ROW_NUMBER（）OVER（）函数⽤法详解（分组排序例⼦
多）
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：
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);
group by的用法及原理详解
⼀次排序：对查询结果进⾏排序（⽆分组）
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
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：出每⼀组中序号为⼀的数据
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：
排序出年龄在13岁到16岁数据，按salary排序
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
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：
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：
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：
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.然后利⽤⼦查询查出每⼀个客户购买时的最⼩价格。
3.根据查出每⼀个客户的最⼩价格来查相应的记录。
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。
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。
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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