SQL语句优化记录

今天药忘吃喽~ 2022-01-22 05:23 345阅读 0赞

维护的系统中有一个统计功能特别慢，需要计算十几分钟，今天分析后发现有一个sql语句执行了近4秒，特意针对SQL进行了优化，记下优化记录。

**主要分为两步：**

**1.优化sql语句**

**2.建索引**

大的sql语句就不贴了，找出其中最慢的一段

select 
    	a1.pid,a1.kfqnum ,a1.kfqdj,qsj,jsj,case when (jsj-qsj)/qsj > 1 then 100 ELSE (jsj-qsj)/qsj*100 end as jzssj 
    from
    (
    	select aa.* from zd_kfq aa,(select * from zd_kfq where Kfqnum = 21) bb WHERE aa.Kfqdj = bb.kfqdj and aa.hg=bb.hg
    ) zz LEFT JOIN
    (
    	select a.pid pid, kfqnum ,kfqdj,a.sz qsj
    	from evaluation_index a
    	where 1=1
    	and a.pid in(
    		select growth_id from evaluation_sub WHERE pid = 'ae80c82c-4172-46f4-895f-29e1e9e7fd3c'
    	)
    	and a.nian=2018-1
    	and a.kfqdj=1
    ) a1 on zz.Kfqnum = a1.kfqnum LEFT JOIN (
    	select a.pid pid, kfqnum ,kfqdj,a.sz jsj
    	from evaluation_index a
    	where 1=1
    	and a.pid in(
    		select growth_id from evaluation_sub WHERE pid = 'ae80c82c-4172-46f4-895f-29e1e9e7fd3c'
    	)
    	and a.nian=2018
    	and a.kfqdj=1
    ) b1 on a1.pid=b1.pid and a1.kfqnum=b1.kfqnum and a1.kfqdj = b1.kfqdj

查询结果如下图，可以看到查询时间是3.5秒左右：

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2Rhb2Nhb3Jlbjkyd3E_size_16_color_FFFFFF_t_70][]

通过explain命令查看一下执行过程：

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2Rhb2Nhb3Jlbjkyd3E_size_16_color_FFFFFF_t_70 1][]

首先去掉语句嵌套，并且将left join替换为join

select this.pid,kfq.kfqnum,kfq.kfqdj,this.sz jsj,last.sz qsj ,case when (this.sz-last.sz)/last.sz > 1 then 100 ELSE (this.sz-last.sz)/last.sz*100 end as jzssj
    from zd_kfq target 
    join zd_kfq kfq ON kfq.Kfqdj = target.kfqdj and kfq.hg=target.hg 
    join evaluation_index this ON kfq.kfqnum = this.kfqnum  -- and kfq.kfqdj = this.kfqdj
    join evaluation_sub sub ON this.pid = sub.growth_id
    join evaluation_index last on last.pid = sub.growth_id and this.pid=last.pid and kfq.kfqnum=last.kfqnum -- and kfq.kfqdj = last.kfqdj
    where target.kfqnum = 21
    AND this.nian = 2018 AND this.kfqdj = target.kfqdj
    AND last.nian = 2018-1 AND last.kfqdj = target.kfqdj
    AND sub.pid = 'ae80c82c-4172-46f4-895f-29e1e9e7fd3c'

执行时间缩短为0.36秒左右，快了10倍 ，结果少了几条值为null的

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2Rhb2Nhb3Jlbjkyd3E_size_16_color_FFFFFF_t_70 2][]

再通过explain命令查看一下执行过程：

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2Rhb2Nhb3Jlbjkyd3E_size_16_color_FFFFFF_t_70 3][]

针对上面表中this/last，也就是evaluation\_index表创建索引，这个在查询中扫描了36321行

CREATE INDEX stat_kfq ON evaluation_index (pid,nian,kfqnum,kfqdj) USING BTREE;

执行时间缩短为0.05秒左右

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2Rhb2Nhb3Jlbjkyd3E_size_16_color_FFFFFF_t_70 4][]

查看执行过程

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2Rhb2Nhb3Jlbjkyd3E_size_16_color_FFFFFF_t_70 5][]

可以看到现在除了kfq和sub两个表都已经使用了索引，这两个表数据量比较少，加上索引基本没什么影响

### 总结 ###

1.先优化sql语句

在保证结果正确的前提下减少使用left join和嵌套查询，能够减少sql执行步骤数量

2.创建索引

针对数据量比较大的表建立联合索引，建立索引遵循**最左前缀匹配原则**

（1）比如针对一个表A、B、C三个字段建立联合索引，当查询条件为A、AB、ABC、AC都可以使用到索引

（2）如果这个表字段包含除了ABC之外的其他字段D，并且D上面没有被其他索引覆盖，那么查询条件为B、或者C的时候就不会使用索引，explain语句的时候type=all

（3）如果这个表字段只有ABC三个字段，或者还包含是主键的D，则查询条件为B或者C时，也会使用到索引，explain语句的时候type=index

**不同type的性能： null > system/const > eq\_ref > ref > ref\_or\_null  >index\_merge >  range > index >  all**

**参考：**

[https://www.cnblogs.com/wangfengming/articles/8275448.html][https_www.cnblogs.com_wangfengming_articles_8275448.html]

[https://www.jb51.net/article/142840.htm][https_www.jb51.net_article_142840.htm]

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[https_www.cnblogs.com_wangfengming_articles_8275448.html]: https://www.cnblogs.com/wangfengming/articles/8275448.html
[https_www.jb51.net_article_142840.htm]: https://www.jb51.net/article/142840.htm