语法格式:row_number() over(partition by 分组列 order by 排序列 desc)
row_number() over()分组排序功能:
在使用 row_number() over()函数时候,over()里头的分组以及排序的执行晚于 where 、group by、 order by 的执行。
例一:
表数据:
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create table test_row_number_over( id varchar (10) not null , name varchar (10) null , age varchar (10) null , salary int null ); select * from test_row_number_over t; insert into test_row_number_over(id, name ,age,salary) values (1, 'a' ,10,8000); insert into test_row_number_over(id, name ,age,salary) values (1, 'a2' ,11,6500); insert into test_row_number_over(id, name ,age,salary) values (2, 'b' ,12,13000); insert into test_row_number_over(id, name ,age,salary) values (2, 'b2' ,13,4500); insert into test_row_number_over(id, name ,age,salary) values (3, 'c' ,14,3000); insert into test_row_number_over(id, name ,age,salary) values (3, 'c2' ,15,20000); insert into test_row_number_over(id, name ,age,salary) values (4, 'd' ,16,30000); insert into test_row_number_over(id, name ,age,salary) values (5, 'd2' ,17,1800); |
一次排序:对查询结果进行排序(无分组)
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select id, name ,age,salary,row_number()over( order by salary desc ) rn from test_row_number_over t |
结果:
进一步排序:根据id分组排序
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select id, name ,age,salary,row_number()over(partition by id order by salary desc ) rank from test_row_number_over t |
结果:
再一次排序:找出每一组中序号为一的数据
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select * from ( select id, name ,age,salary,row_number()over(partition by id order by salary desc ) rank from test_row_number_over t) where rank <2 |
结果:
排序找出年龄在13岁到16岁数据,按salary排序
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select id, name ,age,salary,row_number()over( order by salary desc ) rank from test_row_number_over t where age between '13' and '16' |
结果:结果中 rank 的序号,其实就表明了 over(order by salary desc) 是在where age between and 后执行的
例二:
1.使用row_number()函数进行编号,如
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select email,customerid, row_number() over( order by psd) as rows from qt_customer |
原理:先按psd进行排序,排序完后,给每条数据进行编号。
2.在订单中按价格的升序进行排序,并给每条记录进行排序代码如下:
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select did,customerid,totalprice,row_number() over( order by totalprice) as rows from op_order |
3.统计出每一个各户的所有订单并按每一个客户下的订单的金额 升序排序,同时给每一个客户的订单进行编号。这样就知道每个客户下几单了:
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select row_number() over(partition by customerid order by totalprice) as rows ,customerid,totalprice, did from op_order |
4.统计每一个客户最近下的订单是第几次下的订单:
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with tabs as ( select row_number() over(partition by customerid order by totalprice) as rows ,customerid,totalprice, did from op_order ) select max ( rows ) as '下单次数' ,customerid from tabs group by customerid |
5.统计每一个客户所有的订单中购买的金额最小,而且并统计改订单中,客户是第几次购买的:
思路:利用临时表来执行这一操作。
1.先按客户进行分组,然后按客户的下单的时间进行排序,并进行编号。
2.然后利用子查询查找出每一个客户购买时的最小价格。
3.根据查找出每一个客户的最小价格来查找相应的记录。
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with tabs as ( select row_number() over(partition by customerid order by insdt) as rows ,customerid,totalprice, did from op_order ) select * from tabs where totalprice in ( select min (totalprice) from tabs group by customerid ) |
6.筛选出客户第一次下的订单。
思路。利用rows=1来查询客户第一次下的订单记录。
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with tabs as ( select row_number() over(partition by customerid order by insdt) as rows ,* from op_order ) select * from tabs where rows = 1 select * from op_order |
7.注意:在使用over等开窗函数时,over里头的分组及排序的执行晚于“where,group by,order by”的执行。
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select row_number() over(partition by customerid order by insdt) as rows , customerid,totalprice, did from op_order where insdt> '2011-07-22' |
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原文链接:https://blog.csdn.net/qq_25221835/article/details/82762416