InfluxDB读写性能测试

dylan_zb 3年前
   <p>今天进行了InfluxDB和MySQL的对比测试,这里记录下结果,也方便我以后查阅。</p>    <p>操作系统: CentOS6.5_x64</p>    <p>InfluxDB版本 : v1.1.0</p>    <p>MySQL版本:v5.1.73</p>    <p>CPU : Intel(R) Core(TM) i5-2320 CPU @ 3.00GHz</p>    <p>内存 :12G</p>    <p>硬盘 :SSD </p>    <h2>一、MySQL读写测试</h2>    <h3>测试准备</h3>    <p>初始化SQL语句:</p>    <pre>  <code class="language-cpp">CREATE DATABASE testMysql;  CREATE TABLE `monitorStatus` (      `system_name` VARCHAR(20) NOT NULL,      `site_name` VARCHAR(50) NOT NULL,      `equipment_name` VARCHAR(50) NOT NULL,      `current_value` DOUBLE NOT NULL,      `timestamp` BIGINT(20) NULL DEFAULT NULL,      INDEX `system_name` (`system_name`),      INDEX `site_name` (`site_name`),      INDEX `equipment_name` (`equipment_name`),      INDEX `timestamp` (`timestamp`)  )  ENGINE=InnoDB;  </code></pre>    <p>单写测试代码(insertTest1.c):</p>    <pre>  <code class="language-cpp">  #include <stdlib.h>    #include <stdio.h>    #include <time.h>  #include "mysql/mysql.h"    #define N 100    int main()  {      MYSQL *conn_ptr;        int res;        int t,i,j;      int64_t tstamp = 1486872962;              srand(time(NULL));      t=0;      conn_ptr = mysql_init(NULL);        if (!conn_ptr)      {            printf("mysql_init failed\n");            return EXIT_FAILURE;        }        conn_ptr = mysql_real_connect(conn_ptr,"localhost","root","","testMysql",0,NULL,0);        if (conn_ptr)      {            for(i=1;i<= 10000;i++)          {              mysql_query(conn_ptr,"begin");              for(j=0;j<N;j++,t++)              {                  char query[1024]={0};                    sprintf(query,"insert into monitorStatus values ('sys_%d','s_%d','e_%d','0.%02d','%lld');",                      //j%10,(t+i)%10,(t+j)%10,(t+i+j)%100,tstamp);                      j%10,(t+i)%10,(t+j)%10,rand()%100,tstamp);                  //printf("query : %s\n",query);                  res = mysql_query(conn_ptr,query);                    if (!res)                  {                         //printf("Inserted %lu rows\n",(unsigned long)mysql_affected_rows(conn_ptr));                     }                  else                  {                         fprintf(stderr, "Insert error %d: %sn",mysql_errno(conn_ptr),mysql_error(conn_ptr));                    }                  if(j%10 == 0) tstamp+=1;              }              mysql_query(conn_ptr,"commit");              //printf("i=%d\n",i);          }      }      else      {            printf("Connection failed\n");        }        mysql_close(conn_ptr);        return EXIT_SUCCESS;    }    View Code</code></pre>    <p>可根据情况调整测试代码中的N参数。</p>    <p>单读测试代码(queryTest1.c):</p>    <pre>  <code class="language-cpp">  #include <stdio.h>    #include <stdlib.h>    #include "mysql/mysql.h"    int main()  {        MYSQL *conn_ptr;        MYSQL_RES *res_ptr;        MYSQL_ROW sqlrow;        MYSQL_FIELD *fd;        int res, i, j;          conn_ptr = mysql_init(NULL);        if (!conn_ptr)      {            return EXIT_FAILURE;        }        conn_ptr = mysql_real_connect(conn_ptr,"localhost","root","","testMysql", 0, NULL, 0);        if (conn_ptr)      {            res = mysql_query(conn_ptr,"select * from `monitorStatus` where system_name='sys_8' and site_name='s_9' and equipment_name='e_6' order by timestamp desc limit 10000;");            if (res)          {                       printf("SELECT error:%s\n",mysql_error(conn_ptr));               }          else          {                      res_ptr = mysql_store_result(conn_ptr);                           if(res_ptr)              {                                 printf("%lu Rows\n",(unsigned long)mysql_num_rows(res_ptr));                     j = mysql_num_fields(res_ptr);                            while((sqlrow = mysql_fetch_row(res_ptr)))                    {                        continue;                      for(i = 0; i < j; i++)                                   printf("%s\t", sqlrow[i]);                                      printf("\n");                            }                                if (mysql_errno(conn_ptr))                  {                                            fprintf(stderr,"Retrive error:s\n",mysql_error(conn_ptr));                                 }                      }                      mysql_free_result(res_ptr);                  }        }      else      {            printf("Connection failed\n");        }        mysql_close(conn_ptr);        return EXIT_SUCCESS;    }      View Code</code></pre>    <p>Makefile文件:</p>    <pre>  <code class="language-cpp">all:      gcc -g insertTest1.c -o insertTest1 -L/usr/lib64/mysql/ -lmysqlclient      gcc -g queryTest1.c -o queryTest1 -L/usr/lib64/mysql/ -lmysqlclient    clean:      rm -rf insertTest1      rm -rf queryTest1      </code></pre>    <h3>测试数据记录</h3>    <p>磁盘空间占用查询:</p>    <p>使用du方式(新数据库,仅为测试):</p>    <pre>  <code class="language-cpp">du -sh /var/lib/mysql  </code></pre>    <p>查询特定表:</p>    <pre>  <code class="language-cpp">use information_schema;  select concat(round(sum(DATA_LENGTH/1024/1024), 2), 'MB') as data from TABLES where table_schema='testMysql' and table_name='monitorStatus';  </code></pre>    <p>测试结果:</p>    <ul>     <li> <p>100万条数据</p> <pre>  <code class="language-cpp">[root@localhost mysqlTest]# time ./insertTest1    real    1m20.645s  user    0m8.238s  sys    0m5.931s    [root@localhost mysqlTest]# time ./queryTest1  10000 Rows    real    0m0.269s  user    0m0.006s  sys    0m0.002s  </code></pre> <p>原始数据 : 28.6M</p> <p>du方式 : 279MB</p> <p>sql查询方式: 57.59MB</p> <p>写入速度: 12398 / s</p> <p>读取速度: 37174 / s</p> </li>     <li>1000万条数据 <pre>  <code class="language-cpp">root@localhost mysqlTest]# time ./insertTest1    real    7m15.003s  user    0m48.187s  sys    0m33.885s      [root@localhost mysqlTest]# time ./queryTest1  10000 Rows    real    0m6.592s  user    0m0.005s  sys    0m0.002s  </code></pre> <p>原始数据 : 286M</p> <p>du方式 : 2.4G</p> <p>sql查询方式: 572MB</p> <p>写入速度: 22988 / s</p> <p>读取速度: 1516 / s</p> </li>     <li>3000万条数据 <pre>  <code class="language-cpp">[root@localhost mysqlTest]# time ./insertTest1    real    20m38.235s  user    2m21.459s  sys    1m40.329s  [root@localhost mysqlTest]# time ./queryTest1  10000 Rows    real    0m4.421s  user    0m0.004s  sys    0m0.004s  </code></pre> <p>原始数据 : 858M</p> <p>du方式 : 7.1G</p> <p>sql查询方式: 1714MB</p> <p>写入速度: 24228 / s</p> <p>读取速度: 2261 / s</p> </li>    </ul>    <h2>二、InfluxDB读写测试</h2>    <h3>测试准备</h3>    <p>需要将InfluxDB的源码放入 go/src/github.com/influxdata 目录</p>    <p>单写测试代码(write1.go):</p>    <pre>  <code class="language-cpp">  package main    import (      "log"      "time"      "fmt"      "math/rand"      "github.com/influxdata/influxdb/client/v2"  )    const (      MyDB = "testInfluxdb"      username = "root"      password = ""  )    func queryDB(clnt client.Client, cmd string) (res []client.Result, err error) {      q := client.Query{          Command:  cmd,          Database: MyDB,      }      if response, err := clnt.Query(q); err == nil {          if response.Error() != nil {              return res, response.Error()          }          res = response.Results      } else {          return res, err      }      return res, nil  }    func writePoints(clnt client.Client,num int) {      sampleSize := 1 * 10000      rand.Seed(42)      t := num      bp, _ := client.NewBatchPoints(client.BatchPointsConfig{          Database:  MyDB,          Precision: "us",      })        for i := 0; i < sampleSize; i++ {          t += 1          tags := map[string]string{              "system_name": fmt.Sprintf("sys_%d",i%10),              "site_name":fmt.Sprintf("s_%d", (t+i) % 10),              "equipment_name":fmt.Sprintf("e_%d",t % 10),          }          fields := map[string]interface{}{              "value" : fmt.Sprintf("%d",rand.Int()),          }          pt, err := client.NewPoint("monitorStatus", tags, fields,time.Now())          if err != nil {              log.Fatalln("Error: ", err)          }          bp.AddPoint(pt)      }        err := clnt.Write(bp)      if err != nil {          log.Fatal(err)      }        //fmt.Printf("%d task done\n",num)  }    func main() {      // Make client      c, err := client.NewHTTPClient(client.HTTPConfig{          Addr: "http://localhost:8086",          Username: username,          Password: password,      })        if err != nil {          log.Fatalln("Error: ", err)      }      _, err = queryDB(c, fmt.Sprintf("CREATE DATABASE %s", MyDB))      if err != nil {          log.Fatal(err)      }        i := 1      for i <= 10000 {          defer writePoints(c,i)          //fmt.Printf("i=%d\n",i)          i += 1      }      //fmt.Printf("task done : i=%d \n",i)    }    View Code</code></pre>    <p>单读测试代码(query1.go):</p>    <pre>  <code class="language-cpp">  package main    import (      "log"      //"time"      "fmt"      //"math/rand"      "github.com/influxdata/influxdb/client/v2"  )    const (      MyDB = "testInfluxdb"      username = "root"      password = ""  )    func queryDB(clnt client.Client, cmd string) (res []client.Result, err error) {      q := client.Query{          Command:  cmd,          Database: MyDB,      }      if response, err := clnt.Query(q); err == nil {          if response.Error() != nil {              return res, response.Error()          }          res = response.Results      } else {          return res, err      }      return res, nil  }    func main() {      // Make client      c, err := client.NewHTTPClient(client.HTTPConfig{          Addr: "http://localhost:8086",          Username: username,          Password: password,      })        if err != nil {          log.Fatalln("Error: ", err)      }      q := fmt.Sprintf("select * from monitorStatus where system_name='sys_5' and site_name='s_1' and equipment_name='e_6' order by time desc limit 10000 ;")      res, err2 := queryDB(c, q)      if err2 != nil {          log.Fatal(err)      }      count := len(res[0].Series[0].Values)      log.Printf("Found a total of %v records\n", count)    }    View Code</code></pre>    <h3>测试结果记录</h3>    <p>查看整体磁盘空间占用:</p>    <pre>  <code class="language-cpp">du -sh /var/lib/influxdb/  </code></pre>    <p>查看最终磁盘空间占用:</p>    <pre>  <code class="language-cpp">du -sh /var/lib/influxdb/data/testInfluxdb   </code></pre>    <ul>     <li>100万条数据 <pre>  <code class="language-cpp">[root@localhost goTest2]# time ./write1  real    0m14.594s  user    0m11.475s  sys    0m0.251s    [root@localhost goTest2]# time ./query1  2017/02/12 20:00:24 Found a total of 10000 records    real    0m0.222s  user    0m0.052s  sys    0m0.009s  </code></pre> <p>原始数据 : 28.6M</p> <p>整体磁盘占用:27M</p> <p>最终磁盘占用:21M</p> <p>写入速度: 68521 / s</p> <p>读取速度: 45045 / s</p> </li>     <li> <p>1000万条数据</p> <pre>  <code class="language-cpp">[root@localhost goTest2]# time ./write1    real    2m22.520s  user    1m51.704s  sys    0m2.532s    [root@localhost goTest2]# time ./query1  2017/02/12 20:05:16 Found a total of 10000 records    real    0m0.221s  user    0m0.050s  sys    0m0.003s  </code></pre> <p>原始数据 : 286M</p> <p>整体磁盘占用:214M</p> <p>最终磁盘占用:189M 写入速度: 70165 / s</p> <p>读取速度: 45249 / s</p> </li>     <li>3000万条数据 <pre>  <code class="language-cpp">[root@localhost goTest2]# time ./write1    real    7m19.121s  user    5m49.738s  sys    0m8.189s  [root@localhost goTest2]# ls  query1  query1.go  write1  write1.go  [root@localhost goTest2]# time ./query1  2017/02/12 20:49:40 Found a total of 10000 records    real    0m0.233s  user    0m0.050s  sys    0m0.012s  </code></pre> <p>原始数据 : 858M</p> <p>整体磁盘占用:623M</p> <p>最终磁盘占用:602M</p> <p>写入速度: 68318 / s</p> <p>读取速度: 42918 / s</p> </li>    </ul>    <h2>三、测试结果分析</h2>    <p>整体磁盘占用情况对比:</p>    <p style="text-align:center"><img src="https://simg.open-open.com/show/00bfbb7ad683287c367d51a725485df5.png"></p>    <p>最终磁盘占用情况对比:</p>    <p style="text-align:center"><img src="https://simg.open-open.com/show/50e10435d6c250bc77d0c9da0ab3c612.png"></p>    <p>写入速度对比:</p>    <p style="text-align:center"><img src="https://simg.open-open.com/show/3c2e0e5404bad68225bb3bc8bbe87f8c.png"></p>    <p>读取速度对比:</p>    <p style="text-align:center"><img src="https://simg.open-open.com/show/136f2178d9ee00d53b1312f61115b480.png"></p>    <p>结论:</p>    <p>相比MySQL来说,InfluxDB在磁盘占用和数据读取方面很占优势,而且随着数据规模的扩大,查询速度没有明显的下降。</p>    <p>针对时序数据来说,InfluxDB有明显的优势。</p>    <p>好,就这些了,希望对你有帮助。</p>    <p> </p>    <p> </p>    <p>来自:http://www.cnblogs.com/MikeZhang/p/InfluxDBTest20170212.html</p>    <p> </p>