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小学生之Oracle分析函数,sqlserver开窗函数必发88手机客户端

从SQL Server 2006起,SQL Server开首援救窗口函数 (Window
Function),以及到SQL Server
二零一三,窗口函数功效巩固,目前甘休协助以下两种窗口函数:

 

深入分析函数是如何?
分析函数是Oracle特地用来缓慢解决复杂报表总括须要的作用强大的函数,它能够在数码中进行分组然后总计基于组的某种计算值,而且每一组的每一行都足以回到一个总括值。

  1. 排序函数 (Ranking Function) ;

  2. 聚合函数 (Aggregate Function) ;

  3. 浅析函数 (Analytic Function) ;

  4. NEXT VALUE FO卡宴 Function, 那是给sequence专项使用的三个函数;

从 转

          

 

 

深入分析函数和聚合函数的区别之处是何等?
习感觉常的聚合函数用group by分组,每一个分组重返多个总结值,而深入分析函数采纳partition
by分组,並且每组每行都得以回来二个总结值。

一. 排序函数(Ranking
Function)

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

              

援助文书档案里的代码示例很全。

  在开窗函数现身之前存在着众多用 SQL
语句很难解决的标题,比比较多都要通过复杂的相关子查询大概存款和储蓄进程来达成。SQL
Server 二〇〇五 引进了开窗函数,使得这一个特出的难题能够被轻便的缓和。

浅析函数的花样
解析函数带有一个开窗函数over(),包括三个分析子句:分组(partition by),
排序(order by), 窗口(rows) ,他们的施用方式如下:over(partition by xxx
order by yyy rows between zzz)。
注:窗口子句在此地自个儿只说rows方式的窗口,range情势和滑动窗口也不提

排序函数中,ROW_NUMBE福睿斯()较为常用,可用于去重、分页、分组中选择数据,生成数字协理表等等;

  窗口是用户内定的一组行。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每种分区,并为每一种分区重新启航总括。

    

排序函数在语法上供给OVE奥迪Q5子句里必须含O路虎极光DER
BY,不然语法不经过,对于不想排序的情景可以这么变化;

  OVE中华V子句用于分明在采用关联的开窗函数在此以前,行集的分区和排序。PARTITION BY
将结果集分为多少个分区。

分析函数例子(在scott用户下模拟)

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

 

示范目标:展现各单位职员和工人的薪金,并顺便突显该有的的最高级程序猿资。

 

一、排行开窗函数

 

二. 聚合函数 (Aggregate
Function)

1. 语法

--显示各部门员工的工资,并附带显示该部分的最高工资。
SELECT E.DEPTNO,
       E.EMPNO,
       E.ENAME,
       E.SAL,
       LAST_VALUE(E.SAL) 
       OVER(PARTITION BY E.DEPTNO 
            ORDER BY E.SAL ROWS 
            --unbounded preceding and unbouned following针对当前所有记录的前一条、后一条记录,也就是表中的所有记录
            --unbounded:不受控制的,无限的
            --preceding:在...之前
            --following:在...之后
            BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING) MAX_SAL
  FROM EMP E;

SQL Server 二零零七中,窗口聚合函数仅协助PARTITION
BY,也便是说仅能对分组的多少总体做聚合运算;

Ranking Window Functions

< OVER_CLAUSE > :: =

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

          <ORDER BY_Clause> )

 

SQL Server 二零一一起来,窗口聚合函数援救OEscortDER
BY,以及ROWS/RAGNE选项,原本要求子查询来贯彻的要求,如: 移动平均
(moving averages), 总结聚合 (cumulative aggregates), 累计求和 (running
totals) 等,变得尤为有利;

 

运维结果:

 

只顾:O昂科威DETucson BY 子句钦定对相应 FROM
子句生成的行集举行分区所依据的列。value_expression 只可以引用通过 FROM
子句可用的列。value_expression
不可能援引采用列表中的表明式或别名。value_expression
能够是列表达式、标量子查询、标量函数或用户定义的变量。

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代码示例1:总计/小计/累计求和

 

示范目标:依据deptno分组,然后总括每组值的总和

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 

SELECT EMPNO,
       ENAME,
       DEPTNO,
       SAL,
       SUM(SAL) OVER(PARTITION BY DEPTNO ORDER BY ENAME) max_sal
  FROM SCOTT.EMP;

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

 

 运转结果:

 

二、聚合开窗函数

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三. 浅析函数 (Analytic
Function)

1. 语法

身体力行指标:对各部门拓展分组,并顺便显示第一行至当前行的汇聚

代码示例1:取当前行某列的前叁个/下二个值

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

 

SELECT EMPNO,
       ENAME,
       DEPTNO,
       SAL,
       --注意ROWS BETWEEN unbounded preceding AND current row  是指第一行至当前行的汇总
       SUM(SAL) OVER(PARTITION BY DEPTNO 
                     ORDER BY ENAME 
                     ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) max_sal
  FROM SCOTT.EMP;

 

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

  下例将基于 SalesOrderID
进行分区,然后为各样分区分别计算SUM、AVG、COUNT、MIN、MAX。

 运营结果:

一旦有个门禁系统,在员工每回进门时写入一条记下,记录了“身份号码”,“进门时间”,“服装颜色”,查询每种职工最终二回进门时的“服装颜色”。

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);

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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

 

身体力行目标:当前行至最终一行的集中

 

  下例首先由 SalesOrderID 分区实行联谊,并为各个 SalesOrderID
的每一行总计 ProductID 的比重)。

SELECT EMPNO,
       ENAME,
       DEPTNO,
       SAL,
       --注意ROWS BETWEEN current row AND unbounded following 指当前行到最后一行的汇总
       SUM(SAL) OVER(PARTITION BY DEPTNO 
                     ORDER BY ENAME 
                     ROWS BETWEEN CURRENT ROW AND UNBOUNDED FOLLOWING) max_sal
  FROM SCOTT.EMP;

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);

 运维结果:

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

 

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3. SQL Server 二零一三 增添效果与利益

 示例指标:当前行的上一行(rownum-1)到当前行的汇聚

参考:

  SQL Server 2013 为聚合函数提供了窗口排序和框架接济,能够将 OVEEvoque子句与函数一齐利用,以便总括种种聚合值,举个例子移动平均值、累聚成堆结、运维计算或每组结果的前
N 个结果。

 

SELECT – OVER Clause (Transact-SQL)

  越多详细的情况,请参照他事他说加以考察 

SELECT EMPNO,
       ENAME,
       DEPTNO,
       SAL,
       --注意ROWS BETWEEN 1 preceding AND current row 是指当前行的上一行(rownum-1)到当前行的汇总 
       SUM(SAL) OVER(PARTITION BY DEPTNO 
                     ORDER BY ENAME ROWS 
                     BETWEEN 1 PRECEDING AND CURRENT ROW) max_sal
  FROM SCOTT.EMP;

 

 

SQL Server Windowing Functions: ROWS vs. RANGE

 

运营结果:

三、分析开窗函数

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  可参考 

示范指标:   当前行的上一行(rownum-1)到当前行的下辆行(rownum+2)的集中

 

 

 

SELECT EMPNO,
       ENAME,
       DEPTNO,
       SAL,
       --注意ROWS BETWEEN 1 preceding AND 1 following 是指当前行的上一行(rownum-1)到当前行的下辆行(rownum+2)的汇总
       SUM(SAL) OVER(PARTITION BY DEPTNO 
                     ORDER BY ENAME 
                     ROWS BETWEEN 1 PRECEDING AND 2 FOLLOWING) max_sal
  FROM SCOTT.EMP;

四、NEXT VALUE FOR 函数

 

  通过将 OVEHaval 子句应用于 NEXT VALUE FOWrangler 调用,NEXT VALUE FOTucson函数协理生成排序的体系值。 通过选取 OVEENCORE子句,能够向用户保证重回的值是依照 OVELX570 子句的 O途观DE奥迪Q7 BY
子子句的顺序生成的。

运作结果:

  例如:

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

   FirstName, LastName

FROM Person.Contact ;

评级函数

广大评级函数如下:

  • RANK():再次回到数据项在分组中的排行,在排行相等时会在排名中留给空位,形成排行不总是。
  • DENSE_RANK():一样重返数据项在分组中排名,然则在排名相等时不会留下名位空位。
  • CUME_DIST():重返特定值相对于一组值的岗位,是储存布满(cumulative
    distribution)的简写。
  • PERCENT_RANK():再次回到有些值相对于一组值的比例排名。
  • NTILE():重返n分片后的值,如五分片、陆分片等。
  • ROW_NUMBEPRADO():为每一条分组记录再次回到一个数字,注意分歧于rownum伪列。

  实际情况请参照他事他说加以考察 

RANK()和DENSE_RANK()

rank()和dense_rank()函数都可用于总结数据项在分组中(在不选择partition
by时以具有数据为叁个分组)的排行。它们的分别在于rank()在排行相等时,如:有3个第1名时,则下三个排行的榜单为第4名,未有2、3名;而dense_rank()则在有3个第1名时,下贰个排名字为第2名。即,rank()会产出排行间隔,而dense_rank()则不会冒出排行间隔。

那四个函数多用来select子句中,在不开始展览分组的景况下,能够不采纳partition
by子句。其行使比方如,找寻公司享有人报酬排行:

select ename,

rank() over (order by sal desc) rank,

dense_rank() over (order by sal desc) dense_rank

from emp;

从言语中能够看看,rank()函数必要有至关心重视要字over和order
by。并且rank()是三个单值函数,而不是聚合函数。若要求寻觅每一种工作的最高级技术员资在享有职业最高级技术员资中的排行:

select job,

rank() over (order by max(sal) desc) rank,

dense_rank() over (order by max(sal) desc) dense_rank

from emp

group by job;

在排行中,会冒出NULL值在前在后的标题,能够在OLX570DER
BY子句之后选择主要字NULLS FIPAJEROST/LAST来支配。

PARTITION BY子句

当供给开始展览拿到分组后各组内的排行,则须要采纳partition
by子句。它不相同于group
by的分组,这种分组不“合併聚合”,它一定于把值分组后总结,然后再一次每个值。

最常见的例子如:在table表中有name(姓名)、class(班级)和score(分数)四个字段,求每一种班级里前三名姓名、班级及分数,SQL语句为:

select name,class,score

from (select name,

class,

score,

rank() over(partition by class order by score desc) rank

from table)

where rank <= 3;

在SCOTT用户中测验,求各种部门报酬前3名的人姓名、部门、工作和薪给,如:

select *

from (select ename,

deptno,

job,

sal,

dense_rank() over(partition by deptno order by sal desc) rank

from emp)

where rank <= 3;

ROW_NUMBER()

row_number为每一行再次回到一个数字,在分组中较常用(rownum在非分组中常用)。如,给emp表中各样职业工资由高到低举行排序:

select ename,job,sal,row_number() over (partition by job order by sal
desc) from emp;

窗口函数(累计和、移动平均值等)

窗口函数可用来计量累计和、移动平均值和着力平均值等,具体如下:

计量累计和

查询从贰零零肆年三月到三月的一同销量,SQL语句如下:

SELECT month,

SUM(amount) AS month_amount,

SUM(SUM(amount)) OVER (ORDER BY month ROWS BETWEEN UNBOUNDED PRECEDING
AND CURRENT ROW) AS cumulative_amount

FROM all_sales

where year = 2003

GROUP BY month

ORDER BY month;

对此累计部分SUM(SUM(amount)) OVETiguan (O奇骏DER BY month ROWS BETWEEN UNBOUNDED
PRECEDING AND CU宝马X3RENT ROW)解析如下:

  • SUM(SUM(amount))中内部的SUM(amount)用于总括月销量总和,外界的SUM()用于总括累计划发卖量。
  • O奥德赛DELacrosse BY month 按月度对查询读取的笔录举行排序。
  • ROWS BETWEEN UNBOUNDED PRECEDING AND CUTucsonRENT
    ROW定义了窗口的源点和顶峰,源点为UNBOUNDED
    PRECEDING,意味着起源为稳固的询问结果集的率先行;终点为CUENCORERENT
    ROW表示终点为处理结果集的当下行。当外界SUM函数总括重回当前的一起销量后,窗口的终极便向下活动一行。PRECEDING表示发展累计数,若将UNBOUNDED换到数字如1,则象征跟此前一条记下做积攒;同期还是能向后,使用主要字FOLLOWING,钦命向后积攒数只须求在该重大字前加数字就可以,该数字为向后积存的行数(从此处也能够看来排序的首要)。

如:

若要总结钦赐月份如五月到6月的积累销量,则只供给在where子句中再追加条件month
between 6 and 12就能够。

测算上个月左近半年积存销量,窗口语句:

SUM(SUM(amount)) OVER (ORDER BY month ROWS BETWEEN 3 PRECEDING AND
CURRENT ROW) AS cumulative_amount

算算前段时期和后叁个月积存销量,窗口语句:

SUM(SUM(amount)) OVER (ORDER BY month ROWS BETWEEN 1 PRECEDING AND 1
FOLLOWING) AS cumulative_amount

计量移动平均值

计量前些日子与前6个月以国内出卖量的活动平均值,SQL语句如下:

SELECT month,

SUM(amount) AS month_amount,

AVG(SUM(amount)) OVER (ORDER BY month ROWS BETWEEN 3 PRECEDING AND
CURRENT ROW) AS moving_average

FROM all_sales

where year = 2003

GROUP BY month

ORDER BY month;

对活动平均值部分AVG(SUM(amount)) OVE奥迪Q5 (O奥迪Q5DEWrangler BY month ROWS BETWEEN 3
PRECEDING AND CU智跑RENT ROW)深入分析如下:

  • AVG(SUM(amount))内部的sum(amount)总计月销量和,外界的avg()计算平均值。
  • O传祺DE奥迪Q5 BY month
    按月度对查询读取的笔录举行排序(那是必须的,因为独有排序后工夫做积存或左右求平均值)。
  • ROWS BETWEEN 3 PRECEDING AND CUPAJERORENT
    ROW定义了窗口的起源为近年来记下的前3条记下,窗口的极限为当前记下。

测算大旨平均值

测算当前月份前、后各一个月的销量移动平均值,SQL语句如下:

SELECT month,

SUM(amount) AS month_amount,

AVG(SUM(amount)) OVER (ORDER BY month ROWS BETWEEN 1 PRECEDING AND 1
FOLLOWING) AS moving_average

FROM all_sales

where year = 2003

GROUP BY month

ORDER BY month;

对宗旨平均值部分AVG(SUM(amount)) OVE奥迪Q3 (OWranglerDE本田CR-V BY month ROWS BETWEEN 1
PRECEDING AND 1 FOLLOWING)剖判如下:

  • AVG(SUM(amount))内部的sum(amount)计算月销量和,外界的avg()总括平均值。
  • O讴歌MDXDE揽胜极光 BY month
    按月度对查询读取的笔录实行排序(这是必须的,因为唯有排序后工夫做积攒或左右求平均值)。
  • ROWS BETWEEN 1 PRECEDING AND 1
    FOLLOWING定义了窗口的起源是时下记录此前的那条记下,窗口的顶峰是如今记录之后的那条记下。

窗口第一条和结尾一条记下

FIRST_VALUE()和LAST_VALUE()函数可用来获取窗口中的第一行和最终一行数据,如,可用于获取当前月前些日子和后一个月的销量:

SELECT month,

SUM(amount) AS month_amount,

FIRST_VALUE(SUM(amount)) OVER (ORDER BY month ROWS BETWEEN 1 PRECEDING
AND 1 FOLLOWING) AS pre_month_amount,

LAST_VALUE(SUM(amount)) OVER (ORDER BY month ROWS BETWEEN 1 PRECEDING
AND 1 FOLLOWING) AS next_month_amount

FROM all_sales

where year = 2003

GROUP BY month

ORDER BY month;

里头,窗口定义了起源为前段时间终点为后八个月,故而first_value(sum(amount))为前段日子销量而last_value()为后四个月销量。