: data/db/auditLog.bson filter:'{ atype: "authCheck", "param.ns": "test.orders", "param.command":{ $in:[ "find", "insert", "delete", "update", "findandmodify"]}}' setParameter: { auditAuthorizationSuccess: true} See also: Configure System Events Auditing (page 398), Auditing (page 337), System Event Audit Messages (page 425) 6.3.6 Create a Vulnerability Report If you believe you have discovered a vulnerability in MongoDB or have experienced a security incident related to MongoDB, please report the issue to aid in its resolution. To report an issue, we strongly suggest filing a ticket in the SECURITY83 project in JIRA. MongoDB, Inc responds to vulnerability notifications within 48 hours. 83https://jira.mongodb.org/browse/SECURITY 6.3. Security Tutorials 403 MongoDB Documentation, Release 3.0.7 Create the Report in JIRA Submit a Ticket84 in the Security85 project on our JIRA. The ticket number will become the reference identification for the issue for its lifetime. You can use this identifier for tracking purposes. Information to Provide All vulnerability reports should contain as much information as possible so MongoDB’s developers can move quickly to resolve the issue. In particular, please include the following: • The name of the product. • Common Vulnerability information, if applicable, including: • CVSS (Common Vulnerability Scoring System) Score. • CVE (Common Vulnerability and Exposures) Identifier. • Contact information, including an email address and/or phone number, if applicable. Send the Report via Email While JIRA is the preferred reporting method, you may also report vulnerabilities via email to secu- rity@mongodb.com86. You may encrypt email using MongoDB’s public key at https://docs.mongodb.org/10gen-security-gpg-key.asc. MongoDB, Inc. responds to vulnerability reports sent via email with a response email that contains a reference number for a JIRA ticket posted to the SECURITY87 project. Evaluation of a Vulnerability Report MongoDB, Inc. validates all submitted vulnerabilities and uses Jira to track all communications regarding a vulner- ability, including requests for clarification or additional information. If needed, MongoDB representatives set up a conference call to exchange information regarding the vulnerability. Disclosure MongoDB, Inc. requests that you do not publicly disclose any information regarding the vulnerability or exploit the issue until it has had the opportunity to analyze the vulnerability, to respond to the notification, and to notify key users, customers, and partners. The amount of time required to validate a reported vulnerability depends on the complexity and severity of the issue. MongoDB, Inc. takes all required vulnerabilities very seriously and will always ensure that there is a clear and open channel of communication with the reporter. After validating an issue, MongoDB, Inc. coordinates public disclosure of the issue with the reporter in a mutually agreed timeframe and format. If required or requested, the reporter of a vulnerability will receive credit in the published security bulletin. 84https://jira.mongodb.org/secure/CreateIssue!default.jspa?project-field=%22Security%22 85https://jira.mongodb.org/browse/SECURITY 86security@mongodb.com 87https://jira.mongodb.org/browse/SECURITY 404 Chapter 6. Security MongoDB Documentation, Release 3.0.7 6.4 Security Reference 6.4.1 Security Methods in the mongo Shell User Management and Authentication Methods Name Description db.auth() Authenticates a user to a database. db.createUser() Creates a new user. db.updateUser() Updates user data. db.changeUserPassword() Changes an existing user’s password. db.removeUser() Deprecated. Removes a user from a database. db.dropAllUsers() Deletes all users associated with a database. db.dropUser() Removes a single user. db.grantRolesToUser() Grants a role and its privileges to a user. db.revokeRolesFromUser() Removes a role from a user. db.getUser() Returns information about the specified user. db.getUsers() Returns information about all users associated with a database. Role Management Methods Name Description db.createRole() Creates a role and specifies its privileges. db.updateRole() Updates a user-defined role. db.dropRole() Deletes a user-defined role. db.dropAllRoles() Deletes all user-defined roles associated with a database. db.grantPrivilegesToRole() Assigns privileges to a user-defined role. db.revokePrivilegesFromRole() Removes the specified privileges from a user-defined role. db.grantRolesToRole() Specifies roles from which a user-defined role inherits privileges. db.revokeRolesFromRole() Removes inherited roles from a role. db.getRole() Returns information for the specified role. db.getRoles() Returns information for all the user-defined roles in a database. 6.4.2 Security Reference Documentation Built-In Roles (page 406) Reference on MongoDB provided roles and corresponding access. system.roles Collection (page 414) Describes the content of the collection that stores user-defined roles. system.users Collection (page 416) Describes the content of the collection that stores users’ credentials and role as- signments. Resource Document (page 418) Describes the resource document for roles. Privilege Actions (page 419) List of the actions available for privileges. Default MongoDB Port (page 425) List of default ports used by MongoDB. System Event Audit Messages (page 425) Reference on system event audit messages. 6.4. Security Reference 405 MongoDB Documentation, Release 3.0.7 Built-In Roles MongoDB grants access to data and commands through role-based authorization (page 334) and provides built-in roles that provide the different levels of access commonly needed in a database system. You can additionally create user-defined roles (page 335). A role grants privileges to perform sets of actions (page 419) on defined resources (page 418). A given role applies to the database on which it is defined and can grant access down to a collection level of granularity. Each of MongoDB’s built-in roles defines access at the database level for all non-system collections in the role’s database and at the collection level for all system collections (page 297). MongoDB provides the built-in database user (page 406) and database administration (page 407) roles on every database. MongoDB provides all other built-in roles only on the admin database. This section describes the privileges for each built-in role. You can also view the privileges for a built-in role at any time by issuing the rolesInfo command with the showPrivileges and showBuiltinRoles fields both set to true. Database User Roles Every database includes the following client roles: read Provides the ability to read data on all non-system collections and on the following system collections: system.indexes (page 297), system.js (page 297), and system.namespaces (page 297) collec- tions. The role provides read access by granting the following actions (page 419): •collStats (page 424) •dbHash (page 424) •dbStats (page 424) •find (page 420) •killCursors (page 421) •listIndexes (page 424) •listCollections (page 424) readWrite Provides all the privileges of the read (page 406) role plus ability to modify data on all non-system collections and the system.js (page 297) collection. The role provides the following actions on those collections: •collStats (page 424) •convertToCapped (page 423) •createCollection (page 420) •dbHash (page 424) •dbStats (page 424) •dropCollection (page 420) •createIndex (page 420) •dropIndex (page 423) •emptycapped (page 420) 406 Chapter 6. Security MongoDB Documentation, Release 3.0.7 •find (page 420) •insert (page 420) •killCursors (page 421) •listIndexes (page 424) •listCollections (page 424) •remove (page 420) •renameCollectionSameDB (page 423) •update (page 420) Database Administration Roles Every database includes the following database administration roles: dbAdmin Provides the following actions (page 419) on the database’s system.indexes (page 297), system.namespaces (page 297), and system.profile (page 297) collections: •collStats (page 424) •dbHash (page 424) •dbStats (page 424) •find (page 420) •killCursors (page 421) •listIndexes (page 424) •listCollections (page 424) •dropCollection (page 420) and createCollection (page 420) on system.profile (page 297) only Changed in version 2.6.4: dbAdmin (page 407) added the createCollection (page 420) for the system.profile (page 297) collection. Previous versions only had the dropCollection (page 420) on the system.profile (page 297) collection. Provides the following actions on all non-system collections. This role does not include full read access on non-system collections: •collMod (page 423) •collStats (page 424) •compact (page 423) •convertToCapped (page 423) •createCollection (page 420) •createIndex (page 420) •dbStats (page 424) •dropCollection (page 420) •dropDatabase (page 423) •dropIndex (page 423) 6.4. Security Reference 407 MongoDB Documentation, Release 3.0.7 •enableProfiler (page 420) •indexStats (page 424) •reIndex (page 423) •renameCollectionSameDB (page 423) •repairDatabase (page 423) •storageDetails (page 421) •validate (page 424) dbOwner The database owner can perform any administrative action on the database. This role combines the privileges granted by the readWrite (page 406), dbAdmin (page 407) and userAdmin (page 408) roles. userAdmin Provides the ability to create and modify roles and users on the current database. This role also indirectly provides superuser (page 413) access to either the database or, if scoped to the admin database, the cluster. The userAdmin (page 408) role allows users to grant any user any privilege, including themselves. The userAdmin (page 408) role explicitly provides the following actions: •changeCustomData (page 420) •changePassword (page 420) •createRole (page 420) •createUser (page 420) •dropRole (page 420) •dropUser (page 420) •grantRole (page 421) •revokeRole (page 421) •viewRole (page 421) •viewUser (page 421) Cluster Administration Roles The admin database includes the following roles for administering the whole system rather than just a single database. These roles include but are not limited to replica set and sharded cluster administrative functions. clusterAdmin Provides the greatest cluster-management access. This role combines the privileges granted by the clusterManager (page 408), clusterMonitor (page 409), and hostManager (page 410) roles. Ad- ditionally, the role provides the dropDatabase (page 423) action. clusterManager Provides management and monitoring actions on the cluster. A user with this role can access the config and local databases, which are used in sharding and replication, respectively. Provides the following actions on the cluster as a whole: •addShard (page 422) •applicationMessage (page 422) 408 Chapter 6. Security MongoDB Documentation, Release 3.0.7 •cleanupOrphaned (page 421) •flushRouterConfig (page 422) •listShards (page 422) •removeShard (page 422) •replSetConfigure (page 421) •replSetGetStatus (page 422) •replSetStateChange (page 422) •resync (page 422) Provides the following actions on all databases in the cluster: •enableSharding (page 422) •moveChunk (page 422) •splitChunk (page 422) •splitVector (page 422) On the config database, provides the following actions on the settings (page 741) collection: •insert (page 420) •remove (page 420) •update (page 420) On the config database, provides the following actions on all configuration collections and on the system.indexes (page 297), system.js (page 297), and system.namespaces (page 297) collec- tions: •collStats (page 424) •dbHash (page 424) •dbStats (page 424) •find (page 420) •killCursors (page 421) On the local database, provides the following actions on the replset (page 654) collection: •collStats (page 424) •dbHash (page 424) •dbStats (page 424) •find (page 420) •killCursors (page 421) clusterMonitor Provides read-only access to monitoring tools, such as the MongoDB Cloud Manager88 and Ops Manager89 monitoring agent. Provides the following actions on the cluster as a whole: •connPoolStats (page 424) 88https://cloud.mongodb.com/?jmp=docs 89https://docs.opsmanager.mongodb.com/current/ 6.4. Security Reference 409 MongoDB Documentation, Release 3.0.7 •cursorInfo (page 424) •getCmdLineOpts (page 424) •getLog (page 424) •getParameter (page 423) •getShardMap (page 422) •hostInfo (page 423) •inprog (page 421) •listDatabases (page 424) •listShards (page 422) •netstat (page 424) •replSetGetStatus (page 422) •serverStatus (page 424) •shardingState (page 422) •top (page 424) Provides the following actions on all databases in the cluster: •collStats (page 424) •dbStats (page 424) •getShardVersion (page 422) Provides the find (page 420) action on all system.profile (page 297) collections in the cluster. Provides the following actions on the config database’s configuration collections and system.indexes (page 297), system.js (page 297), and system.namespaces (page 297) collections: •collStats (page 424) •dbHash (page 424) •dbStats (page 424) •find (page 420) •killCursors (page 421) hostManager Provides the ability to monitor and manage servers. Provides the following actions on the cluster as a whole: •applicationMessage (page 422) •closeAllDatabases (page 422) •connPoolSync (page 423) •cpuProfiler (page 421) •diagLogging (page 424) •flushRouterConfig (page 422) •fsync (page 423) •invalidateUserCache (page 421) 410 Chapter 6. Security MongoDB Documentation, Release 3.0.7 •killop (page 421) •logRotate (page 423) •resync (page 422) •setParameter (page 423) •shutdown (page 423) •touch (page 423) •unlock (page 421) Provides the following actions on all databases in the cluster: •killCursors (page 421) •repairDatabase (page 423) Backup and Restoration Roles The admin database includes the following roles for backing up and restoring data: backup Provides minimal privileges needed for backing up data. This role provides sufficient privileges to use the MongoDB Cloud Manager90 backup agent, Ops Manager91 backup agent, or to use mongodump to back up an entire mongod instance. Provides the following actions (page 419) on the mms.backup collection in the admin database: •insert (page 420) •update (page 420) Provides the listDatabases (page 424) action on the cluster as a whole. Provides the listCollections (page 424) action on all databases. Provides the listIndexes (page 424) action for all collections. Provides the find (page 420) action on the following: •all non-system collections in the cluster •all the following system collections in the cluster: system.indexes (page 297), system.namespaces (page 297), and system.js (page 297) •the admin.system.users (page 297) and admin.system.roles (page 297) collections •legacy system.users collections from versions of MongoDB prior to 2.6 To back up the system.profile (page 297) collection, which is created when you activate database pro- filing (page 219), you must have additional read access on this collection. Several roles provide this access, including the clusterAdmin (page 408) and dbAdmin (page 407) roles. restore Provides privileges needed to restore data from backups. This role is sufficient when restoring data with mongorestore without the --oplogReplay option. If running mongorestore with --oplogReplay, however, the restore (page 411) role is insufficient to replay the oplog. To replay the oplog, create a user-defined role (page 391) that has anyAction (page 424) on anyResource (page 419) and grant only to users who must run mongorestore with --oplogReplay. 90https://cloud.mongodb.com/?jmp=docs 91https://docs.opsmanager.mongodb.com/current/ 6.4. Security Reference 411 MongoDB Documentation, Release 3.0.7 Provides the following actions on all non-system collections and system.js (page 297) collections in the cluster; on the admin.system.users (page 297) and admin.system.roles (page 297) collections in the admin database; and on legacy system.users collections from versions of MongoDB prior to 2.6: •collMod (page 423) •createCollection (page 420) •createIndex (page 420) •dropCollection (page 420) •insert (page 420) Provides the listCollections (page 424) action on all databases. Provides the following additional actions on admin.system.users (page 297) and legacy system.users collections: •find (page 420) •remove (page 420) •update (page 420) Provides the find (page 420) action on all the system.namespaces (page 297) collections in the cluster. Although, restore (page 411) includes the ability to modify the documents in the admin.system.users (page 297) collection using normal modification operations, only modify these data using the user management methods. All-Database Roles The admin database provides the following roles that apply to all databases in a mongod instance and are roughly equivalent to their single-database equivalents: readAnyDatabase Provides the same read-only permissions as read (page 406), except it applies to all databases in the cluster. The role also provides the listDatabases (page 424) action on the cluster as a whole. readWriteAnyDatabase Provides the same read and write permissions as readWrite (page 406), except it applies to all databases in the cluster. The role also provides the listDatabases (page 424) action on the cluster as a whole. userAdminAnyDatabase Provides the same access to user administration operations as userAdmin (page 408), except it applies to all databases in the cluster. The role also provides the following actions on the cluster as a whole: •authSchemaUpgrade (page 421) •invalidateUserCache (page 421) •listDatabases (page 424) The role also provides the following actions on the admin.system.users (page 297) and admin.system.roles (page 297) collections on the admin database, and on legacy system.users collections from versions of MongoDB prior to 2.6: •collStats (page 424) •dbHash (page 424) •dbStats (page 424) 412 Chapter 6. Security MongoDB Documentation, Release 3.0.7 •find (page 420) •killCursors (page 421) •planCacheRead (page 421) Changed in version 2.6.4: userAdminAnyDatabase (page 412) added the following permissions on the admin.system.users (page 297) and admin.system.roles (page 297) collections: •createIndex (page 420) •dropIndex (page 423) The userAdminAnyDatabase (page 412) role does not restrict the permissions that a user can grant. As a result, userAdminAnyDatabase (page 412) users can grant themselves privileges in excess of their cur- rent privileges and even can grant themselves all privileges, even though the role does not explicitly authorize privileges beyond user administration. This role is effectively a MongoDB system superuser (page 413). dbAdminAnyDatabase Provides the same access to database administration operations as dbAdmin (page 407), except it applies to all databases in the cluster. The role also provides the listDatabases (page 424) action on the cluster as a whole. Superuser Roles Several roles provide either indirect or direct system-wide superuser access. The following roles provide the ability to assign any user any privilege on any database, which means that users with one of these roles can assign themselves any privilege on any database: • dbOwner (page 408) role, when scoped to the admin database • userAdmin (page 408) role, when scoped to the admin database • userAdminAnyDatabase (page 412) role The following role provides full privileges on all resources: root Provides access to the operations and all the resources of the readWriteAnyDatabase (page 412), dbAdminAnyDatabase (page 413), userAdminAnyDatabase (page 412) and clusterAdmin (page 408) roles combined. Changed in version 3.0.7: The root (page 413) has validate (page 424) action on system. collections. Previously, root (page 413) does not include any access to collections that begin with the system. prefix. For example, without the ability to insert data directly into the system.users (page 297) and system.roles (page 297) collections in the admin database. root (page 413) is not suitable for writ- ing or restoring data that have these collections (e.g. with mongorestore.) To perform these kinds of restore operations, provision users with the restore (page 411) role. Internal Role __system MongoDB assigns this role to user objects that represent cluster members, such as replica set members and mongos instances. The role entitles its holder to take any action against any object in the database. Do not assign this role to user objects representing applications or human administrators, other than in excep- tional circumstances. 6.4. Security Reference 413 MongoDB Documentation, Release 3.0.7 If you need access to all actions on all resources, for example to run applyOps commands, do not assign this role. Instead, create a user-defined role (page 391) that grants anyAction (page 424) on anyResource (page 419) and ensure that only the users who need access to these operations have this access. system.roles Collection New in version 2.6. The system.roles collection in the admin database stores the user-defined roles. To create and manage these user-defined roles, MongoDB provides role management commands. system.roles Schema The documents in the system.roles collection have the following schema: { _id:, role: "", db: "", privileges: [ { resource:{}, actions:[ "", ... ] }, ... ], roles: [ { role: "", db: ""}, ... ] } A system.roles document has the following fields: admin.system.roles.role The role (page 414) field is a string that specifies the name of the role. admin.system.roles.db The db (page 414) field is a string that specifies the database to which the role belongs. MongoDB uniquely identifies each role by the pairing of its name (i.e. role (page 414)) and its database. admin.system.roles.privileges The privileges (page 414) array contains the privilege documents that define the privileges (page 335) for the role. A privilege document has the following syntax: { resource:{}, actions:[ "", ... ] } Each privilege document has the following fields: 414 Chapter 6. Security MongoDB Documentation, Release 3.0.7 admin.system.roles.privileges[n].resource A document that specifies the resources upon which the privilege actions (page 415) apply. The docu- ment has one of the following form: { db:, collection:} or { cluster: true } See Resource Document (page 418) for more details. admin.system.roles.privileges[n].actions An array of actions permitted on the resource. For a list of actions, see Privilege Actions (page 419). admin.system.roles.roles The roles (page 415) array contains role documents that specify the roles from which this role inherits (page 335) privileges. A role document has the following syntax: { role: "", db: ""} A role document has the following fields: admin.system.roles.roles[n].role The name of the role. A role can be a built-in role (page 406) provided by MongoDB or a user-defined role (page 335). admin.system.roles.roles[n].db The name of the database where the role is defined. Examples Consider the following sample documents found in system.roles collection of the admin database. A User-Defined Role Specifies Privileges The following is a sample document for a user-defined role appUser defined for the myApp database: { _id: "myApp.appUser", role: "appUser", db: "myApp", privileges:[ { resource: { db: "myApp" , collection:""}, actions:[ "find", "createCollection", "dbStats", "collStats"]}, { resource: { db: "myApp", collection: "logs"}, actions:[ "insert"]}, { resource: { db: "myApp", collection: "data"}, actions:[ "insert", "update", "remove", "compact"]}, { resource: { db: "myApp", collection: "system.js"}, actions:[ "find"]}, ], roles:[] } The privileges array lists the five privileges that the appUser role specifies: 6.4. Security Reference 415 MongoDB Documentation, Release 3.0.7 • The first privilege permits its actions ( "find","createCollection","dbStats","collStats") on all the collections in the myApp database excluding its system collections. See Specify a Database as Resource (page 418). • The next two privileges permits additional actions on specific collections, logs and data, in the myApp database. See Specify a Collection of a Database as Resource (page 418). • The last privilege permits actions on one system collections (page 297) in the myApp database. While the first privilege gives database-wide permission for the find action, the action does not apply to myApp‘s system collections. To give access to a system collection, a privilege must explicitly specify the collection. See Resource Document (page 418). As indicated by the empty roles array, appUser inherits no additional privileges from other roles. User-Defined Role Inherits from Other Roles The following is a sample document for a user-defined role appAdmin defined for the myApp database: The document shows that the appAdmin role specifies privileges as well as inherits privileges from other roles: { _id: "myApp.appAdmin", role: "appAdmin", db: "myApp", privileges:[ { resource: { db: "myApp", collection:""}, actions:[ "insert", "dbStats", "collStats", "compact", "repairDatabase"] } ], roles:[ { role: "appUser", db: "myApp"} ] } The privileges array lists the privileges that the appAdmin role specifies. This role has a single privilege that permits its actions ( "insert","dbStats","collStats","compact","repairDatabase") on all the collections in the myApp database excluding its system collections. See Specify a Database as Resource (page 418). The roles array lists the roles, identified by the role names and databases, from which the role appAdmin inherits privileges. system.users Collection Changed in version 2.6. The system.users collection in the admin database stores user authentication (page 326) and authorization (page 334) information. To manage data in this collection, MongoDB provides user management commands. system.users Schema The documents in the system.users collection have the following schema: { _id:, user: "", db: "", credentials:{}, 416 Chapter 6. Security MongoDB Documentation, Release 3.0.7 roles:[ { role: "", db: ""}, ... ], customData: } Each system.users document has the following fields: admin.system.users.user The user (page 417) field is a string that identifies the user. A user exists in the context of a single logical database but can have access to other databases through roles specified in the roles (page 417) array. admin.system.users.db The db (page 417) field specifies the database associated with the user. The user’s privileges are not necessarily limited to this database. The user can have privileges in additional databases through the roles (page 417) array. admin.system.users.credentials The credentials (page 417) field contains the user’s authentication information. For users with externally stored authentication credentials, such as users that use Kerberos (page 376) or x.509 certificates for authentica- tion, the system.users document for that user does not contain the credentials (page 417) field. admin.system.users.roles The roles (page 417) array contains role documents that specify the roles granted to the user. The array contains both built-in roles (page 406) and user-defined role (page 335). A role document has the following syntax: { role: "", db: ""} A role document has the following fields: admin.system.users.roles[n].role The name of a role. A role can be a built-in role (page 406) provided by MongoDB or a custom user-defined role (page 335). admin.system.users.roles[n].db The name of the database where role is defined. When specifying a role using the role management or user management commands, you can specify the role name alone (e.g. "readWrite") if the role that exists on the database on which the command is run. admin.system.users.customData The customData (page 417) field contains optional custom information about the user. Example Changed in version 3.0.0. Consider the following document in the system.users collection: { _id : "home.Kari", user : "Kari", db : "home", credentials : { "SCRAM-SHA-1" : { "iterationCount" : 10000, "salt" : nkHYXEZTTYmn+hrY994y1Q==", 6.4. Security Reference 417 MongoDB Documentation, Release 3.0.7 "storedKey" : "wxWGN3ElQ25WbPjACeXdUmN4nNo=", "serverKey" : "h7vBq5tACT/BtrIElY2QTm+pQzM=" } }, roles : [ { role: "read", db: "home" }, { role: "readWrite", db: "test" }, { role: "appUser", db: "myApp" } ], customData : { zipCode: "64157" } } The document shows that a user Kari is associated with the home database. Kari has the read (page 406) role in the home database, the readWrite (page 406) role in the test database, and the appUser role in the myApp database. Resource Document The resource document specifies the resources upon which a privilege permits actions. Database and/or Collection Resource To specify databases and/or collections, use the following syntax: { db:, collection:} Specify a Collection of a Database as Resource If the resource document species both the db and collection fields as non-empty strings, the resource is the specified collection in the specified database. For example, the following document specifies a resource of the inventory collection in the products database: { db: "products", collection: "inventory"} For a user-defined role scoped for a non-admin database, the resource specification for its privileges must specify the same database as the role. User-defined roles scoped for the admin database can specify other databases. Specify a Database as Resource If only the collection field is an empty string (""), the resource is the specified database, excluding the system collections (page 297). For example, the following resource document specifies the resource of the test database, excluding the system collections: { db: "test", collection:""} For a user-defined role scoped for a non-admin database, the resource specification for its privileges must specify the same database as the role. User-defined roles scoped for the admin database can specify other databases. Note: When you specify a database as the resource, system collections are excluded, unless you name them explicitly, as in the following: { db: "test", collection: "system.js"} System collections include but are not limited to the following: • .system.profile (page 297) • .system.js (page 297) 418 Chapter 6. Security MongoDB Documentation, Release 3.0.7 • system.users Collection (page 416) in the admin database • system.roles Collection (page 414) in the admin database Specify Collections Across Databases as Resource If only the db field is an empty string (""), the resource is all collections with the specified name across all databases. For example, the following document specifies the resource of all the accounts collections across all the databases: { db:"", collection: "accounts"} For user-defined roles, only roles scoped for the admin database can have this resource specification for their privi- leges. Specify All Non-System Collections in All Databases If both the db and collection fields are empty strings (""), the resource is all collections, excluding the system collections (page 297), in all the databases: { db:"", collection:""} For user-defined roles, only roles scoped for the admin database can have this resource specification for their privi- leges. Cluster Resource To specify the cluster as the resource, use the following syntax: { cluster: true } Use the cluster resource for actions that affect the state of the system rather than act on specific set of databases or collections. Examples of such actions are shutdown, replSetReconfig, and addShard. For example, the following document grants the action shutdown on the cluster. { resource: { cluster: true }, actions:[ "shutdown"]} For user-defined roles, only roles scoped for the admin database can have this resource specification for their privi- leges. anyResource The internal resource anyResource gives access to every resource in the system and is intended for internal use. Do not use this resource, other than in exceptional circumstances. The syntax for this resource is { anyResource: true }. Privilege Actions New in version 2.6. Privilege actions define the operations a user can perform on a resource (page 418). A MongoDB privilege (page 335) comprises a resource (page 418) and the permitted actions. This page lists available actions grouped by common purpose. MongoDB provides built-in roles with pre-defined pairings of resources and permitted actions. For lists of the actions granted, see Built-In Roles (page 406). To define custom roles, see Create a User-Defined Role (page 391). 6.4. Security Reference 419 MongoDB Documentation, Release 3.0.7 Query and Write Actions find User can perform the db.collection.find() method. Apply this action to database or collection re- sources. insert User can perform the insert command. Apply this action to database or collection resources. remove User can perform the db.collection.remove() method. Apply this action to database or collection resources. update User can perform the update command. Apply this action to database or collection resources. Database Management Actions changeCustomData User can change the custom information of any user in the given database. Apply this action to database resources. changeOwnCustomData Users can change their own custom information. Apply this action to database resources. See also Change Your Password and Custom Data (page 395). changeOwnPassword Users can change their own passwords. Apply this action to database resources. See also Change Your Password and Custom Data (page 395). changePassword User can change the password of any user in the given database. Apply this action to database resources. createCollection User can perform the db.createCollection() method. Apply this action to database or collection re- sources. createIndex Provides access to the db.collection.createIndex() method and the createIndexes command. Apply this action to database or collection resources. createRole User can create new roles in the given database. Apply this action to database resources. createUser User can create new users in the given database. Apply this action to database resources. dropCollection User can perform the db.collection.drop() method. Apply this action to database or collection re- sources. dropRole User can delete any role from the given database. Apply this action to database resources. dropUser User can remove any user from the given database. Apply this action to database resources. emptycapped User can perform the emptycapped command. Apply this action to database or collection resources. 420 Chapter 6. Security MongoDB Documentation, Release 3.0.7 enableProfiler User can perform the db.setProfilingLevel() method. Apply this action to database resources. grantRole User can grant any role in the database to any user from any database in the system. Apply this action to database resources. killCursors User can kill cursors on the target collection. revokeRole User can remove any role from any user from any database in the system. Apply this action to database resources. unlock User can perform the db.fsyncUnlock() method. Apply this action to the cluster resource. viewRole User can view information about any role in the given database. Apply this action to database resources. viewUser User can view the information of any user in the given database. Apply this action to database resources. Deployment Management Actions authSchemaUpgrade User can perform the authSchemaUpgrade command. Apply this action to the cluster resource. cleanupOrphaned User can perform the cleanupOrphaned command. Apply this action to the cluster resource. cpuProfiler User can enable and use the CPU profiler. Apply this action to the cluster resource. inprog User can use the db.currentOp() method to return pending and active operations. Apply this action to the cluster resource. invalidateUserCache Provides access to the invalidateUserCache command. Apply this action to the cluster resource. killop User can perform the db.killOp() method. Apply this action to the cluster resource. planCacheRead User can perform the planCacheListPlans and planCacheListQueryShapes commands and the PlanCache.getPlansByQuery() and PlanCache.listQueryShapes() methods. Apply this ac- tion to database or collection resources. planCacheWrite User can perform the planCacheClear command and the PlanCache.clear() and PlanCache.clearPlansByQuery() methods. Apply this action to database or collection resources. storageDetails User can perform the storageDetails command. Apply this action to database or collection resources. Replication Actions appendOplogNote User can append notes to the oplog. Apply this action to the cluster resource. 6.4. Security Reference 421 MongoDB Documentation, Release 3.0.7 replSetConfigure User can configure a replica set. Apply this action to the cluster resource. replSetGetStatus User can perform the replSetGetStatus command. Apply this action to the cluster resource. replSetHeartbeat User can perform the replSetHeartbeat command. Apply this action to the cluster resource. replSetStateChange User can change the state of a replica set through the replSetFreeze, replSetMaintenance, replSetStepDown, and replSetSyncFrom commands. Apply this action to the cluster resource. resync User can perform the resync command. Apply this action to the cluster resource. Sharding Actions addShard User can perform the addShard command. Apply this action to the cluster resource. enableSharding User can enable sharding on a database using the enableSharding command and can shard a collection using the shardCollection command. Apply this action to database or collection resources. flushRouterConfig User can perform the flushRouterConfig command. Apply this action to the cluster resource. getShardMap User can perform the getShardMap command. Apply this action to the cluster resource. getShardVersion User can perform the getShardVersion command. Apply this action to database resources. listShards User can perform the listShards command. Apply this action to the cluster resource. moveChunk User can perform the moveChunk command. In addition, user can perform the movePrimary command provided that the privilege is applied to an appropriate database resource. Apply this action to database or collection resources. removeShard User can perform the removeShard command. Apply this action to the cluster resource. shardingState User can perform the shardingState command. Apply this action to the cluster resource. splitChunk User can perform the splitChunk command. Apply this action to database or collection resources. splitVector User can perform the splitVector command. Apply this action to database or collection resources. Server Administration Actions applicationMessage User can perform the logApplicationMessage command. Apply this action to the cluster resource. 422 Chapter 6. Security MongoDB Documentation, Release 3.0.7 closeAllDatabases User can perform the closeAllDatabases command. Apply this action to the cluster resource. collMod User can perform the collMod command. Apply this action to database or collection resources. compact User can perform the compact command. Apply this action to database or collection resources. connPoolSync User can perform the connPoolSync command. Apply this action to the cluster resource. convertToCapped User can perform the convertToCapped command. Apply this action to database or collection resources. dropDatabase User can perform the dropDatabase command. Apply this action to database resources. dropIndex User can perform the dropIndexes command. Apply this action to database or collection resources. fsync User can perform the fsync command. Apply this action to the cluster resource. getParameter User can perform the getParameter command. Apply this action to the cluster resource. hostInfo Provides information about the server the MongoDB instance runs on. Apply this action to the cluster resource. logRotate User can perform the logRotate command. Apply this action to the cluster resource. reIndex User can perform the reIndex command. Apply this action to database or collection resources. renameCollectionSameDB Allows the user to rename collections on the current database using the renameCollection command. Apply this action to database resources. Additionally, the user must either have find (page 420) on the source collection or not have find (page 420) on the destination collection. If a collection with the new name already exists, the user must also have the dropCollection (page 420) action on the destination collection. repairDatabase User can perform the repairDatabase command. Apply this action to database resources. setParameter User can perform the setParameter command. Apply this action to the cluster resource. shutdown User can perform the shutdown command. Apply this action to the cluster resource. touch User can perform the touch command. Apply this action to the cluster resource. 6.4. Security Reference 423 MongoDB Documentation, Release 3.0.7 Diagnostic Actions collStats User can perform the collStats command. Apply this action to database or collection resources. connPoolStats User can perform the connPoolStats and shardConnPoolStats commands. Apply this action to the cluster resource. cursorInfo User can perform the cursorInfo command. Apply this action to the cluster resource. dbHash User can perform the dbHash command. Apply this action to database or collection resources. dbStats User can perform the dbStats command. Apply this action to database resources. diagLogging User can perform the diagLogging command. Apply this action to the cluster resource. getCmdLineOpts User can perform the getCmdLineOpts command. Apply this action to the cluster resource. getLog User can perform the getLog command. Apply this action to the cluster resource. indexStats User can perform the indexStats command. Apply this action to database or collection resources. Changed in version 3.0: MongoDB 3.0 removes the indexStats command. listDatabases User can perform the listDatabases command. Apply this action to the cluster resource. listCollections User can perform the listCollections command. Apply this action to database resources. listIndexes User can perform the ListIndexes command. Apply this action to database or collection resources. netstat User can perform the netstat command. Apply this action to the cluster resource. serverStatus User can perform the serverStatus command. Apply this action to the cluster resource. validate User can perform the validate command. Apply this action to database or collection resources. top User can perform the top command. Apply this action to the cluster resource. Internal Actions anyAction Allows any action on a resource. Do not assign this action except for exceptional circumstances. internal Allows internal actions. Do not assign this action except for exceptional circumstances. 424 Chapter 6. Security MongoDB Documentation, Release 3.0.7 Default MongoDB Port The following table lists the default TCP ports used by MongoDB: Default Port Description 27017 The default port for mongod and mongos instances. You can change this port with port or --port. 27018 The default port when running with --shardsvr runtime operation or the shardsvr value for the clusterRole setting in a configuration file. 27019 The default port when running with --configsvr runtime operation or the configsvr value for the clusterRole setting in a configuration file. 28017 The default port for the web status page. The web status page is always accessible at a port number that is 1000 greater than the port determined by port. System Event Audit Messages Note: Available only in MongoDB Enterprise92. Audit Message The event auditing feature (page 337) can record events in JSON format. To configure auditing output, see Configure System Events Auditing (page 398) The recorded JSON messages have the following syntax: { atype: , ts : { "$date": }, local: { ip: , port: }, remote: { ip: , port: }, users : [ { user: , db: }, ... ], roles: [ { role: , db: }, ... ], param: , result: } field string atype Action type. See Audit Event Actions, Details, and Results (page 426). field document ts Document that contains the date and UTC time of the event, in ISO 8601 format. field document local Document that contains the local ip address and the port number of the running instance. field document remote Document that contains the remote ip address and the port number of the incoming connection associated with the event. field array users Array of user identification documents. Because MongoDB allows a session to log in with different user per database, this array can have more than one user. Each document contains a user field for the username and a db field for the authentication database for that user. field array roles Array of documents that specify the roles (page 334) granted to the user. Each document contains a role field for the name of the role and a db field for the database associated with the role. 92http://www.mongodb.com/products/mongodb-enterprise?jmp=docs 6.4. Security Reference 425 MongoDB Documentation, Release 3.0.7 field document param Specific details for the event. See Audit Event Actions, Details, and Results (page 426). field integer result Error code. See Audit Event Actions, Details, and Results (page 426). Audit Event Actions, Details, and Results The following table lists for each atype or action type, the associated param details and the result values, if any. atype param result authenticate { user: , db: , mechanism: } 0 - Success 18 - Authentication Failed authCheck { command: , ns: ., args: } ns field is optional. args field may be redacted. 0 - Success 13 - Unauthorized to perform the op- eration. By default, the auditing system logs only the authorization fail- ures. To enable the system to log authorization successes, use the auditAuthorizationSuccess parameter. 93 createCollection (page 420) { ns: . } 0 - Success createDatabase { ns: } 0 - Success createIndex (page 420) { ns: ., indexName: , indexSpec: } 0 - Success renameCollection { old: ., new: . } 0 - Success dropCollection (page 420) { ns: . } 0 - Success dropDatabase (page 423) { ns: } 0 - Success Continued on next page 93 Enabling auditAuthorizationSuccess degrades performance more than logging only the authorization failures. 426 Chapter 6. Security MongoDB Documentation, Release 3.0.7 Table 6.1 – continued from previous page atype param result dropIndex (page 423) { ns: ., indexName: } 0 - Success createUser (page 420) { user: , db: , customData: , roles: [ { role: , db: }, ... ] } The customData field is optional. 0 - Success dropUser (page 420) { user: , db: } 0 - Success dropAllUsersFromDatabase { db: } 0 - Success updateUser { user: , db: , passwordChanged: , customData: , roles: [ { role: , db: }, ... ] } The customData field is optional. 0 - Success Continued on next page 6.4. Security Reference 427 MongoDB Documentation, Release 3.0.7 Table 6.1 – continued from previous page atype param result grantRolesToUser { user: , db: , roles: [ { role: , db: }, ... ] } 0 - Success revokeRolesFromUser { user: , db: , roles: [ { role: , db: }, ... ] } 0 - Success createRole (page 420) { role: , db: , roles: [ { role: , db: }, ... ], privileges: [ { resource: , actions: [ , ... ] }, ... ] } The roles and the privileges fields are optional. For details on the resource document, see Resource Document (page 418). For a list of actions, see Privilege Ac- tions (page 419). 0 - Success Continued on next page 428 Chapter 6. Security MongoDB Documentation, Release 3.0.7 Table 6.1 – continued from previous page atype param result updateRole { role: , db: , roles: [ { role: , db: }, ... ], privileges: [ { resource: , actions: [ , ... ] }, ... ] } The roles and the privileges fields are optional. For details on the resource document, see Resource Document (page 418). For a list of actions, see Privilege Ac- tions (page 419). 0 - Success dropRole (page 420) { role: , db: } 0 - Success dropAllRolesFromDatabase { db: } 0 - Success grantRolesToRole { role: , db: , roles: [ { role: , db: }, ... ] } 0 - Success Continued on next page 6.4. Security Reference 429 MongoDB Documentation, Release 3.0.7 Table 6.1 – continued from previous page atype param result revokeRolesFromRole { role: , db: , roles: [ { role: , db: }, ... ] } 0 - Success grantPrivilegesToRole { role: , db: , privileges: [ { resource: , actions: [ , ... ] }, ... ] } For details on the resource document, see Resource Document (page 418). For a list of actions, see Privilege Ac- tions (page 419). 0 - Success revokePrivilegesFromRole { role: , db: , privileges: [ { resource: , actions: [ , ... ] }, ... ] } For details on the resource document, see Resource Document (page 418). For a list of actions, see Privilege Ac- tions (page 419). 0 - Success Continued on next page 430 Chapter 6. Security MongoDB Documentation, Release 3.0.7 Table 6.1 – continued from previous page atype param result replSetReconfig { old: , new: } Indicates membership change in the replica set. The old field is optional. 0 - Success enableSharding (page 422) { ns: } 0 - Success shardCollection { ns: ., key: , options: { unique: } } 0 - Success addShard (page 422) { shard: , connectionString: :, maxSize: } When a shard is a replica set, the connectionString includes the replica set name and can include other members of the replica set. 0 - Success removeShard (page 422) { shard: } 0 - Success shutdown (page 423) {} Indicates commencement of database shutdown. 0 - Success applicationMessage (page 422) { msg: } See logApplicationMessage. 0 - Success 6.4.3 Security Release Notes Alerts Security Release Notes (page 431) Security vulnerability for password. Security Release Notes Access to system.users Collection Changed in version 2.4. In 2.4, only users with the userAdmin role have access to the system.users collection. 6.4. Security Reference 431 MongoDB Documentation, Release 3.0.7 In version 2.2 and earlier, the read-write users of a database all have access to the system.users collection, which contains the user names and user password hashes. 94 Password Hashing Insecurity If a user has the same password for multiple databases, the hash will be the same. A malicious user could exploit this to gain access on a second database using a different user’s credentials. As a result, always use unique username and password combinations for each database. Thanks to Will Urbanski, from Dell SecureWorks, for identifying this issue. 6.5 Security Checklist This documents provides a list of security measures that you should implement to protect your MongoDB installation. 6.5.1 Require Authentication Enable MongoDB authentication and specify the authentication mechanism. You can use the MongoDB authentica- tion mechanism or an existing external framework. Authentication requires that all clients and servers provide valid credentials before they can connect to the system. In clustered deployments, enable authentication for each MongoDB server. See Authentication (page 326), Enable Client Access Control (page 360), and Enable Authentication in a Sharded Cluster (page 362). 6.5.2 Configure Role-Based Access Control Create a user administrator first, then create additional users. Create a unique MongoDB user for each person and application that accesses the system. Create roles that define the exact access a set of users needs. Follow a principle of least privilege. Then create users and assign them only the roles they need to perform their operations. A user can be a person or a client application. See Authorization (page 334), Create a User Administrator (page 387), and Manage User and Roles (page 389), . 6.5.3 Encrypt Communication Configure MongoDB to use TLS/SSL for all incoming and outgoing connections. Use TLS/SSL to encrypt commu- nication between mongod and mongos components of a MongoDB client as well as between all applications and MongoDB. See Configure mongod and mongos for TLS/SSL (page 347). 6.5.4 Limit Network Exposure Ensure that MongoDB runs in a trusted network environment and limit the interfaces on which MongoDB instances listen for incoming connections. Allow only trusted clients to access the network interfaces and ports on which MongoDB instances are available. 94 Read-only users do not have access to the system.users collection. 432 Chapter 6. Security MongoDB Documentation, Release 3.0.7 See the bindIp setting, and see Configure Linux iptables Firewall for MongoDB (page 340) and Configure Windows netsh Firewall for MongoDB (page 343). 6.5.5 Audit System Activity Track access and changes to database configurations and data. MongoDB Enterprise95 includes a system auditing facility that can record system events (e.g. user operations, connection events) on a MongoDB instance. These audit records permit forensic analysis and allow administrators to verify proper controls. See Auditing (page 337) and Configure System Events Auditing (page 398). 6.5.6 Encrypt and Protect Data Encrypt MongoDB data on each host using file-system, device, or physical encryption. Protect MongoDB data using file-system permissions. MongoDB data includes data files, configuration files, auditing logs, and key files. 6.5.7 Run MongoDB with a Dedicated User Run MongoDB processes with a dedicated operating system user account. Ensure that the account has permissions to access data but no unnecessary permissions. See Install MongoDB (page 5) for more information on running MongoDB. 6.5.8 Run MongoDB with Secure Configuration Options MongoDB supports the execution of JavaScript code for certain server-side operations: mapReduce, group, and $where. If you do not use these operations, disable server-side scripting by using the --noscripting option on the command line. Use only the MongoDB wire protocol on production deployments. Do not enable the following, all of which enable the web server interface: enabled, net.http.JSONPEnabled, and net.http.RESTInterfaceEnabled. Leave these disabled, unless required for backwards compatibility. Keep input validation enabled. MongoDB enables input validation by default through the wireObjectCheck setting. This ensures that all documents stored by the mongod instance are valid BSON. 6.5.9 Request a Security Technical Implementation Guide (where applicable) The Security Technical Implementation Guide (STIG) contains security guidelines for deployments within the United States Department of Defense. MongoDB Inc. provides its STIG, upon request, for situations where it is required. Please request a copy96 for more information. 6.5.10 Consider Security Standards Compliance For applications requiring HIPAA or PCI-DSS compliance, please refer to the MongoDB Security Reference Architec- ture97 to learn more about how you can use the key security capabilities to build compliant application infrastructure. 95http://www.mongodb.com/products/mongodb-enterprise?jmp=docs 96http://www.mongodb.com/lp/contact/stig-requests 97http://info.mongodb.com/rs/mongodb/images/MongoDB_Security_Architecture_WP.pdf 6.5. Security Checklist 433 MongoDB Documentation, Release 3.0.7 434 Chapter 6. Security CHAPTER 7 Aggregation Aggregations operations process data records and return computed results. Aggregation operations group values from multiple documents together, and can perform a variety of operations on the grouped data to return a single result. MongoDB provides three ways to perform aggregation: the aggregation pipeline (page 440), the map-reduce function (page 442), and single purpose aggregation methods and commands (page 444). Aggregation Introduction (page 435) A high-level introduction to aggregation. Aggregation Concepts (page 439) Introduces the use and operation of the data aggregation modalities available in MongoDB. Aggregation Pipeline (page 440) The aggregation pipeline is a framework for performing aggregation tasks, modeled on the concept of data processing pipelines. Using this framework, MongoDB passes the doc- uments of a single collection through a pipeline. The pipeline transforms the documents into aggregated results, and is accessed through the aggregate database command. Map-Reduce (page 442) Map-reduce is a generic multi-phase data aggregation modality for processing quan- tities of data. MongoDB provides map-reduce with the mapReduce database command. Single Purpose Aggregation Operations (page 444) MongoDB provides a collection of specific data aggrega- tion operations to support a number of common data aggregation functions. These operations include returning counts of documents, distinct values of a field, and simple grouping operations. Aggregation Mechanics (page 447) Details internal optimization operations, limits, support for sharded col- lections, and concurrency concerns. Aggregation Examples (page 452) Examples and tutorials for data aggregation operations in MongoDB. Aggregation Reference (page 469) References for all aggregation operations material for all data aggregation meth- ods in MongoDB. 7.1 Aggregation Introduction Aggregations are operations that process data records and return computed results. MongoDB provides a rich set of aggregation operations that examine and perform calculations on the data sets. Running data aggregation on the mongod instance simplifies application code and limits resource requirements. Like queries, aggregation operations in MongoDB use collections of documents as an input and return results in the form of one or more documents. 435 MongoDB Documentation, Release 3.0.7 7.1.1 Aggregation Modalities Aggregation Pipelines MongoDB 2.2 introduced a new aggregation framework (page 440), modeled on the concept of data processing pipelines. Documents enter a multi-stage pipeline that transforms the documents into an aggregated result. The most basic pipeline stages provide filters that operate like queries and document transformations that modify the form of the output document. Other pipeline operations provide tools for grouping and sorting documents by specific field or fields as well as tools for aggregating the contents of arrays, including arrays of documents. In addition, pipeline stages can use operators for tasks such as calculating the average or concatenating a string. The pipeline provides efficient data aggregation using native operations within MongoDB, and is the preferred method for data aggregation in MongoDB. Map-Reduce MongoDB also provides map-reduce (page 442) operations to perform aggregation. In general, map-reduce operations have two phases: a map stage that processes each document and emits one or more objects for each input document, and reduce phase that combines the output of the map operation. Optionally, map-reduce can have a finalize stage to make final modifications to the result. Like other aggregation operations, map-reduce can specify a query condition to select the input documents as well as sort and limit the results. 436 Chapter 7. Aggregation MongoDB Documentation, Release 3.0.7 Map-reduce uses custom JavaScript functions to perform the map and reduce operations, as well as the optional finalize operation. While the custom JavaScript provide great flexibility compared to the aggregation pipeline, in general, map- reduce is less efficient and more complex than the aggregation pipeline. Note: Starting in MongoDB 2.4, certain mongo shell functions and properties are inaccessible in map-reduce op- erations. MongoDB 2.4 also provides support for multiple JavaScript operations to run at the same time. Before MongoDB 2.4, JavaScript code executed in a single thread, raising concurrency issues for map-reduce. Single Purpose Aggregation Operations For a number of common single purpose aggregation operations (page 444), MongoDB provides special purpose database commands. These common aggregation operations are: returning a count of matching documents, returning the distinct values for a field, and grouping data based on the values of a field. All of these operations aggregate documents from a single collection. While these operations provide simple access to common aggregation processes, they lack the flexibility and capabilities of the aggregation pipeline and map-reduce. 7.1. Aggregation Introduction 437 MongoDB Documentation, Release 3.0.7 438 Chapter 7. Aggregation MongoDB Documentation, Release 3.0.7 7.1.2 Additional Features and Behaviors Both the aggregation pipeline and map-reduce can operate on a sharded collection (page 661). Map-reduce operations can also output to a sharded collection. See Aggregation Pipeline and Sharded Collections (page 450) and Map-Reduce and Sharded Collections (page 451) for details. The aggregation pipeline can use indexes to improve its performance during some of its stages. In addition, the aggre- gation pipeline has an internal optimization phase. See Pipeline Operators and Indexes (page 441) and Aggregation Pipeline Optimization (page 447) for details. For a feature comparison of the aggregation pipeline, map-reduce, and the special group functionality, see Aggregation Commands Comparison (page 474). 7.1.3 Additional Resources • MongoDB Analytics: Learn Aggregation by Example: Exploratory Analytics and Visualization Using Flight Data1 • MongoDB for Time Series Data: Analyzing Time Series Data Using the Aggregation Framework and Hadoop2 • The Aggregation Framework3 • Webinar: Exploring the Aggregation Framework4 • Quick Reference Cards5 7.2 Aggregation Concepts MongoDB provides the three approaches to aggregation, each with its own strengths and purposes for a given situation. This section describes these approaches and also describes behaviors and limitations specific to each approach. See also the chart (page 474) that compares the approaches. Aggregation Pipeline (page 440) The aggregation pipeline is a framework for performing aggregation tasks, modeled on the concept of data processing pipelines. Using this framework, MongoDB passes the documents of a single collection through a pipeline. The pipeline transforms the documents into aggregated results, and is accessed through the aggregate database command. Map-Reduce (page 442) Map-reduce is a generic multi-phase data aggregation modality for processing quantities of data. MongoDB provides map-reduce with the mapReduce database command. Single Purpose Aggregation Operations (page 444) MongoDB provides a collection of specific data aggregation op- erations to support a number of common data aggregation functions. These operations include returning counts of documents, distinct values of a field, and simple grouping operations. Aggregation Mechanics (page 447) Details internal optimization operations, limits, support for sharded collections, and concurrency concerns. 1http://www.mongodb.com/presentations/mongodb-analytics-learn-aggregation-example-exploratory-analytics-and-visualization?jmp=docs 2http://www.mongodb.com/presentations/mongodb-time-series-data-part-2-analyzing-time-series-data-using-aggregation- framework?jmp=docs 3https://www.mongodb.com/presentations/aggregation-framework-0?jmp=docs 4https://www.mongodb.com/webinar/exploring-the-aggregation-framework?jmp=docs 5https://www.mongodb.com/lp/misc/quick-reference-cards?jmp=docs 7.2. Aggregation Concepts 439 MongoDB Documentation, Release 3.0.7 7.2.1 Aggregation Pipeline New in version 2.2. The aggregation pipeline is a framework for data aggregation modeled on the concept of data processing pipelines. Documents enter a multi-stage pipeline that transforms the documents into an aggregated results. The aggregation pipeline provides an alternative to map-reduce and may be the preferred solution for aggregation tasks where the complexity of map-reduce may be unwarranted. Aggregation pipeline have some limitations on value types and result size. See Aggregation Pipeline Limits (page 450) for details on limits and restrictions on the aggregation pipeline. Pipeline The MongoDB aggregation pipeline consists of stages. Each stage transforms the documents as they pass through the pipeline. Pipeline stages do not need to produce one output document for every input document; e.g., some stages may generate new documents or filter out documents. Pipeline stages can appear multiple times in the pipeline. MongoDB provides the db.collection.aggregate() method in the mongo shell and the aggregate com- mand for aggregation pipeline. See aggregation-pipeline-operator-reference for the available stages. For example usage of the aggregation pipeline, consider Aggregation with User Preference Data (page 456) and Aggregation with the Zip Code Data Set (page 453). 440 Chapter 7. Aggregation MongoDB Documentation, Release 3.0.7 Pipeline Expressions Some pipeline stages takes a pipeline expression as its operand. Pipeline expressions specify the transformation to apply to the input documents. Expressions have a document (page 172) structure and can contain other expression (page 470). Pipeline expressions can only operate on the current document in the pipeline and cannot refer to data from other documents: expression operations provide in-memory transformation of documents. Generally, expressions are stateless and are only evaluated when seen by the aggregation process with one exception: accumulator expressions. The accumulators, used with the $group pipeline operator, maintain their state (e.g. totals, maximums, minimums, and related data) as documents progress through the pipeline. For more information on expressions, see Expressions (page 470). Aggregation Pipeline Behavior In MongoDB, the aggregate command operates on a single collection, logically passing the entire collection into the aggregation pipeline. To optimize the operation, wherever possible, use the following strategies to avoid scanning the entire collection. Pipeline Operators and Indexes The $match and $sort pipeline operators can take advantage of an index when they occur at the beginning of the pipeline. New in version 2.4: The $geoNear pipeline operator takes advantage of a geospatial index. When using $geoNear, the $geoNear pipeline operation must appear as the first stage in an aggregation pipeline. Even when the pipeline uses an index, aggregation still requires access to the actual documents; i.e. indexes cannot fully cover an aggregation pipeline. Changed in version 2.6: In previous versions, for very select use cases, an index could cover a pipeline. Early Filtering If your aggregation operation requires only a subset of the data in a collection, use the $match, $limit, and $skip stages to restrict the documents that enter at the beginning of the pipeline. When placed at the beginning of a pipeline, $match operations use suitable indexes to scan only the matching documents in a collection. Placing a $match pipeline stage followed by a $sort stage at the start of the pipeline is logically equivalent to a single query with a sort and can use an index. When possible, place $match operators at the beginning of the pipeline. Additional Features The aggregation pipeline has an internal optimization phase that provides improved performance for certain sequences of operators. For details, see Aggregation Pipeline Optimization (page 447). The aggregation pipeline supports operations on sharded collections. See Aggregation Pipeline and Sharded Collec- tions (page 450). 7.2. Aggregation Concepts 441 MongoDB Documentation, Release 3.0.7 Additional Resources • MongoDB Analytics: Learn Aggregation by Example: Exploratory Analytics and Visualization Using Flight Data6 • MongoDB for Time Series Data: Analyzing Time Series Data Using the Aggregation Framework and Hadoop7 • The Aggregation Framework8 • Webinar: Exploring the Aggregation Framework9 • Quick Reference Cards10 7.2.2 Map-Reduce Map-reduce is a data processing paradigm for condensing large volumes of data into useful aggregated results. For map-reduce operations, MongoDB provides the mapReduce database command. Consider the following map-reduce operation: In this map-reduce operation, MongoDB applies the map phase to each input document (i.e. the documents in the collection that match the query condition). The map function emits key-value pairs. For those keys that have multiple values, MongoDB applies the reduce phase, which collects and condenses the aggregated data. MongoDB then stores the results in a collection. Optionally, the output of the reduce function may pass through a finalize function to further condense or process the results of the aggregation. All map-reduce functions in MongoDB are JavaScript and run within the mongod process. Map-reduce operations take the documents of a single collection as the input and can perform any arbitrary sorting and limiting before beginning the map stage. mapReduce can return the results of a map-reduce operation as a document, or may write the results to collections. The input and the output collections may be sharded. Note: For most aggregation operations, the Aggregation Pipeline (page 440) provides better performance and more coherent interface. However, map-reduce operations provide some flexibility that is not presently available in the aggregation pipeline. Map-Reduce JavaScript Functions In MongoDB, map-reduce operations use custom JavaScript functions to map, or associate, values to a key. If a key has multiple values mapped to it, the operation reduces the values for the key to a single object. The use of custom JavaScript functions provide flexibility to map-reduce operations. For instance, when processing a document, the map function can create more than one key and value mapping or no mapping. Map-reduce operations can also use a custom JavaScript function to make final modifications to the results at the end of the map and reduce operation, such as perform additional calculations. Map-Reduce Behavior In MongoDB, the map-reduce operation can write results to a collection or return the results inline. If you write map-reduce output to a collection, you can perform subsequent map-reduce operations on the same input collection 6http://www.mongodb.com/presentations/mongodb-analytics-learn-aggregation-example-exploratory-analytics-and-visualization?jmp=docs 7http://www.mongodb.com/presentations/mongodb-time-series-data-part-2-analyzing-time-series-data-using-aggregation- framework?jmp=docs 8https://www.mongodb.com/presentations/aggregation-framework-0?jmp=docs 9https://www.mongodb.com/webinar/exploring-the-aggregation-framework?jmp=docs 10https://www.mongodb.com/lp/misc/quick-reference-cards?jmp=docs 442 Chapter 7. Aggregation MongoDB Documentation, Release 3.0.7 7.2. Aggregation Concepts 443 MongoDB Documentation, Release 3.0.7 that merge replace, merge, or reduce new results with previous results. See mapReduce and Perform Incremental Map-Reduce (page 463) for details and examples. When returning the results of a map reduce operation inline, the result documents must be within the BSON Document Size limit, which is currently 16 megabytes. For additional information on limits and restrictions on map-reduce operations, see the https://docs.mongodb.org/manual/reference/command/mapReduce reference page. MongoDB supports map-reduce operations on sharded collections (page 661). Map-reduce operations can also output the results to a sharded collection. See Map-Reduce and Sharded Collections (page 451). 7.2.3 Single Purpose Aggregation Operations Aggregation refers to a broad class of data manipulation operations that compute a result based on an input and a spe- cific procedure. MongoDB provides a number of aggregation operations that perform specific aggregation operations on a set of data. Although limited in scope, particularly compared to the aggregation pipeline (page 439) and map-reduce (page 442), these operations provide straightforward semantics for common data processing options. Count MongoDB can return a count of the number of documents that match a query. The count command as well as the count() and cursor.count() methods provide access to counts in the mongo shell. Example Given a collection named records with only the following documents: { a:1, b:0} { a:1, b:1} { a:1, b:4} { a:2, b:2} The following operation would count all documents in the collection and return the number 4: db.records.count() The following operation will count only the documents where the value of the field a is 1 and return 3: db.records.count( { a:1}) Distinct The distinct operation takes a number of documents that match a query and returns all of the unique values for a field in the matching documents. The distinct command and db.collection.distinct() method provide this operation in the mongo shell. Consider the following examples of a distinct operation: Example Given a collection named records with only the following documents: { a:1, b:0} { a:1, b:1} { a:1, b:1} { a:1, b:4} 444 Chapter 7. Aggregation MongoDB Documentation, Release 3.0.7 7.2. Aggregation Concepts 445 MongoDB Documentation, Release 3.0.7 { a:2, b:2} { a:2, b:2} Consider the following db.collection.distinct() operation which returns the distinct values of the field b: db.records.distinct( "b") The results of this operation would resemble: [0,1,4,2] Group The group operation takes a number of documents that match a query, and then collects groups of documents based on the value of a field or fields. It returns an array of documents with computed results for each group of documents. Access the grouping functionality via the group command or the db.collection.group() method in the mongo shell. Warning: group does not support data in sharded collections. In addition, the results of the group operation must be no larger than 16 megabytes. Consider the following group operation: Example Given a collection named records with the following documents: { a:1, count:4} { a:1, count:2} { a:1, count:4} { a:2, count:3} { a:2, count:1} { a:1, count:5} { a:4, count:4} Consider the following group operation which groups documents by the field a, where a is less than 3, and sums the field count for each group: db.records.group( { key:{a:1}, cond:{a: { $lt:3}}, reduce: function(cur, result) { result.count += cur.count }, initial: { count:0} }) The results of this group operation would resemble the following: [ { a:1, count: 15}, { a:2, count:4} ] See also: The $group for related functionality in the aggregation pipeline (page 440). 446 Chapter 7. Aggregation MongoDB Documentation, Release 3.0.7 7.2.4 Aggregation Mechanics This section describes behaviors and limitations for the various aggregation modalities. Aggregation Pipeline Optimization (page 447) Details the internal optimization of certain pipeline sequence. Aggregation Pipeline Limits (page 450) Presents limitations on aggregation pipeline operations. Aggregation Pipeline and Sharded Collections (page 450) Mechanics of aggregation pipeline operations on sharded collections. Map-Reduce and Sharded Collections (page 451) Mechanics of map-reduce operation with sharded collections. Map Reduce Concurrency (page 452) Details the locks taken during map-reduce operations. Aggregation Pipeline Optimization Aggregation pipeline operations have an optimization phase which attempts to reshape the pipeline for improved performance. To see how the optimizer transforms a particular aggregation pipeline, include the explain option in the db.collection.aggregate() method. Optimizations are subject to change between releases. Projection Optimization The aggregation pipeline can determine if it requires only a subset of the fields in the documents to obtain the results. If so, the pipeline will only use those required fields, reducing the amount of data passing through the pipeline. Pipeline Sequence Optimization $sort + $match Sequence Optimization When you have a sequence with $sort followed by a $match, the $match moves before the $sort to minimize the number of objects to sort. For example, if the pipeline consists of the following stages: { $sort: { age:-1}}, { $match: { status: 'A'}} During the optimization phase, the optimizer transforms the sequence to the following: { $match: { status: 'A'}}, { $sort: { age:-1}} $skip + $limit Sequence Optimization When you have a sequence with $skip followed by a $limit, the $limit moves before the $skip. With the reordering, the $limit value increases by the $skip amount. For example, if the pipeline consists of the following stages: { $skip: 10}, { $limit:5} During the optimization phase, the optimizer transforms the sequence to the following: { $limit: 15}, { $skip: 10} 7.2. Aggregation Concepts 447 MongoDB Documentation, Release 3.0.7 This optimization allows for more opportunities for $sort + $limit Coalescence (page 448), such as with $sort + $skip + $limit sequences. See $sort + $limit Coalescence (page 448) for details on the coalescence and $sort + $skip + $limit Sequence (page 449) for an example. For aggregation operations on sharded collections (page 450), this optimization reduces the results returned from each shard. $redact + $match Sequence Optimization When possible, when the pipeline has the $redact stage immedi- ately followed by the $match stage, the aggregation can sometimes add a portion of the $match stage before the $redact stage. If the added $match stage is at the start of a pipeline, the aggregation can use an index as well as query the collection to limit the number of documents that enter the pipeline. See Pipeline Operators and Indexes (page 441) for more information. For example, if the pipeline consists of the following stages: { $redact: { $cond:{ if: { $eq:[ "$level",5 ] }, then: "$$PRUNE", else: "$$DESCEND"}}}, { $match: { year: 2014, category: { $ne: "Z"}}} The optimizer can add the same $match stage before the $redact stage: { $match: { year: 2014}}, { $redact: { $cond:{ if: { $eq:[ "$level",5 ] }, then: "$$PRUNE", else: "$$DESCEND"}}}, { $match: { year: 2014, category: { $ne: "Z"}}} Pipeline Coalescence Optimization When possible, the optimization phase coalesces a pipeline stage into its predecessor. Generally, coalescence occurs after any sequence reordering optimization. $sort + $limit Coalescence When a $sort immediately precedes a $limit, the optimizer can coalesce the $limit into the $sort. This allows the sort operation to only maintain the top n results as it progresses, where n is the specified limit, and MongoDB only needs to store n items in memory 11. See sort-and-memory for more information. $limit + $limit Coalescence When a $limit immediately follows another $limit, the two stages can coalesce into a single $limit where the limit amount is the smaller of the two initial limit amounts. For example, a pipeline contains the following sequence: { $limit: 100}, { $limit: 10} Then the second $limit stage can coalesce into the first $limit stage and result in a single $limit stage where the limit amount 10 is the minimum of the two initial limits 100 and 10. { $limit: 10} $skip + $skip Coalescence When a $skip immediately follows another $skip, the two stages can coalesce into a single $skip where the skip amount is the sum of the two initial skip amounts. For example, a pipeline contains the following sequence: { $skip:5}, { $skip:2} 11 The optimization will still apply when allowDiskUse is true and the n items exceed the aggregation memory limit (page 450). 448 Chapter 7. Aggregation MongoDB Documentation, Release 3.0.7 Then the second $skip stage can coalesce into the first $skip stage and result in a single $skip stage where the skip amount 7 is the sum of the two initial limits 5 and 2. { $skip:7} $match + $match Coalescence When a $match immediately follows another $match, the two stages can coalesce into a single $match combining the conditions with an $and. For example, a pipeline contains the following sequence: { $match: { year: 2014}}, { $match: { status: "A"}} Then the second $match stage can coalesce into the first $match stage and result in a single $match stage { $match: { $and:[{ "year": 2014},{ "status": "A"}]}} Examples The following examples are some sequences that can take advantage of both sequence reordering and coalescence. Generally, coalescence occurs after any sequence reordering optimization. $sort + $skip + $limit Sequence A pipeline contains a sequence of $sort followed by a $skip followed by a $limit: { $sort: { age:-1}}, { $skip: 10}, { $limit:5} First, the optimizer performs the $skip + $limit Sequence Optimization (page 447) to transforms the sequence to the following: { $sort: { age:-1}}, { $limit: 15} { $skip: 10} The $skip + $limit Sequence Optimization (page 447) increases the $limit amount with the reordering. See $skip + $limit Sequence Optimization (page 447) for details. The reordered sequence now has $sort immediately preceding the $limit, and the pipeline can coalesce the two stages to decrease memory usage during the sort operation. See $sort + $limit Coalescence (page 448) for more information. $limit + $skip + $limit + $skip Sequence A pipeline contains a sequence of alternating $limit and $skip stages: { $limit: 100}, { $skip:5}, { $limit: 10}, { $skip:2} The $skip + $limit Sequence Optimization (page 447) reverses the position of the { $skip: 5 } and { $limit: 10 } stages and increases the limit amount: 7.2. Aggregation Concepts 449 MongoDB Documentation, Release 3.0.7 { $limit: 100}, { $limit: 15}, { $skip:5}, { $skip:2} The optimizer then coalesces the two $limit stages into a single $limit stage and the two $skip stages into a single $skip stage. The resulting sequence is the following: { $limit: 15}, { $skip:7} See $limit + $limit Coalescence (page 448) and $skip + $skip Coalescence (page 448) for details. See also: explain option in the db.collection.aggregate() Aggregation Pipeline Limits Aggregation operations with the aggregate command have the following limitations. Result Size Restrictions If the aggregate command returns a single document that contains the complete result set, the command will produce an error if the result set exceeds the BSON Document Size limit, which is currently 16 megabytes. To manage result sets that exceed this limit, the aggregate command can return result sets of any size if the command return a cursor or store the results to a collection. Changed in version 2.6: The aggregate command can return results as a cursor or store the results in a collection, which are not subject to the size limit. The db.collection.aggregate() returns a cursor and can return result sets of any size. Memory Restrictions Changed in version 2.6. Pipeline stages have a limit of 100 megabytes of RAM. If a stage exceeds this limit, MongoDB will produce an error. To allow for the handling of large datasets, use the allowDiskUse option to enable aggregation pipeline stages to write data to temporary files. See also: sort-memory-limit and group-memory-limit. Aggregation Pipeline and Sharded Collections The aggregation pipeline supports operations on sharded collections. This section describes behaviors specific to the aggregation pipeline (page 440) and sharded collections. Behavior Changed in version 2.6. 450 Chapter 7. Aggregation MongoDB Documentation, Release 3.0.7 When operating on a sharded collection, the aggregation pipeline is split into two parts. The first pipeline runs on each shard, or if an early $match can exclude shards through the use of the shard key in the predicate, the pipeline runs on only the relevant shards. The second pipeline consists of the remaining pipeline stages and runs on the primary shard (page 669). The primary shard merges the cursors from the other shards and runs the second pipeline on these results. The primary shard forwards the final results to the mongos. In previous versions, the second pipeline would run on the mongos. 12 Optimization When splitting the aggregation pipeline into two parts, the pipeline is split to ensure that the shards perform as many stages as possible with consideration for optimization. To see how the pipeline was split, include the explain option in the db.collection.aggregate() method. Optimizations are subject to change between releases. Map-Reduce and Sharded Collections Map-reduce supports operations on sharded collections, both as an input and as an output. This section describes the behaviors of mapReduce specific to sharded collections. Sharded Collection as Input When using sharded collection as the input for a map-reduce operation, mongos will automatically dispatch the map- reduce job to each shard in parallel. There is no special option required. mongos will wait for jobs on all shards to finish. Sharded Collection as Output Changed in version 2.2. If the out field for mapReduce has the sharded value, MongoDB shards the output collection using the _id field as the shard key. To output to a sharded collection: • If the output collection does not exist, MongoDB creates and shards the collection on the _id field. • For a new or an empty sharded collection, MongoDB uses the results of the first stage of the map-reduce operation to create the initial chunks distributed among the shards. • mongos dispatches, in parallel, a map-reduce post-processing job to every shard that owns a chunk. During the post-processing, each shard will pull the results for its own chunks from the other shards, run the final reduce/finalize, and write locally to the output collection. Note: • During later map-reduce jobs, MongoDB splits chunks as needed. • Balancing of chunks for the output collection is automatically prevented during post-processing to avoid con- currency issues. In MongoDB 2.0: 12 Until all shards upgrade to v2.6, the second pipeline runs on the mongos if any shards are still running v2.4. 7.2. Aggregation Concepts 451 MongoDB Documentation, Release 3.0.7 • mongos retrieves the results from each shard, performs a merge sort to order the results, and proceeds to the reduce/finalize phase as needed. mongos then writes the result to the output collection in sharded mode. • This model requires only a small amount of memory, even for large data sets. • Shard chunks are not automatically split during insertion. This requires manual intervention until the chunks are granular and balanced. Important: For best results, only use the sharded output options for mapReduce in version 2.2 or later. Map Reduce Concurrency The map-reduce operation is composed of many tasks, including reads from the input collection, executions of the map function, executions of the reduce function, writes to a temporary collection during processing, and writes to the output collection. During the operation, map-reduce takes the following locks: • The read phase takes a read lock. It yields every 100 documents. • The insert into the temporary collection takes a write lock for a single write. • If the output collection does not exist, the creation of the output collection takes a write lock. • If the output collection exists, then the output actions (i.e. merge, replace, reduce) take a write lock. This write lock is global, and blocks all operations on the mongod instance. Changed in version 2.4: The V8 JavaScript engine, which became the default in 2.4, allows multiple JavaScript operations to execute at the same time. Prior to 2.4, JavaScript code (i.e. map, reduce, finalize functions) executed in a single thread. Note: The final write lock during post-processing makes the results appear atomically. However, output actions merge and reduce may take minutes to process. For the merge and reduce, the nonAtomic flag is avail- able, which releases the lock between writing each output document. See the db.collection.mapReduce() reference for more information. 7.3 Aggregation Examples This document provides the practical examples that display the capabilities of aggregation (page 439). Aggregation with the Zip Code Data Set (page 453) Use the aggregation pipeline to group values and to calculate aggregated sums and averages for a collection of United States zip codes. Aggregation with User Preference Data (page 456) Use the pipeline to sort, normalize, and sum data on a collection of user data. Map-Reduce Examples (page 460) Define map-reduce operations that select ranges, group data, and calculate sums and averages. Perform Incremental Map-Reduce (page 463) Run a map-reduce operations over one collection and output results to another collection. Troubleshoot the Map Function (page 465) Steps to troubleshoot the map function. Troubleshoot the Reduce Function (page 466) Steps to troubleshoot the reduce function. 452 Chapter 7. Aggregation MongoDB Documentation, Release 3.0.7 7.3.1 Aggregation with the Zip Code Data Set The examples in this document use the zipcodes collection. This collection is available at: me- dia.mongodb.org/zips.json13. Use mongoimport to load this data set into your mongod instance. Data Model Each document in the zipcodes collection has the following form: { "_id": "10280", "city": "NEW YORK", "state": "NY", "pop": 5574, "loc":[ -74.016323, 40.710537 ] } • The _id field holds the zip code as a string. • The city field holds the city name. A city can have more than one zip code associated with it as different sections of the city can each have a different zip code. • The state field holds the two letter state abbreviation. • The pop field holds the population. • The loc field holds the location as a latitude longitude pair. aggregate() Method All of the following examples use the aggregate() helper in the mongo shell. The aggregate() method uses the aggregation pipeline (page 440) to processes documents into aggregated results. An aggregation pipeline (page 440) consists of stages with each stage processing the documents as they pass along the pipeline. Documents pass through the stages in sequence. The aggregate() method in the mongo shell provides a wrapper around the aggregate database command. See the documentation for your driver for a more idiomatic interface for data aggregation operations. Return States with Populations above 10 Million The following aggregation operation returns all states with total population greater than 10 million: db.zipcodes.aggregate( [ { $group: { _id: "$state", totalPop: { $sum: "$pop"}}}, { $match: { totalPop: { $gte: 10*1000*1000}}} ]) In this example, the aggregation pipeline (page 440) consists of the $group stage followed by the $match stage: • The $group stage groups the documents of the zipcode collection by the state field, calculates the totalPop field for each state, and outputs a document for each unique state. 13http://media.mongodb.org/zips.json 7.3. Aggregation Examples 453 MongoDB Documentation, Release 3.0.7 The new per-state documents have two fields: the _id field and the totalPop field. The _id field contains the value of the state; i.e. the group by field. The totalPop field is a calculated field that contains the total population of each state. To calculate the value, $group uses the $sum operator to add the population field (pop) for each state. After the $group stage, the documents in the pipeline resemble the following: { "_id": "AK", "totalPop": 550043 } • The $match stage filters these grouped documents to output only those documents whose totalPop value is greater than or equal to 10 million. The $match stage does not alter the matching documents but outputs the matching documents unmodified. The equivalent SQL for this aggregation operation is: SELECT state, SUM(pop) AS totalPop FROM zipcodes GROUPBY state HAVING totalPop>=(10 *1000*1000) See also: $group, $match, $sum Return Average City Population by State The following aggregation operation returns the average populations for cities in each state: db.zipcodes.aggregate( [ { $group: { _id: { state: "$state", city: "$city" }, pop: { $sum: "$pop"}}}, { $group: { _id: "$_id.state", avgCityPop: { $avg: "$pop"}}} ]) In this example, the aggregation pipeline (page 440) consists of the $group stage followed by another $group stage: • The first $group stage groups the documents by the combination of city and state, uses the $sum ex- pression to calculate the population for each combination, and outputs a document for each city and state combination. 14 After this stage in the pipeline, the documents resemble the following: { "_id":{ "state": "CO", "city": "EDGEWATER" }, "pop": 13154 } • A second $group stage groups the documents in the pipeline by the _id.state field (i.e. the state field inside the _id document), uses the $avg expression to calculate the average city population (avgCityPop) for each state, and outputs a document for each state. The documents that result from this aggregation operation resembles the following: 14 A city can have more than one zip code associated with it as different sections of the city can each have a different zip code. 454 Chapter 7. Aggregation MongoDB Documentation, Release 3.0.7 { "_id": "MN", "avgCityPop": 5335 } See also: $group, $sum, $avg Return Largest and Smallest Cities by State The following aggregation operation returns the smallest and largest cities by population for each state: db.zipcodes.aggregate( [ { $group: { _id: { state: "$state", city: "$city"}, pop: { $sum: "$pop"} } }, { $sort: { pop:1}}, { $group: { _id: "$_id.state", biggestCity: { $last: "$_id.city"}, biggestPop: { $last: "$pop"}, smallestCity: { $first: "$_id.city"}, smallestPop: { $first: "$pop"} } }, // the following $project is optional, and // modifies the output format. { $project: { _id:0, state: "$_id", biggestCity: { name: "$biggestCity", pop: "$biggestPop"}, smallestCity: { name: "$smallestCity", pop: "$smallestPop"} } } ]) In this example, the aggregation pipeline (page 440) consists of a $group stage, a $sort stage, another $group stage, and a $project stage: • The first $group stage groups the documents by the combination of the city and state, calculates the sum of the pop values for each combination, and outputs a document for each city and state combination. At this stage in the pipeline, the documents resemble the following: { "_id":{ "state": "CO", "city": "EDGEWATER" }, "pop": 13154 } 7.3. Aggregation Examples 455 MongoDB Documentation, Release 3.0.7 • The $sort stage orders the documents in the pipeline by the pop field value, from smallest to largest; i.e. by increasing order. This operation does not alter the documents. • The next $group stage groups the now-sorted documents by the _id.state field (i.e. the state field inside the _id document) and outputs a document for each state. The stage also calculates the following four fields for each state. Using the $last expression, the $group operator creates the biggestCity and biggestPop fields that store the city with the largest population and that population. Using the $first expression, the $group operator creates the smallestCity and smallestPop fields that store the city with the smallest population and that population. The documents, at this stage in the pipeline, resemble the following: { "_id": "WA", "biggestCity": "SEATTLE", "biggestPop": 520096, "smallestCity": "BENGE", "smallestPop":2 } • The final $project stage renames the _id field to state and moves the biggestCity, biggestPop, smallestCity, and smallestPop into biggestCity and smallestCity embedded documents. The output documents of this aggregation operation resemble the following: { "state": "RI", "biggestCity":{ "name": "CRANSTON", "pop": 176404 }, "smallestCity":{ "name": "CLAYVILLE", "pop": 45 } } 7.3.2 Aggregation with User Preference Data Data Model Consider a hypothetical sports club with a database that contains a users collection that tracks the user’s join dates, sport preferences, and stores these data in documents that resemble the following: { _id: "jane", joined: ISODate("2011-03-02"), likes:["golf", "racquetball"] } { _id: "joe", joined: ISODate("2012-07-02"), likes:["tennis", "golf", "swimming"] } 456 Chapter 7. Aggregation MongoDB Documentation, Release 3.0.7 Normalize and Sort Documents The following operation returns user names in upper case and in alphabetical order. The aggregation includes user names for all documents in the users collection. You might do this to normalize user names for processing. db.users.aggregate( [ { $project: { name:{$toUpper:"$_id"} , _id:0}}, { $sort: { name:1}} ] ) All documents from the users collection pass through the pipeline, which consists of the following operations: • The $project operator: – creates a new field called name. – converts the value of the _id to upper case, with the $toUpper operator. Then the $project creates a new field, named name to hold this value. – suppresses the id field. $project will pass the _id field by default, unless explicitly suppressed. • The $sort operator orders the results by the name field. The results of the aggregation would resemble the following: { "name": "JANE" }, { "name": "JILL" }, { "name": "JOE" } Return Usernames Ordered by Join Month The following aggregation operation returns user names sorted by the month they joined. This kind of aggregation could help generate membership renewal notices. db.users.aggregate( [ { $project: { month_joined: { $month: "$joined"}, name: "$_id", _id:0 } }, { $sort: { month_joined:1}} ] ) The pipeline passes all documents in the users collection through the following operations: • The $project operator: – Creates two new fields: month_joined and name. 7.3. Aggregation Examples 457 MongoDB Documentation, Release 3.0.7 – Suppresses the id from the results. The aggregate() method includes the _id, unless explicitly suppressed. • The $month operator converts the values of the joined field to integer representations of the month. Then the $project operator assigns those values to the month_joined field. • The $sort operator sorts the results by the month_joined field. The operation returns results that resemble the following: { "month_joined":1, "name": "ruth" }, { "month_joined":1, "name": "harold" }, { "month_joined":1, "name": "kate" } { "month_joined":2, "name": "jill" } Return Total Number of Joins per Month The following operation shows how many people joined each month of the year. You might use this aggregated data for recruiting and marketing strategies. db.users.aggregate( [ { $project: { month_joined: { $month: "$joined"}}}, { $group: { _id: {month_joined:"$month_joined"} , number: { $sum:1}}}, { $sort:{ "_id.month_joined":1}} ] ) The pipeline passes all documents in the users collection through the following operations: • The $project operator creates a new field called month_joined. • The $month operator converts the values of the joined field to integer representations of the month. Then the $project operator assigns the values to the month_joined field. • The $group operator collects all documents with a given month_joined value and counts how many docu- ments there are for that value. Specifically, for each unique value, $group creates a new “per-month” document with two fields: –_id, which contains a nested document with the month_joined field and its value. – number, which is a generated field. The $sum operator increments this field by 1 for every document containing the given month_joined value. • The $sort operator sorts the documents created by $group according to the contents of the month_joined field. The result of this aggregation operation would resemble the following: 458 Chapter 7. Aggregation MongoDB Documentation, Release 3.0.7 { "_id":{ "month_joined":1 }, "number":3 }, { "_id":{ "month_joined":2 }, "number":9 }, { "_id":{ "month_joined":3 }, "number":5 } Return the Five Most Common “Likes” The following aggregation collects top five most “liked” activities in the data set. This type of analysis could help inform planning and future development. db.users.aggregate( [ { $unwind: "$likes"}, { $group: { _id: "$likes" , number: { $sum:1}}}, { $sort: { number:-1}}, { $limit:5} ] ) The pipeline begins with all documents in the users collection, and passes these documents through the following operations: • The $unwind operator separates each value in the likes array, and creates a new version of the source document for every element in the array. Example Given the following document from the users collection: { _id: "jane", joined: ISODate("2011-03-02"), likes:["golf", "racquetball"] } The $unwind operator would create the following documents: { _id: "jane", joined: ISODate("2011-03-02"), likes: "golf" } { _id: "jane", 7.3. Aggregation Examples 459 MongoDB Documentation, Release 3.0.7 joined: ISODate("2011-03-02"), likes: "racquetball" } • The $group operator collects all documents the same value for the likes field and counts each grouping. With this information, $group creates a new document with two fields: –_id, which contains the likes value. – number, which is a generated field. The $sum operator increments this field by 1 for every document containing the given likes value. • The $sort operator sorts these documents by the number field in reverse order. • The $limit operator only includes the first 5 result documents. The results of aggregation would resemble the following: { "_id": "golf", "number": 33 }, { "_id": "racquetball", "number": 31 }, { "_id": "swimming", "number": 24 }, { "_id": "handball", "number": 19 }, { "_id": "tennis", "number": 18 } 7.3.3 Map-Reduce Examples In the mongo shell, the db.collection.mapReduce() method is a wrapper around the mapReduce command. The following examples use the db.collection.mapReduce() method: Consider the following map-reduce operations on a collection orders that contains documents of the following prototype: { _id: ObjectId("50a8240b927d5d8b5891743c"), cust_id: "abc123", ord_date: new Date("Oct 04, 2012"), status: 'A', price: 25, items: [ { sku: "mmm", qty:5, price: 2.5}, { sku: "nnn", qty:5, price: 2.5}] } 460 Chapter 7. Aggregation MongoDB Documentation, Release 3.0.7 Return the Total Price Per Customer Perform the map-reduce operation on the orders collection to group by the cust_id, and calculate the sum of the price for each cust_id: 1. Define the map function to process each input document: • In the function, this refers to the document that the map-reduce operation is processing. • The function maps the price to the cust_id for each document and emits the cust_id and price pair. var mapFunction1= function() { emit(this.cust_id, this.price); }; 2. Define the corresponding reduce function with two arguments keyCustId and valuesPrices: • The valuesPrices is an array whose elements are the price values emitted by the map function and grouped by keyCustId. • The function reduces the valuesPrice array to the sum of its elements. var reduceFunction1= function(keyCustId, valuesPrices) { return Array.sum(valuesPrices); }; 3. Perform the map-reduce on all documents in the orders collection using the mapFunction1 map function and the reduceFunction1 reduce function. db.orders.mapReduce( mapFunction1, reduceFunction1, { out: "map_reduce_example"} ) This operation outputs the results to a collection named map_reduce_example. If the map_reduce_example collection already exists, the operation will replace the contents with the re- sults of this map-reduce operation: Calculate Order and Total Quantity with Average Quantity Per Item In this example, you will perform a map-reduce operation on the orders collection for all documents that have an ord_date value greater than 01/01/2012. The operation groups by the item.sku field, and calculates the number of orders and the total quantity ordered for each sku. The operation concludes by calculating the average quantity per order for each sku value: 1. Define the map function to process each input document: • In the function, this refers to the document that the map-reduce operation is processing. • For each item, the function associates the sku with a new object value that contains the count of 1 and the item qty for the order and emits the sku and value pair. var mapFunction2= function() { for (var idx=0; idx< this.items.length; idx++){ var key= this.items[idx].sku; var value={ count:1, qty: this.items[idx].qty 7.3. Aggregation Examples 461 MongoDB Documentation, Release 3.0.7 }; emit(key, value); } }; 2. Define the corresponding reduce function with two arguments keySKU and countObjVals: • countObjVals is an array whose elements are the objects mapped to the grouped keySKU values passed by map function to the reducer function. • The function reduces the countObjVals array to a single object reducedValue that contains the count and the qty fields. • In reducedVal, the count field contains the sum of the count fields from the individual array ele- ments, and the qty field contains the sum of the qty fields from the individual array elements. var reduceFunction2= function(keySKU, countObjVals) { reducedVal= { count:0, qty:0}; for (var idx=0; idx< countObjVals.length; idx++){ reducedVal.count += countObjVals[idx].count; reducedVal.qty += countObjVals[idx].qty; } return reducedVal; }; 3. Define a finalize function with two arguments key and reducedVal. The function modifies the reducedVal object to add a computed field named avg and returns the modified object: var finalizeFunction2= function (key, reducedVal) { reducedVal.avg= reducedVal.qty/reducedVal.count; return reducedVal; }; 4. Perform the map-reduce operation on the orders collection using the mapFunction2, reduceFunction2, and finalizeFunction2 functions. db.orders.mapReduce( mapFunction2, reduceFunction2, { out: { merge: "map_reduce_example"}, query: { ord_date: { $gt: new Date('01/01/2012')} }, finalize: finalizeFunction2 } ) This operation uses the query field to select only those documents with ord_date greater than new Date(01/01/2012). Then it output the results to a collection map_reduce_example. If the map_reduce_example collection already exists, the operation will merge the existing contents with the results of this map-reduce operation. 462 Chapter 7. Aggregation MongoDB Documentation, Release 3.0.7 7.3.4 Perform Incremental Map-Reduce Map-reduce operations can handle complex aggregation tasks. To perform map-reduce operations, MongoDB provides the mapReduce command and, in the mongo shell, the db.collection.mapReduce() wrapper method. If the map-reduce data set is constantly growing, you may want to perform an incremental map-reduce rather than performing the map-reduce operation over the entire data set each time. To perform incremental map-reduce: 1. Run a map-reduce job over the current collection and output the result to a separate collection. 2. When you have more data to process, run subsequent map-reduce job with: • the query parameter that specifies conditions that match only the new documents. • the out parameter that specifies the reduce action to merge the new results into the existing output collection. Consider the following example where you schedule a map-reduce operation on a sessions collection to run at the end of each day. Data Setup The sessions collection contains documents that log users’ sessions each day, for example: db.sessions.save( { userid: "a", ts: ISODate('2011-11-03 14:17:00'), length: 95}); db.sessions.save( { userid: "b", ts: ISODate('2011-11-03 14:23:00'), length: 110}); db.sessions.save( { userid: "c", ts: ISODate('2011-11-03 15:02:00'), length: 120}); db.sessions.save( { userid: "d", ts: ISODate('2011-11-03 16:45:00'), length: 45}); db.sessions.save( { userid: "a", ts: ISODate('2011-11-04 11:05:00'), length: 105}); db.sessions.save( { userid: "b", ts: ISODate('2011-11-04 13:14:00'), length: 120}); db.sessions.save( { userid: "c", ts: ISODate('2011-11-04 17:00:00'), length: 130}); db.sessions.save( { userid: "d", ts: ISODate('2011-11-04 15:37:00'), length: 65}); Initial Map-Reduce of Current Collection Run the first map-reduce operation as follows: 1. Define the map function that maps the userid to an object that contains the fields userid, total_time, count, and avg_time: var mapFunction= function() { var key= this.userid; var value={ userid: this.userid, total_time: this.length, count:1, avg_time:0 }; emit( key, value ); }; 2. Define the corresponding reduce function with two arguments key and values to calculate the total time and the count. The key corresponds to the userid, and the values is an array whose elements corresponds to the individual objects mapped to the userid in the mapFunction. 7.3. Aggregation Examples 463 MongoDB Documentation, Release 3.0.7 var reduceFunction= function(key, values) { var reducedObject={ userid: key, total_time:0, count:0, avg_time:0 }; values.forEach( function(value) { reducedObject.total_time += value.total_time; reducedObject.count += value.count; } ); return reducedObject; }; 3. Define the finalize function with two arguments key and reducedValue. The function modifies the reducedValue document to add another field average and returns the modified document. var finalizeFunction= function (key, reducedValue) { if (reducedValue.count>0) reducedValue.avg_time= reducedValue.total_time/ reducedValue.count; return reducedValue; }; 4. Perform map-reduce on the session collection using the mapFunction, the reduceFunction, and the finalizeFunction functions. Output the results to a collection session_stat. If the session_stat collection already exists, the operation will replace the contents: db.sessions.mapReduce( mapFunction, reduceFunction, { out: "session_stat", finalize: finalizeFunction } ) Subsequent Incremental Map-Reduce Later, as the sessions collection grows, you can run additional map-reduce operations. For example, add new documents to the sessions collection: db.sessions.save( { userid: "a", ts: ISODate('2011-11-05 14:17:00'), length: 100}); db.sessions.save( { userid: "b", ts: ISODate('2011-11-05 14:23:00'), length: 115}); db.sessions.save( { userid: "c", ts: ISODate('2011-11-05 15:02:00'), length: 125}); db.sessions.save( { userid: "d", ts: ISODate('2011-11-05 16:45:00'), length: 55}); At the end of the day, perform incremental map-reduce on the sessions collection, but use the query field to select only the new documents. Output the results to the collection session_stat, but reduce the contents with the results of the incremental map-reduce: db.sessions.mapReduce( mapFunction, reduceFunction, { 464 Chapter 7. Aggregation MongoDB Documentation, Release 3.0.7 query: { ts: { $gt: ISODate('2011-11-05 00:00:00') } }, out: { reduce: "session_stat"}, finalize: finalizeFunction } ); 7.3.5 Troubleshoot the Map Function The map function is a JavaScript function that associates or “maps” a value with a key and emits the key and value pair during a map-reduce (page 442) operation. To verify the key and value pairs emitted by the map function, write your own emit function. Consider a collection orders that contains documents of the following prototype: { _id: ObjectId("50a8240b927d5d8b5891743c"), cust_id: "abc123", ord_date: new Date("Oct 04, 2012"), status: 'A', price: 250, items: [ { sku: "mmm", qty:5, price: 2.5}, { sku: "nnn", qty:5, price: 2.5}] } 1. Define the map function that maps the price to the cust_id for each document and emits the cust_id and price pair: var map= function() { emit(this.cust_id, this.price); }; 2. Define the emit function to print the key and value: var emit= function(key, value) { print("emit"); print("key: "+ key+ " value: "+ tojson(value)); } 3. Invoke the map function with a single document from the orders collection: var myDoc= db.orders.findOne( { _id: ObjectId("50a8240b927d5d8b5891743c") } ); map.apply(myDoc); 4. Verify the key and value pair is as you expected. emit key: abc123 value:250 5. Invoke the map function with multiple documents from the orders collection: var myCursor= db.orders.find( { cust_id: "abc123"}); while (myCursor.hasNext()) { var doc= myCursor.next(); print ("document _id= "+ tojson(doc._id)); map.apply(doc); print(); } 7.3. Aggregation Examples 465 MongoDB Documentation, Release 3.0.7 6. Verify the key and value pairs are as you expected. See also: The map function must meet various requirements. For a list of all the requirements for the map function, see mapReduce, or the mongo shell helper method db.collection.mapReduce(). 7.3.6 Troubleshoot the Reduce Function The reduce function is a JavaScript function that “reduces” to a single object all the values associated with a par- ticular key during a map-reduce (page 442) operation. The reduce function must meet various requirements. This tutorial helps verify that the reduce function meets the following criteria: • The reduce function must return an object whose type must be identical to the type of the value emitted by the map function. • The order of the elements in the valuesArray should not affect the output of the reduce function. • The reduce function must be idempotent. For a list of all the requirements for the reduce function, see mapReduce, or the mongo shell helper method db.collection.mapReduce(). Confirm Output Type You can test that the reduce function returns a value that is the same type as the value emitted from the map function. 1. Define a reduceFunction1 function that takes the arguments keyCustId and valuesPrices. valuesPrices is an array of integers: var reduceFunction1= function(keyCustId, valuesPrices) { return Array.sum(valuesPrices); }; 2. Define a sample array of integers: var myTestValues=[5,5, 10]; 3. Invoke the reduceFunction1 with myTestValues: reduceFunction1('myKey', myTestValues); 4. Verify the reduceFunction1 returned an integer: 20 5. Define a reduceFunction2 function that takes the arguments keySKU and valuesCountObjects. valuesCountObjects is an array of documents that contain two fields count and qty: var reduceFunction2= function(keySKU, valuesCountObjects) { reducedValue= { count:0, qty:0}; for (var idx=0; idx< valuesCountObjects.length; idx++){ reducedValue.count += valuesCountObjects[idx].count; reducedValue.qty += valuesCountObjects[idx].qty; } return reducedValue; }; 466 Chapter 7. Aggregation MongoDB Documentation, Release 3.0.7 6. Define a sample array of documents: var myTestObjects=[ { count:1, qty:5}, { count:2, qty: 10}, { count:3, qty: 15} ]; 7. Invoke the reduceFunction2 with myTestObjects: reduceFunction2('myKey', myTestObjects); 8. Verify the reduceFunction2 returned a document with exactly the count and the qty field: { "count":6, "qty": 30} Ensure Insensitivity to the Order of Mapped Values The reduce function takes a key and a values array as its argument. You can test that the result of the reduce function does not depend on the order of the elements in the values array. 1. Define a sample values1 array and a sample values2 array that only differ in the order of the array elements: var values1=[ { count:1, qty:5}, { count:2, qty: 10}, { count:3, qty: 15} ]; var values2=[ { count:3, qty: 15}, { count:1, qty:5}, { count:2, qty: 10} ]; 2. Define a reduceFunction2 function that takes the arguments keySKU and valuesCountObjects. valuesCountObjects is an array of documents that contain two fields count and qty: var reduceFunction2= function(keySKU, valuesCountObjects) { reducedValue= { count:0, qty:0}; for (var idx=0; idx< valuesCountObjects.length; idx++){ reducedValue.count += valuesCountObjects[idx].count; reducedValue.qty += valuesCountObjects[idx].qty; } return reducedValue; }; 3. Invoke the reduceFunction2 first with values1 and then with values2: reduceFunction2('myKey', values1); reduceFunction2('myKey', values2); 4. Verify the reduceFunction2 returned the same result: { "count":6, "qty": 30} 7.3. Aggregation Examples 467 MongoDB Documentation, Release 3.0.7 Ensure Reduce Function Idempotence Because the map-reduce operation may call a reduce multiple times for the same key, and won’t call a reduce for single instances of a key in the working set, the reduce function must return a value of the same type as the value emitted from the map function. You can test that the reduce function process “reduced” values without affecting the final value. 1. Define a reduceFunction2 function that takes the arguments keySKU and valuesCountObjects. valuesCountObjects is an array of documents that contain two fields count and qty: var reduceFunction2= function(keySKU, valuesCountObjects) { reducedValue= { count:0, qty:0}; for (var idx=0; idx< valuesCountObjects.length; idx++){ reducedValue.count += valuesCountObjects[idx].count; reducedValue.qty += valuesCountObjects[idx].qty; } return reducedValue; }; 2. Define a sample key: var myKey= 'myKey'; 3. Define a sample valuesIdempotent array that contains an element that is a call to the reduceFunction2 function: var valuesIdempotent=[ { count:1, qty:5}, { count:2, qty: 10}, reduceFunction2(myKey, [ { count:3, qty: 15}]) ]; 4. Define a sample values1 array that combines the values passed to reduceFunction2: var values1=[ { count:1, qty:5}, { count:2, qty: 10}, { count:3, qty: 15} ]; 5. Invoke the reduceFunction2 first with myKey and valuesIdempotent and then with myKey and values1: reduceFunction2(myKey, valuesIdempotent); reduceFunction2(myKey, values1); 6. Verify the reduceFunction2 returned the same result: { "count":6, "qty": 30} 7.3.7 Additional Resources • MongoDB Analytics: Learn Aggregation by Example: Exploratory Analytics and Visualization Using Flight Data15 15http://www.mongodb.com/presentations/mongodb-analytics-learn-aggregation-example-exploratory-analytics-and-visualization?jmp=docs 468 Chapter 7. Aggregation MongoDB Documentation, Release 3.0.7 • MongoDB for Time Series Data: Analyzing Time Series Data Using the Aggregation Framework and Hadoop16 • The Aggregation Framework17 • Webinar: Exploring the Aggregation Framework18 • Quick Reference Cards19 7.4 Aggregation Reference Aggregation Pipeline Quick Reference (page 469) Quick reference card for aggregation pipeline. https://docs.mongodb.org/manual/reference/operator/aggregation Aggregation pipeline operations have a collection of operators available to define and manipulate documents in pipeline stages. Aggregation Commands Comparison (page 474) A comparison of group, mapReduce and aggregate that ex- plores the strengths and limitations of each aggregation modality. SQL to Aggregation Mapping Chart (page 476) An overview common aggregation operations in SQL and Mon- goDB using the aggregation pipeline and operators in MongoDB and common SQL statements. Aggregation Commands (page 478) The reference for the data aggregation commands, which provide the interfaces to MongoDB’s aggregation capability. Variables in Aggregation Expressions (page 478) Use of variables in aggregation pipeline expressions. 7.4.1 Aggregation Pipeline Quick Reference Stages Pipeline stages appear in an array. Documents pass through the stages in sequence. All except the $out and $geoNear stages can appear multiple times in a pipeline. db.collection.aggregate( [ { }, ... ] ) 16http://www.mongodb.com/presentations/mongodb-time-series-data-part-2-analyzing-time-series-data-using-aggregation- framework?jmp=docs 17https://www.mongodb.com/presentations/aggregation-framework-0?jmp=docs 18https://www.mongodb.com/webinar/exploring-the-aggregation-framework?jmp=docs 19https://www.mongodb.com/lp/misc/quick-reference-cards?jmp=docs 7.4. Aggregation Reference 469 MongoDB Documentation, Release 3.0.7 Name Description $projectReshapes each document in the stream, such as by adding new fields or removing existing fields. For each input document, outputs one document. $match Filters the document stream to allow only matching documents to pass unmodified into the next pipeline stage. $match uses standard MongoDB queries. For each input document, outputs either one document (a match) or zero documents (no match). $redactReshapes each document in the stream by restricting the content for each document based on information stored in the documents themselves. Incorporates the functionality of $project and $match. Can be used to implement field level redaction. For each input document, outputs either one or zero document. $limit Passes the first n documents unmodified to the pipeline where n is the specified limit. For each input document, outputs either one document (for the first n documents) or zero documents (after the first n documents). $skip Skips the first n documents where n is the specified skip number and passes the remaining documents unmodified to the pipeline. For each input document, outputs either zero documents (for the first n documents) or one document (if after the first n documents). $unwindDeconstructs an array field from the input documents to output a document for each element. Each output document replaces the array with an element value. For each input document, outputs n documents where n is the number of array elements and can be zero for an empty array. $group Groups input documents by a specified identifier expression and applies the accumulator expression(s), if specified, to each group. Consumes all input documents and outputs one document per each distinct group. The output documents only contain the identifier field and, if specified, accumulated fields. $sort Reorders the document stream by a specified sort key. Only the order changes; the documents remain unmodified. For each input document, outputs one document. $geoNearReturns an ordered stream of documents based on the proximity to a geospatial point. Incorporates the functionality of $match, $sort, and $limit for geospatial data. The output documents include an additional distance field and can include a location identifier field. $out Writes the resulting documents of the aggregation pipeline to a collection. To use the $out stage, it must be the last stage in the pipeline. Expressions Expressions can include field paths and system variables (page 470), literals (page 471), expression objects (page 471), and expression operators (page 471). Expressions can be nested. Field Path and System Variables Aggregation expressions use field path to access fields in the input documents. To specify a field path, use a string that prefixes with a dollar sign $ the field name or the dotted field name, if the field is in embedded document. For example, "$user" to specify the field path for the user field or "$user.name" to specify the field path to "user.name" field. "$" is equivalent to "$$CURRENT." where the CURRENT (page 479) is a system variable that defaults to the root of the current object in the most stages, unless stated otherwise in specific stages. CURRENT (page 479) can be rebound. Along with the CURRENT (page 479) system variable, other system variables (page 478) are also available for use in expressions. To use user-defined variables, use $let and $map expressions. To access variables in expressions, use a string that prefixes the variable name with $$. 470 Chapter 7. Aggregation MongoDB Documentation, Release 3.0.7 Literals Literals can be of any type. However, MongoDB parses string literals that start with a dollar sign $ as a path to a field and numeric/boolean literals in expression objects (page 471) as projection flags. To avoid parsing literals, use the $literal expression. Expression Objects Expression objects have the following form: {:, ... } If the expressions are numeric or boolean literals, MongoDB treats the literals as projection flags (e.g. 1 or true to include the field), valid only in the $project stage. To avoid treating numeric or boolean literals as projection flags, use the $literal expression to wrap the numeric or boolean literals. Operator Expressions Operator expressions are similar to functions that take arguments. In general, these expressions take an array of arguments and have the following form: {:[, ... ] } If operator accepts a single argument, you can omit the outer array designating the argument list: {:} To avoid parsing ambiguity if the argument is a literal array, you must wrap the literal array in a $literal expression or keep the outer array that designates the argument list. Boolean Expressions Boolean expressions evaluate their argument expressions as booleans and return a boolean as the result. In addition to the false boolean value, Boolean expression evaluates as false the following: null, 0, and undefined values. The Boolean expression evaluates all other values as true, including non-zero numeric values and arrays. Name Description $and Returns true only when all its expressions evaluate to true. Accepts any number of argument expressions. $or Returns true when any of its expressions evaluates to true. Accepts any number of argument expressions. $not Returns the boolean value that is the opposite of its argument expression. Accepts a sing