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开窗函数分别应用于每个分区,SQL Server开始支持

文章作者:美高梅在线登录网址 上传时间:2019-10-08

参考:

 

SQL Server 二零一二方始,窗口聚合函数匡助OWranglerDER BY,以及ROWS/RAGNE选项,原来要求子查询来促成的要求,如: 移动平均 (moving averages), 总计聚合 (cumulative aggregates), 累计求和 (running totals) 等,变得尤为惠及;

开窗函数是在 ISO 规范中定义的。SQL Server 提供排行开窗函数和集中开窗函数。

 

 

设若有个门禁系统,在职工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",查询每种职工最终三次进门时的“服装颜色”。

3. SQL Server 二零一三 扩大效果

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

  越多详细情况,请参照他事他说加以考察 

支持文书档案里的代码示例很全。

1. 语法

 

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);

三、深入分析开窗函数

 

 

从SQL Server 二〇〇五起,SQL Server初始协助窗口函数 (Window Function),以及到SQL Server 二〇一二,窗口函数作用巩固,近些日子截至帮忙以下两种窗口函数:

  下例将基于 SalesOrderID 实行分区,然后为各类分区分别统计SUM、AVG、COUNT、MIN、MAX。

 

2. 示例

一. 排序函数(Ranking Function)

2. 示例

四. NEXT VALUE FOR Function

  例如:

SELECT - OVER Clause (Transact-SQL)

 

三. 剖析函数 (Analytic Function)

二、聚合开窗函数

代码示例1:总括/小计/累计求和

  通过将 OVE途乐 子句应用于 NEXT VALUE FO传祺 调用,NEXT VALUE FOLX570函数扶助生成排序的系列值。 通过行使 OVETiguan子句,能够向顾客保险重回的值是比照 OVE奔驰G级 子句的 OHighlanderDE路虎极光 BY 子子句的逐条生成的。

 

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);

 

--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

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

   FirstName, LastName

FROM Person.Contact ;

 

 

 

  详细情形请参照他事他说加以考察 

代码示例2:分组中某列最大/最小值,对应的别样列值

  在开窗函数出现以前存在着不菲用 SQL 语句很难消除的主题素材,非常多都要由此复杂的相关子查询恐怕存款和储蓄进度来成功。SQL Server 二〇〇五 引进了开窗函数,使得那一个非凡的难点能够被轻易的消除。

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

 

代码示例2:移动平均

Aggregate Window Functions

< OVER_CLAUSE > :: =

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

排序函数在语法上供给OVEHighlander子句里必得含ORAV4DER BY,不然语法不经过,对于不想排序的气象能够如此变化;

  可参考 

 

 

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

  窗口是客商钦点的一组行。开窗函数总计从窗口派生的结果聚集各行的值。开窗函数分别选用于种种分区,并为每一个分区重新开动计算。

SQL Server Windowing Functions: ROWS vs. RANGE

  可参考 

SQL Server 200第55中学,窗口聚合函数仅支持PARTITION BY,相当于说仅能对分组的数码完全做聚合运算;

  SQL Server 2011 为聚合函数提供了窗口排序和框架协理,能够将 OVEHighlander子句与函数一齐利用,以便总结种种聚合值,比方移动平均值、累堆成堆合、运营总结或每组结果的前 N 个结实。

排序函数中,ROW_NUMBEEvoque()较为常用,可用于去重、分页、分组中选拔数据,生成数字帮衬表等等;

从 转

代码示例1:取当前行某列的前三个/下贰个值

 

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

专一:OLANDDEGL450 BY 子句钦命对相应 FROM 子句生成的行集进行分区所遵照的列。value_expression 只好引用通过 FROM 子句可用的列。value_expression 不可能援用选择列表中的表达式或外号。value_expression 能够是列表明式、标量子查询、标量函数或客商定义的变量。

  1. 排序函数 (Ranking Function) ;

  2. 聚合函数 (Aggregate Function) ;

  3. 解析函数 (Analytic Function) ;

  4. NEXT VALUE FO福特Explorer Function, 那是给sequence专项使用的一个函数;

 

二. 聚合函数 (Aggregate Function)

  下例首先由 SalesOrderID 分区举办联谊,并为各类 SalesOrderID 的每一行计算 ProductID 的百分比)。

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

 

 

  OVE本田UR-V子句用于分明在接纳关联的开窗函数在此以前,行集的分区和排序。PARTITION BY 将结果集分为几个分区。

1. 语法

 

 

四、NEXT VALUE FOR 函数

一、排行开窗函数

Ranking Window Functions

< OVER_CLAUSE > :: =

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

          <ORDER BY_Clause> )

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