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SQL优化–inner、left join替换in、not in、except

SQL优化–inner、left join替换in、not in、except

 

新系统上线,用户基数16万,各种查询timeout。打开砂锅问到底,直接看sql语句吧,都是泪呀,一大堆in\not in\except。这里总结一下,怎么替换掉in\not in\except。

1. in/except->left join

查询目的

根据

  • 客户表(Customer,按照站点、册本划分,16万数据)
  • 水表表(Meter,16万数据)
  • 水表抄表数据表(Meter_Data,远传表每天更新,27万数据)

关联查询,查询某天某个册本下水表未上传抄表数据的用户。

原查询结构

select * 
from Customer cs
where 
cs.Group_No = '册本编号' and
cs.Customer_No in 
(
    select Customer_No 
    from  Customer cs
    left join Meter me on cs.Customer_No = me.Customer_No
    where cs.Group_No = '册本编号'
    except
    select Customer_No
    from Customer cs
    left join Meter me on cs.Customer_No = me.Customer_No
    inner join Meter_data md on me.meter_no = md.meter_no and md.date = '2019-04-09'
    where cs.Group_NO='册本编号'
)

原查询思路

  1. 查询出目标册本已上传数据的用户编号
select Customer_No
from Customer cs
left join Meter me on cs.Customer_No = me.Customer_No
inner join Meter_data md on me.meter_no = md.meter_no and md.date = '2019-04-09'
where cs.Group_NO='册本编号'
  1. 查询出目标册本全部用户编号
select Customer_No 
from  Customer cs
left join Meter me on cs.Customer_No = me.Customer_No
where cs.Group_No = '册本编号'
  1. 全部用户编号中排除已上传数据的用户编号,即为未上传数据的用户编号
全部用户编号 except 已抄表的用户编号
  1. 查询出在未抄表用户编号集合中的用户信息。
select * 
from Customer cs
where 
cs.Group_No = '册本编号' and
cs.Customer_No in 
(全部用户编号 except 已抄表的用户编号)

思路倒是没有问题,但是in+except查询效率不要太慢了,本来想测试个时间,结果执行了几分钟愣是没出结果,直接终止掉了

优化查询结构

其实in\not in\except这些语法在查询中使用,效率不高是公认的事实,但是可能是由于语义比较明显吧,很多人还是喜欢这样用。我们这里使用left join来替代in+except。这里就来改掉上面的查询:

select cs.*
from Customer cs
left join Meter me on cs.Customer_No = me.Customer_No
left join Meter_data md on me.meter_no = md.meter_no and md.date = '2019-04-09'
where cs.Group_NO='册本编号' and md.meter_no is null;

优化查询思路

  1. 用left join代替in+except,通过left join获取目标册本下全部用户的信息,并与当天上传的抄表数据进行连接;
  2. 连接中,右表为空即抄表数据为空的,即为当前未上传数据的客户信息;

left join on expression where expression 执行时,首先确保左表数据全部返回,然后应用on后指定的条件。因此,on的条件如果是对左表数据的过滤,是无效的;对右表数据的过滤是有效的。对左表数据的过滤条件,需要放到where条件中。

2. not in->left join

上面in+except的写法,可以使用not in简化一下,但是一样效率不高。这里想要说明的是not in也可以很方便的使用left join替换。

not in结构

select * 
from Customer cs
where 
cs.Group_No = '册本编号' and
cs.Customer_No not in 
(
    select Customer_No
    from Customer cs
    left join Meter me on cs.Customer_No = me.Customer_No
    inner join Meter_data md on me.meter_no = md.meter_no and md.date = '2019-04-09'
    where cs.Group_NO='册本编号'
)

left join结构

select cs.*
from Customer cs
left join Meter me on cs.Customer_No = me.Customer_No
left join Meter_data md on me.meter_no = md.meter_no and md.date = '2019-04-09'
where cs.Group_NO='册本编号' and md.meter_no is null;

3. in->inner join

查询目的

还是上面的查询背景,这里查询某天某个册本已经上传抄表数据的用户信息。

in结构

select * 
from Customer cs
where 
cs.Group_No = '册本编号' and
cs.Customer_No in 
(
    select Customer_No
    from Customer cs
    left join Meter me on cs.Customer_No = me.Customer_No
    inner join Meter_data md on me.meter_no = md.meter_no and md.date = '2019-04-09'
    where cs.Group_NO='册本编号'
)

这里使用in不够高效,但是我们使用left join是否可以呢?

left join结构

select cs.*
from Customer cs
left join Meter me on cs.Customer_No = me.Customer_No
left join Meter_data md on me.meter_no = md.meter_no and md.date = '2019-04-09'
where cs.Group_NO='册本编号' and md.meter_no is not null;

left join结构的话,这里需要使用is not null作为筛选条件。但是is not null同样非常低效。因此我们使用inner join

inner join结构

select cs.*
from Customer cs
left join Meter me on cs.Customer_No = me.Customer_No
inner join Meter_data md on me.meter_no = md.meter_no and md.date = '2019-04-09'
where cs.Group_NO='册本编号';

inner join通过连接操作,直接获取到已上传抄表数据的用户信息。

4. not in -> in -> inner join

前面的查询场景中,我们默认的条件是未上传抄表数据的用户,当天在meter_data表是没有记录的。现在假设我们每天凌晨初始化meter_data表,设置抄表数值默认为零,抄表数据上传默认为state=0未上传。上传后,更新抄表数值和抄表状态state=1。

这时,我们来优化上面的not in查询结构还有另外一种思路。

not in结构

select * 
from Customer cs
where 
cs.Group_No = '册本编号' and
cs.Customer_No not in 
(
    select Customer_No
    from Customer cs
    left join Meter me on cs.Customer_No = me.Customer_No
    inner join Meter_data md on me.meter_no = md.meter_no and md.date = '2019-04-09'
    where cs.Group_NO='册本编号' and meter.state=1
)

in结构

通过筛选条件取反,变换not in->in

select * 
from Customer cs
where 
cs.Group_No = '册本编号' and
cs.Customer_No in 
(
    select Customer_No
    from Customer cs
    left join Meter me on cs.Customer_No = me.Customer_No
    inner join Meter_data md on me.meter_no = md.meter_no and md.date = '2019-04-09'
    where cs.Group_NO='册本编号' and meter.state=0
)

inner join结构

select cs.*
from Customer cs
left join Meter me on cs.Customer_No = me.Customer_No
inner join Meter_data md on me.meter_no = md.meter_no and md.date = '2019-04-09'
where cs.Group_NO='册本编号' and meter.state=0;

5. 总结如下

上面的查询结构拆分出来后,大家可能觉得这么简单的sql怎么可能写成这个沙雕。其实真实业务系统,还有关联其他将近10张表。这里想说的是,在in\not in\except这种查询结构时,如果涉及到的数据量较大,建议坚决用连接替换。

  • … in (all except sub)… 查询结构可以转换为->left join
  • … not in … 查询结构可以转换为->left join
  • … not in … 查询也可以转换为 in -> inner join,这里需要确认转换查询条件时,是否有对应的数据
  • … in 查询结构可以转换为->inner join

原文地址https://www.cnblogs.com/zhangdk/p/notintoleftjoin.html

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