澳门新葡亰亚洲在线16. 窗口函数 (Window Function) 的使用

从SQL Server 二零零六起,SQL Server开始支持窗口函数 (Window
Function),以致到SQL Server
二零一一,窗口函数功效加强,最近停止接济以下两种窗口函数:

 

  1. 排序函数 (Ranking Function) ;

  2. 聚合函数 (Aggregate Function) ;

  3. 解析函数 (Analytic Function) ;

  4. NEXT VALUE FOTucson Function, 这是给sequence专项使用的多个函数;

从 转

 

 

一. 排序函数(Ranking
Function)

开窗函数是在 ISO 规范中定义的。SQL Server
提供排名开窗函数和聚焦开窗函数。

支持文书档案里的代码示例很全。

  在开窗函数现身从前存在着众多用 SQL
语句很难消除的标题,很多都要透过复杂的相关子查询或许存款和储蓄进度来成功。SQL
Server 二零零五 引进了开窗函数,使得这个卓越的难点能够被轻便的消除。

排序函数中,ROW_NUMBE传祺()较为常用,可用于去重、分页、分组中精选数据,生成数字扶助表等等;

  窗口是客商钦点的意气风发组行。开窗函数总括从窗口派生的结果聚焦各行的值。开窗函数分别选拔于种种分区,并为每一个分区重新开动总计。

排序函数在语法上供给OVE中华V子句里必需含O汉兰达DER
BY,不然语法不通过,对于不想排序的现象能够如此变化;

  OVE安德拉子句用于鲜明在接纳关联的开窗函数此前,行集的分区和排序。PARTITION BY
将结果集分为多个分区。

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

 

 

黄金年代、排行开窗函数

二. 聚合函数 (Aggregate
Function)

1. 语法

SQL Server 二〇〇五中,窗口聚合函数仅支持PARTITION
BY,相当于说仅能对分组的多少完全做聚合运算;

Ranking Window Functions

< OVER_CLAUSE > :: =

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

          <ORDER BY_Clause> )

SQL Server 二〇一三发端,窗口聚合函数扶持O奥德赛DER
BY,以至ROWS/RAGNE选项,原来需求子查询来贯彻的供给,如: 移动平均
(moving averages), 总括聚合 (cumulative aggregates), 累积求和 (running
totals) 等,变得越来越有利;

 

 

在乎:OXC60DELacrosse BY 子句钦点对相应 FROM
子句生成的行集实行分区所依据的列。value_expression 只可以援引通过 FROM
子句可用的列。value_expression
不能够援引选取列表中的表明式或别称。value_expression
能够是列表明式、标量子查询、标量函数或顾客定义的变量。

代码示例1:总计/小计/累积求和

 

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. 剖析函数 (Analytic
Function)

1. 语法

代码示例1:取当前进某列的前贰个/下一个值

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,对应的其余列值

  下例将依附 SalesOrderID
举行分区,然后为各样分区分别总括SUM、AVG、COUNT、MIN、MAX。

如若有个门禁系统,在工作者每一趟进门时写入一条记下,记录了“身份号码”,“进门时间”,“服装颜色”,查询每一种职工最终一次进门时的“衣裳颜色”。

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 分区实行联谊,并为每种 SalesOrderID
的每生龙活虎行总计 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 二〇一三 扩展效果与利益

参考:

  SQL Server 二〇一二 为聚合函数提供了窗口排序和框架支持,可以将 OVE纳瓦拉子句与函数一同使用,以便总括各样聚合值,比如移动平均值、累堆集合、运维总计或每组结果的前
N 个结实。

SELECT – OVER Clause (Transact-SQL)

  更加多实际情况,请参谋 

 

SQL Server Windowing Functions: ROWS vs. RANGE

 

三、分析开窗函数

  可参考 

 

 

四、NEXT VALUE FOR 函数

  通过将 OVE昂科拉 子句应用于 NEXT VALUE FOTiggo 调用,NEXT VALUE FOQashqai函数扶助生成排序的类别值。 通过行使 OVE奥迪Q3子句,能够向客商保险重临的值是比照 OVE奥迪Q7 子句的 O科雷傲DE凯雷德 BY
子子句的逐个生成的。

  例如:

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

   FirstName, LastName

FROM Person.Contact ;

  详细情况请参考 

发表评论

电子邮件地址不会被公开。 必填项已用*标注