HiveSQL——row_number() over() 使用


語法格式:row_number() over(partition by 分組列 order by 排序列 desc)

row_number() over()分組排序功能:

在使用 row_number() over()函數時候,over()里頭的分組以及排序的執行晚於 where 、group by、  order by 的執行。

例一:

表數據:

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:對查詢結果進行排序(無分組)

select id,name,age,salary,row_number()over(order by salary desc) rn
from TEST_ROW_NUMBER_OVER t


結果:

 

進一步排序:根據id分組排序

select id,name,age,salary,row_number()over(partition by id order by salary desc) rank
from TEST_ROW_NUMBER_OVER t


結果:

 

 再一次排序:找出每一組中序號為一的數據

 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


結果:

 

排序找出年齡在13歲到16歲數據,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'


結果:結果中 rank 的序號,其實就表明了 over(order by salary desc) 是在where age between and 后執行的

 

例二:

1.使用row_number()函數進行編號,如

select email,customerID, ROW_NUMBER() over(order by psd) as rows from QT_Customer
原理:先按psd進行排序,排序完后,給每條數據進行編號。

2.在訂單中按價格的升序進行排序,並給每條記錄進行排序代碼如下:

select DID,customerID,totalPrice,ROW_NUMBER() over(order by totalPrice) as rows from OP_Order
3.統計出每一個各戶的所有訂單並按每一個客戶下的訂單的金額 升序排序,同時給每一個客戶的訂單進行編號。這樣就知道每個客戶下幾單了:

select ROW_NUMBER() over(partition by customerID order by totalPrice)
as rows,customerID,totalPrice, DID from OP_Order
4.統計每一個客戶最近下的訂單是第幾次下的訂單:

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 '下單次數',customerID from tabs
group by customerID
5.統計每一個客戶所有的訂單中購買的金額最小,而且並統計改訂單中,客戶是第幾次購買的:

思路:利用臨時表來執行這一操作。

1.先按客戶進行分組,然后按客戶的下單的時間進行排序,並進行編號。

2.然后利用子查詢查找出每一個客戶購買時的最小價格。

3.根據查找出每一個客戶的最小價格來查找相應的記錄。

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.篩選出客戶第一次下的訂單。

思路。利用rows=1來查詢客戶第一次下的訂單記錄。

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等開窗函數時,over里頭的分組及排序的執行晚於“where,group by,order by”的執行。

select
ROW_NUMBER() over(partition by customerID order by insDT) as rows,
customerID,totalPrice, DID
from OP_Order where insDT>'2011-07-22'
 

原文鏈接:https://blog.csdn.net/qq_25221835/article/details/82762416


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