ROW_NUMBER() OVER()函数用法详解 （分组排序 例子多）[亲测有效]

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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);

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：找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：

排序找出年龄在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。

    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'