Hadoop log4j日志说明
log4j.propertites # Define some default values that can be overridden by system properties hadoop.root.logger=INFO,console hadoop.log.dir=. hadoop.log.file=hadoop.log # # Job Summary Appender # # Use following logger to send summary to separate file defined by # hadoop.mapreduce.jobsummary.log.file rolled daily: # hadoop.mapreduce.jobsummary.logger=INFO,JSA # hadoop.mapreduce.jobsummary.logger=${hadoop.root.logger} hadoop.mapreduce.jobsummary.log.file=hadoop-mapreduce.jobsummary.log # Define the root logger to the system property "hadoop.root.logger". log4j.rootLogger=${hadoop.root.logger}, EventCounter # Logging Threshold log4j.threshhold=ALL # # Daily Rolling File Appender # log4j.appender.DRFA=org.apache.log4j.DailyRollingFileAppender log4j.appender.DRFA.File=${hadoop.log.dir}/${hadoop.log.file} # Rollver at midnight log4j.appender.DRFA.DatePattern=.yyyy-MM-dd # 30-day backup #log4j.appender.DRFA.MaxBackupIndex=30 log4j.appender.DRFA.layout=org.apache.log4j.PatternLayout # Pattern format: Date LogLevel LoggerName LogMessage #log4j.appender.DRFA.layout.ConversionPattern=%l %m%n # Debugging Pattern format 日志文件格式 log4j.appender.DRFA.layout.ConversionPattern=%d{ISO8601} %-5p %c{2} (%F:%M(%L)) - %m%n # # console # Add "console" to rootlogger above if you want to use this # log4j.appender.console=org.apache.log4j.ConsoleAppender log4j.appender.console.target=System.err log4j.appender.console.layout=org.apache.log4j.PatternLayout log4j.appender.console.layout.ConversionPattern=%l: %m%n # # TaskLog Appender # #Default values hadoop.tasklog.taskid=null hadoop.tasklog.iscleanup=false hadoop.tasklog.noKeepSplits=4 hadoop.tasklog.totalLogFileSize=100 hadoop.tasklog.purgeLogSplits=true hadoop.tasklog.logsRetainHours=12 log4j.appender.TLA=org.apache.hadoop.mapred.TaskLogAppender log4j.appender.TLA.taskId=${hadoop.tasklog.taskid} log4j.appender.TLA.isCleanup=${hadoop.tasklog.iscleanup} log4j.appender.TLA.totalLogFileSize=${hadoop.tasklog.totalLogFileSize} log4j.appender.TLA.layout=org.apache.log4j.PatternLayout log4j.appender.TLA.layout.ConversionPattern=%l %p %c: %m%n # #Security audit appender # hadoop.security.log.file=SecurityAuth.audit log4j.appender.DRFAS=org.apache.log4j.DailyRollingFileAppender log4j.appender.DRFAS.File=${hadoop.log.dir}/${hadoop.security.log.file} log4j.appender.DRFAS.layout=org.apache.log4j.PatternLayout log4j.appender.DRFAS.layout.ConversionPattern=%l %p %c: %m%n #new logger log4j.logger.SecurityLogger=OFF,console log4j.logger.SecurityLogger.additivity=false # # Rolling File Appender # #log4j.appender.RFA=org.apache.log4j.RollingFileAppender #log4j.appender.RFA.File=${hadoop.log.dir}/${hadoop.log.file} # Logfile size and and 30-day backups #log4j.appender.RFA.MaxFileSize=1MB #log4j.appender.RFA.MaxBackupIndex=30 #log4j.appender.RFA.layout=org.apache.log4j.PatternLayout #log4j.appender.RFA.layout.ConversionPattern=%d{ISO8601} %-5p %c{2} - %m%n #log4j.appender.RFA.layout.ConversionPattern=%d{ISO8601} %-5p %c{2} (%F:%M(%L)) - %m%n # # FSNamesystem Audit logging # All audit events are logged at INFO level # log4j.logger.org.apache.hadoop.hdfs.server.namenode.FSNamesystem.audit=DEBUG # Custom Logging levels hadoop.metrics.log.level=DEBUG #log4j.logger.org.apache.hadoop.mapred.JobTracker=DEBUG #log4j.logger.org.apache.hadoop.mapred.TaskTracker=DEBUG #log4j.logger.org.apache.hadoop.fs.FSNamesystem=DEBUG #应该是设置包下类的日志级别 log4j.logger.org.apache.hadoop.metrics2=${hadoop.metrics.log.level} # Jets3t library log4j.logger.org.jets3t.service.impl.rest.httpclient.RestS3Service=ERROR # # Null Appender # Trap security logger on the hadoop client side # log4j.appender.NullAppender=org.apache.log4j.varia.NullAppender # # Event Counter Appender # Sends counts of logging messages at different severity levels to Hadoop Metrics. # log4j.appender.EventCounter=org.apache.hadoop.log.metrics.EventCounter # # Job Summary Appender # log4j.appender.JSA=org.apache.log4j.DailyRollingFileAppender log4j.appender.JSA.File=${hadoop.log.dir}/${hadoop.mapreduce.jobsummary.log.file} log4j.appender.JSA.layout=org.apache.log4j.PatternLayout log4j.appender.JSA.layout.ConversionPattern=%l %p %c{2}: %m%n log4j.appender.JSA.DatePattern=.yyyy-MM-dd log4j.logger.org.apache.hadoop.mapred.JobInProgress$JobSummary=${hadoop.mapreduce.jobsummary.logger} log4j.additivity.org.apache.hadoop.mapred.JobInProgress$JobSummary=false
hadoop日志级别设置
在hadoop/bin/ hadoop-daemon.sh文件下
export HADOOP_ROOT_LOGGER="DEBUG,DRFA"
自定义日志
目标：将需要的信息写入自己指定的独立的日志中。
需求：这次只是一个尝试，在DFSClient中，将部分内容写入指定的日志文件中。在客户端读取HDFS数据时，将读的blockID写入文件。
步骤：
1、修改hadoop/conf/log4j.properties文件。在文件末尾添加如下内容：
#为写日志的操作取个名字，MyDFSClient。用来在DFSClient中获取该日志的实例。并指定输出方式为自定义的OUT
log4j.logger.MyDFSClient=DEBUG,OUT
#设置OUT的输出方式为输出到文件
log4j.appender.OUT=org.apache.log4j.FileAppender
#设置文件路径
log4j.appender.OUT.File=${hadoop.log.dir}/DFSClient.log
#设置文件的布局
log4j.appender.OUT.layout=org.apache.log4j.PatternLayout
#设置文件的格式
log4j.appender.OUT.layout.ConversionPattern=%d{ISO8601} %p %c: %m%n
#设置该日志操作不与父类日志操作重叠
log4j.additivity.MyDFSClient=false
2、保存该文件，复制到集群各个节点的hadoop/conf目录下，替换原有的文件。
3、修改DFSClient类
这里只是简单的为了验证这个过程的正确性，以后还回加入更有意义的日志内容。
首先在DFSClient类中声明一个LOG实例：
public static final Log myLOG = LogFactory.getLog("MyDFSClient");
在read(byte buf[], int off, int len)函数中，添加如下代码：
myLOG.info("Read Block!!!!");
if(currentBlock!=null)
myLOG.info("Read block: "+currentBlock.getBlockId());
4、重新启动hadoop。
5、这里使用dfs命令进行测试。
$bin/hadoop dfs -cat /user/XXX/out/part-r-00000
可以看到文件part-r-00000的内容输出到屏幕。这时在/hadoop/logs/DFSClient.log文件中，可以看到刚才在类中记录的日志。验证成功。