sqlserver开窗函数

2019-07-22 23:35栏目:网站首页

从SQL Server 贰零零陆起,SQL Server早先协理窗口函数 (Window Function),以及到SQL Server 2012,窗口函数功用巩固,近来截至支持以下两种窗口函数:

 

  1. 排序函数 (Ranking Function) ;

  2. 聚合函数 (Aggregate Function) ;

  3. 深入分析函数 (Analytic Function) ;

  4. NEXT VALUE FORAV4 Function, 那是给sequence专用的三个函数;

从 转

 

 

一. 排序函数(Ranking Function)

开窗函数是在 ISO 标准中定义的。SQL Server 提供排行开窗函数和聚集开窗函数。

协助文档里的代码示例很全。

  在开窗函数出现从前存在着无数用 SQL 语句很难消除的主题材料,很多都要通过复杂的相关子查询恐怕存款和储蓄进程来成功。SQL Server 二零零五 引进了开窗函数,使得那些精粹的难点能够被轻松的解决。

排序函数中,ROW_NUMBEENVISION()较为常用,可用于去重、分页、分组中选择数据,生成数字匡助表等等;

  窗口是用户内定的一组行。开窗函数总结从窗口派生的结果聚集各行的值。开窗函数分别使用于各样分区,并为每一个分区重新起动总括。

排序函数在语法上供给OVE奥德赛子句里必须含ORDER BY,不然语法不通过,对于不想排序的风貌能够那样变化;

  OVE陆风X8子句用于明确在行使关联的开窗函数从前,行集的分区和排序。PARTITION BY 将结果集分为五个分区。

drop table if exists test_ranking

create table test_ranking
( 
id int not null,
name varchar(20) not null,
value int not null
) 

insert test_ranking 
select 1,'name1',1 union all 
select 1,'name2',2 union all 
select 2,'name3',2 union all 
select 3,'name4',2

select id , name, ROW_NUMBER() over (PARTITION by id ORDER BY name) as num
from test_ranking

select id , name, ROW_NUMBER() over (PARTITION by id) as num
from test_ranking
/*
Msg 4112, Level 15, State 1, Line 1
The function 'ROW_NUMBER' must have an OVER clause with ORDER BY.
*/

--ORDERY BY后面给一个和原表无关的派生列
select id , name, ROW_NUMBER() over (PARTITION by id ORDER BY GETDATE()) as num
from test_ranking

select id , name, ROW_NUMBER() over (PARTITION by id ORDER BY (select 0)) as num
from test_ranking

 

 

一、排名开窗函数

二. 聚合函数 (Aggregate Function)

1. 语法

SQL Server 二零零六中,窗口聚合函数仅援助PARTITION BY,也便是说仅能对分组的数码全体做聚合运算;

Ranking Window Functions

< OVER_CLAUSE > :: =

   OVER ( [ PARTITION BY value_expression , ... [ n ] ]

          <ORDER BY_Clause> )

SQL Server 二〇一三始发,窗口聚合函数援救OOdysseyDER BY,以及ROWS/RAGNE选项,原来需求子查询来落成的供给,如: 移动平均 (moving averages), 总结聚合 (cumulative aggregates), 累计求和 (running totals) 等,变得更为惠及;

 

 

在意:O奇骏DE陆风X8 BY 子句钦定对相应 FROM 子句生成的行集实行分区所依附的列。value_expression 只好援用通过 FROM 子句可用的列。value_expression 不可能援用采取列表中的表明式或别名。value_expression 可以是列表明式、标量子查询、标量函数或用户定义的变量。

代码示例1:计算/小计/累计求和

 

drop table if exists test_aggregate;

create table test_aggregate
(
event_id      varchar(100),
rk            int,
price         int
)

insert into test_aggregate
values
('a',1,10),
('a',2,10),
('a',3,50),
('b',1,10),
('b',2,20),
('b',3,30)


--1. 没有窗口函数时,用子查询
select a.event_id, 
       a.rk,  --build ranking column if needed
       a.price, 
     (select sum(price) from test_aggregate b where b.event_id = a.event_id and b.rk <= a.rk) as totalprice 
  from test_aggregate a


--2. 从SQL Server 2012起,用窗口函数
--2.1 
--没有PARTITION BY, 没有ORDER BY,为全部总计;
--只有PARTITION BY, 没有ORDER BY,为分组小计;
--只有ORDER BY,没有PARTITION BY,为全部累计求和(RANGE选项,见2.2)
select *,
     sum(price) over() as TotalPrice,
     sum(price) over(partition by event_id) as SubTotalPrice,
       sum(price) over(order by rk) as RunningTotalPrice
  from test_aggregate a

--2.2 注意ORDER BY列的选择,可能会带来不同结果
select *,
     sum(price) over(partition by event_id order by rk) as totalprice 
  from test_aggregate a
/*
event_id    rk    price    totalprice
a    1    10    10
a    2    10    20
a    3    50    70
b    1    10    10
b    2    20    30
b    3    30    60
*/

select *,
     sum(price) over(partition by event_id order by price) as totalprice 
  from test_aggregate a
/*
event_id    rk    price    totalprice
a    1    10    20
a    2    10    20
a    3    50    70
b    1    10    10
b    2    20    30
b    3    30    60
*/

--因为ORDER BY还有个子选项ROWS/RANGE,不指定的情况下默认为RANGE UNBOUNDED PRECEDING AND CURRENT ROW 
--RANGE按照ORDER BY中的列值,将相同的值的行均视为当前同一行
select  *,sum(price) over(partition by event_id order by price) as totalprice from test_aggregate a
select  *,sum(price) over(partition by event_id order by price range between unbounded preceding and current row) as totalprice from test_aggregate a

--如果ORDER BY中的列值有重复值,手动改用ROWS选项即可实现逐行累计求和
select  *,sum(price) over(partition by event_id order by price rows between unbounded preceding and current row) as totalprice from test_aggregate a

2. 示例

 

  可参考 

代码示例2:移动平均

 

--移动平均,举个例子,就是求前N天的平均值,和股票市场的均线类似
drop table if exists test_moving_avg

create table test_moving_avg
(
ID    int, 
Value int,
DT    datetime
)

insert into test_moving_avg 
values
(1,10,GETDATE()-10),
(2,110,GETDATE()-9),
(3,100,GETDATE()-8),
(4,80,GETDATE()-7),
(5,60,GETDATE()-6),
(6,40,GETDATE()-5),
(7,30,GETDATE()-4),
(8,50,GETDATE()-3),
(9,20,GETDATE()-2),
(10,10,GETDATE()-1)

--1. 没有窗口函数时,用子查询
select *,
(select AVG(Value) from test_moving_avg a where a.DT >= DATEADD(DAY, -5, b.DT) AND a.DT < b.DT) AS avg_value_5days
from test_moving_avg b

--2. 从SQL Server 2012起,用窗口函数
--三个内置常量,第一行,最后一行,当前行:UNBOUNDED PRECEDING, UNBOUNDED FOLLOWING, CURRENT ROW 
--在行间移动,用BETWEEN m preceding AND n following (m, n > 0)
SELECT *,
       sum(value) over (ORDER BY DT ROWS BETWEEN 5 preceding AND CURRENT ROW) moving_sum,
       avg(value) over (ORDER BY DT ROWS BETWEEN 4 preceding AND CURRENT ROW) moving_avg1,
       avg(value) over (ORDER BY DT ROWS BETWEEN 5 preceding AND 1 preceding) moving_avg2,
       avg(value) over (ORDER BY DT ROWS BETWEEN 3 preceding AND 1 following) moving_avg3
FROM  test_moving_avg
ORDER BY DT

 

 

二、聚合开窗函数

三. 剖判函数 (Analytic Function)

1. 语法

代码示例1:取当前行某列的前一个/下多少个值

Aggregate Window Functions

< OVER_CLAUSE > :: =

   OVER ( [ PARTITION BY value_expression , ... [ n ] ] )

drop table if exists test_analytic

create table test_analytic
(
SalesYear         varchar(10),
Revenue           int,
Offset            int
)

insert into test_analytic
values
(2013,1001,1),
(2014,1002,1),
(2015,1003,1),
(2016,1004,1),
(2017,1005,1),
(2018,1006,1)

--当年及去年的销售额
select *,lag(Revenue,1,null) over(order by SalesYear asc) as PreviousYearRevenue from test_analytic
select *,lag(Revenue,Offset,null) over(order by SalesYear asc) as PreviousYearRevenue from test_analytic
select *,lead(Revenue,1,null) over(order by SalesYear desc) as PreviousYearRevenue from test_analytic

--当年及下一年的销售额
select *,lead(Revenue,1,null) over(order by SalesYear asc) as NextYearRevenue from test_analytic
select *,lead(Revenue,Offset,null) over(order by SalesYear asc) as NextYearRevenue from test_analytic
select *,lag(Revenue,1,null) over(order by SalesYear desc) as NextYearRevenue from test_analytic

--可以根据offset调整跨度

 

 

2. 示例

代码示例2:分组中某列最大/最小值,对应的别的列值

  下例将依附 SalesOrderID 举办分区,然后为各种分区分别计算SUM、AVG、COUNT、MIN、MAX。

假使有个门禁系统,在职员和工人每一遍进门时写入一条记下,记录了“身份号码”,“进门时间”,“衣裳颜色",查询各样职工最终二次进门时的“衣服颜色”。

SELECT SalesOrderID, ProductID, OrderQty

   ,SUM(OrderQty) OVER(PARTITION BY SalesOrderID) AS 'Total'

   ,AVG(OrderQty) OVER(PARTITION BY SalesOrderID) AS 'Avg'

   ,COUNT(OrderQty) OVER(PARTITION BY SalesOrderID) AS 'Count'

   ,MIN(OrderQty) OVER(PARTITION BY SalesOrderID) AS 'Min'

   ,MAX(OrderQty) OVER(PARTITION BY SalesOrderID) AS 'Max'

FROM SalesOrderDetail

WHERE SalesOrderID IN(43659,43664);

drop table if exists test_first_last

create table test_first_last
(
EmployeeID             int,
EnterTime              datetime,
ColorOfClothes         varchar(20)
)

insert into test_first_last
values
(1001, GETDATE()-9, 'GREEN'),
(1001, GETDATE()-8, 'RED'),
(1001, GETDATE()-7, 'YELLOW'),
(1001, GETDATE()-6, 'BLUE'),
(1002, GETDATE()-5, 'BLACK'),
(1002, GETDATE()-4, 'WHITE')

--1. 用子查询
--LastColorOfColthes
select * from test_first_last a
where not exists(select 1 from test_first_last b where a.EmployeeID = b.EmployeeID and a.EnterTime < b.EnterTime)

--LastColorOfColthes
select *
from 
(select *, ROW_NUMBER() over(partition by EmployeeID order by EnterTime DESC) num
from test_first_last ) t
where t.num =1


--2. 用窗口函数
--用LAST_VALUE时,必须加上ROWS/RANGE BETWEEN CURRENT ROW AND UNBOUNDED FOLLOWING,否则结果不正确
select *, 
       FIRST_VALUE(ColorOfClothes) OVER (PARTITION BY EmployeeID ORDER BY EnterTime DESC) as LastColorOfClothes,
       FIRST_VALUE(ColorOfClothes) OVER (PARTITION BY EmployeeID ORDER BY EnterTime ASC) as FirstColorOfClothes,
       LAST_VALUE(ColorOfClothes) OVER (PARTITION BY EmployeeID ORDER BY EnterTime ASC ROWS BETWEEN CURRENT ROW AND UNBOUNDED FOLLOWING) as LastColorOfClothes,
       LAST_VALUE(ColorOfClothes) OVER (PARTITION BY EmployeeID ORDER BY EnterTime DESC ROWS BETWEEN CURRENT ROW AND UNBOUNDED FOLLOWING) as FirstColorOfClothes
from test_first_last

--对于显示表中所有行,并追加Last/First字段时用窗口函数方便些
--对于挑选表中某一行/多行时,用子查询更方便

 

 

  下例首先由 SalesOrderID 分区进行联谊,并为种种 SalesOrderID 的每一行计算 ProductID 的比重)。

四. NEXT VALUE FOR Function

SELECT SalesOrderID, ProductID, OrderQty

   ,SUM(OrderQty) OVER(PARTITION BY SalesOrderID) AS 'Total'

   ,CAST(1.0 * OrderQty / SUM(OrderQty) OVER(PARTITION BY SalesOrderID)

       *100 AS DECIMAL(5,2))AS 'Percent by ProductID'

FROM SalesOrderDetail

WHERE SalesOrderID IN(43659,43664);

drop sequence if exists test_seq

create sequence test_seq
start with 1
increment by 1;

GO

drop table if exists test_next_value

create table test_next_value
(
ID         int,
Name       varchar(10)
)

insert into test_next_value(Name)
values
('AAA'),
('AAA'),
('BBB'),
('CCC')

--对于多行数据获取sequence的next value,是否使用窗口函数都会逐行计数
--窗口函数中ORDER BY用于控制不同列值的计数顺序
select *, NEXT VALUE FOR test_seq from test_next_value
select *, NEXT VALUE FOR test_seq OVER(ORDER BY Name DESC) from test_next_value

 

 

3. SQL Server 2013 增加效果

参考:

  SQL Server 2011 为聚合函数提供了窗口排序和框架帮衬,能够将 OVE冠道子句与函数一起行使,以便总计各类聚合值,比方移动平均值、累堆会集、运维总结或每组结果的前 N 个结实。

SELECT - OVER Clause (Transact-SQL)

  更加多详细情形,请参谋 

 

SQL Server Windowing Functions: ROWS vs. RANGE

 

三、深入分析开窗函数

  可参考 

 

 

四、NEXT VALUE FOR 函数

  通过将 OVEHaval 子句应用于 NEXT VALUE FOMurano 调用,NEXT VALUE FO福睿斯函数援救生成排序的连串值。 通过动用 OVE福特Explorer子句,能够向用户保障再次来到的值是安分守己 OVE昂科雷 子句的 OEvoqueDEKuga BY 子子句的依次生成的。

  例如:

SELECT NEXT VALUE FOR Test.CountBy1 OVER (ORDER BY LastName) AS ListNumber,

   FirstName, LastName

FROM Person.Contact ;

  实际情况请参谋 

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