SQL优化——避免使用Not IN

对于有一定数据量的表，使用 IN 和Not IN往往效率很低

• 在项目中遇到这样一个问题：

原来表中有7000多条数据，日常查询、跑应用都很流畅，而当数据量增加到3w条左右时，运行速度慢到无法忍受。
经过简单排查，将问题定位在了一条使用 Not IN 进行查询的sql语句上：

SELECT * FROM tb_case WHERE SYMBOL!= 9 AND 
CASENO NOT IN 
(SELECT CASENO FROM tb_carout WHERE STATUS=25 AND SYMBOL!=9)

把这条语句拎出来单独执行，足足跑了一分多钟。。

该语句之所以效率低下，很大一部分原因是Not IN不走索引。

• 解决办法很简单——避免使用Not IN

1.使用Not Exists

SELECT COUNT(*) FROM tb_case a WHERE SYMBOL!= 9 and 
NOT exists 
(SELECT CASENO FROM tb_carout b WHERE a.caseno=b.caseno and STATUS=25 AND SYMBOL!=9)

2.使用Left Join

SELECT * FROM tb_case a 
left join tb_carout b on a.caseno=b.caseno and b.STATUS=25 and b.SYMBOL!=9 
where b.caseno is null and a.symbol!=9 

提升效果很明显，执行时间不足0.1s

• IN和Exists的区别

简单来说，前者是非相关子查询，子查询先执行，且只执行一次，执行完毕后将值传递给外层查询；后者是相关子查询，将外层查询的一个元组传递给内层查询，然后执行内层查询，外层查询根据返回的结果集得到满足条件的记录，重复这个过程直到外层查询的所有元组都处理完毕。
从这个过程来看，非相关子查询比相关子查询效率高。
详细过程参考SQL相关子查询与非相关子查询

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最后记录下多个表Left Join的写法

SELECT TB_CASE.CASENO AS CASENO,TB_CASE.LAWGROUP AS LAWGROUP,S1.ROLE_NAME AS LGNAME,TB_CASE.CARPARK AS CARPARK,
S2.ROLE_NAME AS CARPARKNAME,TB_CASE.LAWTIME AS LAWTIME,TB_CASE.CARTYPE AS CARTYPE,TB_CASE.CARNO AS CARNO,
TB_CASE.STATUS AS STATUS,TB_CASE.IS_CLONE AS IS_CLONE,TB_CASE.BCFS AS BCFS 
FROM 
TB_CASE,SYS_ROLE S1, SYS_ROLE S2 
WHERE 
((NOT(TB_CASE.CASENO IN (SELECT TB_CAROUT.CASENO FROM TB_CAROUT WHERE ((TB_CAROUT.STATUS = '25') AND (TB_CAROUT.SYMBOL <> 9))))) 
AND (TB_CASE.LAWGROUP = S1.ROLE_ID) AND (TB_CASE.CARPARK = S2.ROLE_ID))
;

Left Join写法：

SELECT T1.CASENO AS CASENO,T1.LAWGROUP AS LAWGROUP,S1.ROLE_NAME AS LGNAME,T1.CARPARK AS CARPARK,S2.ROLE_NAME AS CARPARKNAME,
T1.LAWTIME AS LAWTIME,T1.CARTYPE AS CARTYPE,T1.CARNO AS CARNO,T1.STATUS AS STATUS,T1.IS_CLONE AS IS_CLONE,
T1.BCFS AS BCFS FROM TB_CASE T1
left join TB_CAROUT T2 on T1.CASENO=T2.CASENO  and T2.STATUS='25' AND T2.SYMBOL!=9
left join SYS_ROLE S1 ON T1.LAWGROUP=S1.ROLE_ID 
left join SYS_ROLE S2 ON T1.CARPARK=S2.ROLE_ID 
where  T2.CASENO IS NULL;