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 / s1000万条数据
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 / s3000万条数据
[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 / s1000万条数据
[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 / s3000万条数据
[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：
最终磁盘占用情况对比：
写入速度对比：
读取速度对比：
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和MySQL的读写对比测试.md
欢迎补充
