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InfluxDB读写性能测试

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。

操作系统: CentOS6.5_x64

InfluxDB版本 : v1.1.0

MySQL版本:v5.1.73

CPU : Intel(R) Core(TM) i5-2320 CPU @ 3.00GHz

内存 :12G

硬盘 :SSD 

一、MySQL读写测试

测试准备

初始化SQL语句:

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;

单写测试代码(insertTest1.c):


#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

可根据情况调整测试代码中的N参数。

单读测试代码(queryTest1.c):


#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

Makefile文件:

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    

测试数据记录

磁盘空间占用查询:

使用du方式(新数据库,仅为测试):

du -sh /var/lib/mysql

查询特定表:

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';

测试结果:

  • 100万条数据

    [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
    

    原始数据 : 28.6M

    du方式 : 279MB

    sql查询方式: 57.59MB

    写入速度: 12398 / s

    读取速度: 37174 / s

  • 1000万条数据
    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
    

    原始数据 : 286M

    du方式 : 2.4G

    sql查询方式: 572MB

    写入速度: 22988 / s

    读取速度: 1516 / s

  • 3000万条数据
    [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
    

    原始数据 : 858M

    du方式 : 7.1G

    sql查询方式: 1714MB

    写入速度: 24228 / s

    读取速度: 2261 / s

二、InfluxDB读写测试

测试准备

需要将InfluxDB的源码放入 go/src/github.com/influxdata 目录

单写测试代码(write1.go):


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

单读测试代码(query1.go):


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

测试结果记录

查看整体磁盘空间占用:

du -sh /var/lib/influxdb/

查看最终磁盘空间占用:

du -sh /var/lib/influxdb/data/testInfluxdb 
  • 100万条数据
    [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
    

    原始数据 : 28.6M

    整体磁盘占用:27M

    最终磁盘占用:21M

    写入速度: 68521 / s

    读取速度: 45045 / s

  • 1000万条数据

    [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
    

    原始数据 : 286M

    整体磁盘占用:214M

    最终磁盘占用:189M 写入速度: 70165 / s

    读取速度: 45249 / s

  • 3000万条数据
    [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
    

    原始数据 : 858M

    整体磁盘占用:623M

    最终磁盘占用:602M

    写入速度: 68318 / s

    读取速度: 42918 / s

三、测试结果分析

整体磁盘占用情况对比:

InfluxDB读写性能测试

最终磁盘占用情况对比:

InfluxDB读写性能测试

写入速度对比:

InfluxDB读写性能测试

读取速度对比:

InfluxDB读写性能测试

结论:

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。

针对时序数据来说,InfluxDB有明显的优势。

好,就这些了,希望对你有帮助。

本文github地址:

https://github.com/mike-zhang/mikeBlogEssays/blob/master/2017/ 20170212_InfluxDB读写性能测试.md

欢迎补充

原文  http://www.cnblogs.com/MikeZhang/p/InfluxDBTest20170212.html
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