场景,如果出现慢SQL,需要DBA加索引优化,怎么知道加的索引是有效的呢?这需要一遍遍的试验和调整,总不能直接拿线上的数据库测试吧,一般方法是在测试环境建立测试表,然后从线上的从库拷贝一些数据进测试环境,接着再进行加索引和explain


但有时候,导出的数据量少,执行计划看不出效果,导出数据量多,又会冲刷线上机器的buffer pool和影响IO,如果有个工具能够直接生成数据就好了,生成跟线上一样的100万,或者1000万就好了


以前sysbench压力测试,有一个生成数据的功能,生成100万数据是这样的


sysbench --test=oltp --mysql-table-engine=myisam --oltp-table-size=1000000 \
--mysql-socket=/tmp/mysql.sock --mysql-user=test --mysql-host=localhost \
--mysql-password=test prepare


但它生成表结构是固定的,进行压力测试的SQL语句也是固定的,无法调试线上的SQL语句


CREATE TABLE `sbtest` (
 `id` int(10) unsigned NOT NULL auto_increment,
 `k` int(10) unsigned NOT NULL default '0',
 `c` char(120) NOT NULL default '',
 `pad` char(60) NOT NULL default '',
 PRIMARY KEY (`id`),
 KEY `k` (`k`));


能否有一个创建用户自定义的表结构,并且对这个表结构生成上百千万数据的工具呢?有一个叫datagen的工具,链接在文章末尾


drwxr-xr-x. 2 root mysql     4096 Sep 27  2016 bizsql
drwxr-xr-x. 2 root mysql     4096 May 31 20:51 conf
-rw-r--r--. 1 root mysql 23698092 Sep 27  2016 datagen.jar
-rwxr-xr-x. 1 root mysql      147 Sep 27  2016 datagen.sh
-rw-rw-r--. 1 root mysql    31599 May 31 20:54 envbuilder.log
-rw-r--r--. 1 root mysql     1741 May 31 20:53 example.schema
-rw-r--r--. 1 root mysql     1336 May 31 09:42 example.schema_backup
-rw-r--r--. 1 root mysql     2062 Sep 27  2016 readme


方法很简单的2步,把你想要的表结构和想要生成多少条数据,写入到example.schema文件,比如这样,如果想要生成100万条数据,在表末尾加入注释/*{RC{1000000}}*/


CREATE TABLE `test`.`tbl_test` (
`post_id` BIGINT(20) DEFAULT '0'  ,
`star` INTEGER(10) DEFAULT '0'  ,
`view_count` INTEGER(11) DEFAULT '0'  ,
`bean` INTEGER(11) DEFAULT '0'  ,
`nearby` INTEGER(11) DEFAULT '0'  ,
PRIMARY KEY (post_id) ,
INDEX (poster_uid)
) COLLATE='utf8mb4_general_ci' ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 /*{RC{1000000}}*/;

第2步,填写连接测试数据库的账号密码,只需要加入一行




<property name="obURL" value="jdbc:mysql://数据IP:数据库端口/数据库名字?user=用户名&password=密码"/>


vi conf/datagen.xml 
<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
        xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
        xsi:schemaLocation="http://www.springframework.org/schema/beans
        classpath:org/springframework/beans/factory/xml/spring-beans-2.5.xsd">    
        <bean id="datagen" class="com.alipay.obmeter.tools.DataGen">
           <property name="obURL" value="jdbc:mysql://数据IP:数据库端口/数据库名字?user=用户名&password=密码"/>
                 
           <property name="inputDDL" value="example.schema"/>
           <property name="rowCountPerTable" value="1000000"/>
           <property name="maxThreadCountPerTable" value="20"/>
           <property name="maxThreadCount" value="20"/>
           <property name="dropTableFirst" value="true"/>
           <property name="needFreeze" value="false"/>
           <property name="staticRatio" value="1.0"/>
        </bean>
</beans>



接着运行shell脚本,往测试库建表,插入数据

[root@localhost datagen]# /bin/bash datagen.sh



[2017-05-31 08:53:15][WARN ] [DataGen :184] - Parsing ddl...
[2017-05-31 08:53:15][WARN ] [DataGen :187] - Creating table...
[2017-05-31 08:53:15][WARN ] [MultiThreadPrepareDataComparator:508] - Preparing generators...
[2017-05-31 08:53:15][WARN ] [MultiThreadPrepareDataComparator:510] - Generating dynamic data...
[2017-05-31 08:54:34][WARN ] [MultiThreadPrepareDataComparator:526] - Generate done.


在测试库,就会出现100万条数据了


mysql> select count(*) from test.tbl_test;
+----------+
| count(*) |
+----------+
|  1000000 |
+----------+
1 row in set (0.16 sec)


现在就可以加索引,explain线上真实的SQL语句了



mysql> explain select post_id  from test.tbl_test where post_type <> 1 and check_status = 9 and flag = 1 and post_time < 1496178301 order by post_time asc limit 200; \G
+----+-------------+----------+-------+---------------+-----------+---------+------+--------+-------------+
| id | select_type | table    | type  | possible_keys | key       | key_len | ref  | rows   | Extra       |
+----+-------------+----------+-------+---------------+-----------+---------+------+--------+-------------+
|  1 | SIMPLE      | tbl_test | range | post_time     | post_time | 9       | NULL | 501491 | Using where |
+----+-------------+----------+-------+---------------+-----------+---------+------+--------+-------------+
1 row in set (0.00 sec)
ERROR: 
No query specified



加索引


mysql>  alter table test.tbl_test add index idx_f(check_status,flag,post_type,post_time);           
Query OK, 0 rows affected (4.45 sec)
Records: 0  Duplicates: 0  Warnings: 0


再来一次explain,扫描50万行变2行



mysql> explain select post_id  from test.tbl_test where post_type <> 1 and check_status = 9 and flag = 1 and post_time < 1496178301 order by post_time asc limit 200; \G
+----+-------------+----------+-------+-----------------+-------+---------+------+------+------------------------------------------+
| id | select_type | table    | type  | possible_keys   | key   | key_len | ref  | rows | Extra                                    |
+----+-------------+----------+-------+-----------------+-------+---------+------+------+------------------------------------------+
|  1 | SIMPLE      | tbl_test | range | post_time,idx_f | idx_f | 15      | NULL |    2 | Using where; Using index; Using filesort |
+----+-------------+----------+-------+-----------------+-------+---------+------+------+------------------------------------------+
1 row in set (0.00 sec)


等调试好索引以后,确定能优化SQL以后,再往线上环境去加索引




当然还有一些很强大的功能

比如某个字段,只出现规定的几个值,比如状态status字段0,1,2,以及每个状态出现的概率

比如模拟线上的用户UID,可以限制某个字段随机数的范围,从00000001到899999999之间等

具体可以查看readme的介绍


百度链接: https://pan.baidu.com/s/1pKGQLkB 密码: 6t4u


转载于:https://blog.51cto.com/dadaman/1931186