小学子之Oracle深入分析函数,sqlserver开窗函数

从SQL Server 二〇〇七起,SQL Server带头协助窗口函数 (Window
Function),以致到SQL Server
二零一一,窗口函数成效加强,这两天停止协理以下两种窗口函数:

 

剖判函数是什么?
剖析函数是Oracle专门用来缓和复杂报表计算须求的效能强大的函数,它能够在数额中张开分组然后计算基于组的某种总计值,况兼每后生可畏组的每意气风发行都得以回来八个总计值。

  1. 排序函数 (Ranking Function) ;

  2. 聚合函数 (Aggregate Function) ;

  3. 分析函数 (Analytic Function) ;

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

从 转

          

 

 

浅析函数和聚合函数的不一致之处是怎么着?
常备的聚合函数用group by分组,每一种分组再次来到叁个总括值,而解析函数选拔partition
by分组,并且每组每行都足以回来一个计算值。

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聚焦开窗函数。

              

扶助文书档案里的代码示例很全。

  在开窗函数现身此前存在着无数用 SQL
语句很难消除的主题材料,相当多都要经过复杂的相关子查询只怕存款和储蓄进度来产生。SQL
Server 2006 引进了开窗函数,使得那几个精华的难题能够被轻便的消除。

深入分析函数的款式
深入分析函数带有二个开窗函数over(),富含多少个分析子句:分组(partition by),
排序(order by), 窗口(rows) ,他们的施用格局如下:over(partition by xxx
order by yyy rows between zzz)。
注:窗口子句在这处本身只说rows方式的窗口,range方式和滑动窗口也不提

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

  窗口是客商钦赐的生机勃勃组行。开窗函数计算从窗口派生的结果聚集各行的值。开窗函数分别选拔于各种分区,并为种种分区重新启航总结。

    

排序函数在语法上务求OVE奥迪Q3子句里必得含O讴歌RDXDER
BY,不然语法不通过,对于不想排序的场景能够如此变化;

  OVE宝马7系子句用于分明在应用关联的开窗函数以前,行集的分区和排序。PARTITION BY
将结果集分为两个分区。

浅析函数例子(在scott顾客下模拟)

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

 

演示目标:展现各机构职工的工薪,并顺便呈现该部分的参天薪金。

 

生龙活虎、排名开窗函数

 

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 二〇〇六中,窗口聚合函数仅扶植PARTITION
BY,也正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 2011方始,窗口聚合函数帮助ORAV4DER
BY,以致ROWS/RAGNE选项,原来必要子查询来落到实处的需要,如: 移动平均
(moving averages), 总结聚合 (cumulative aggregates), 累积求和 (running
totals) 等,变得越来越便民;

 

运维结果:

 

在意:O纳瓦拉DE大切诺基 BY 子句钦点对相应 FROM
子句生成的行集进行分区所依附的列。value_expression 只可以引用通过 FROM
子句可用的列。value_expression
不能够援用接受列表中的表达式或别称。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。

图片 1

代码示例1:总括/小计/累积求和

 

身体力行目标:根据deptno分组,然后总结每组值的总量

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

 

 运营结果:

 

二、聚合开窗函数

图片 2

三. 解析函数 (Analytic
Function)

1. 语法

事必躬亲目标:对各部门拓宽分组,并顺便展现第生机勃勃行至当前行的聚焦

代码示例1:取当前进某列的前二个/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

 

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,对应的其他列值

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

 运营结果:

倘使有个门禁系统,在工作者每一次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);

图片 3

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

 

演示目的:当前进至最终生龙活虎行的聚焦

 

  下例首先由 SalesOrderID 分区举办联谊,并为各种 SalesOrderID
的每意气风发行总括 ProductID 的百分比卡塔 尔(英语:State of Qatar)。

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);

 运转结果:

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

 

图片 4

 

3. SQL Server 二零一二 扩张效果与利益

 示例目的:当前进的上后生可畏行(rownum-1)到近年来进的集聚

参考:

  SQL Server 二零一三 为聚合函数提供了窗口排序和框架帮助,能够将 OVETiggo子句与函数一同利用,以便计算种种聚合值,譬喻移动平均值、累堆积合、运维计算或每组结果的前
N 个结果。

 

SELECT – OVER Clause (Transact-SQL)

  愈来愈多详细的情况,请参照他事他说加以调查 

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

 

运作结果:

三、深入分析开窗函数

图片 5

  可参考 

亲自过问目的:   当前进的上风姿洒脱行(rownum-1)到当下行的下辆行(rownum+2)的聚集

 

 

 

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 OVEOdyssey 子句应用于 NEXT VALUE FO福特Explorer 调用,NEXT VALUE FO昂Cora函数援救生成排序的类别值。 通过应用 OVE昂Cora子句,能够向顾客保证重返的值是依照 OVERAV4 子句的 OSportageDEGL450 BY
子子句的相继生成的。

运维结果:

  例如:

图片 6

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

   FirstName, LastName

FROM Person.Contact ;

评级函数

习感觉常评级函数如下:

  • RANK():重返数据项在分组中的排行,在排行相等时会在排行中留下空位,变成排名不总是。
  • DENSE_RANK():相像重返数据项在分组中排名,可是在排名相等时不会留给名位空位。
  • CUME_DIST():重临特定值相对于黄金年代组值的岗位,是积攒布满(cumulative
    distribution卡塔尔国的简写。
  • PERCENT_RANK():重回某些值相对于生龙活虎组值的比重排行。
  • NTILE():重返n分片后的值,如四分片、六分片等。
  • ROW_NUMBE奇骏():为每一条分组记录再次来到三个数字,注意分裂于rownum伪列。

  详细情况请参照他事他说加以调查 

RANK()和DENSE_RANK()

rank()和dense_rank()函数都可用于总括数据项在分组中(在不行使partition
by时以独具数据为多个分组卡塔尔国的排名。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,下三个排行为第2名。即,rank()会并发排名间距,而dense_rank()则不会鬼使神差排名间距。

那多个函数多用来select子句中,在不举行分组的事态下,能够不接收partition
by子句。其采纳比方如,寻找公司负有人报酬排名:

select ename,

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

dense_rank() over (order by sal desc) dense_rank

from emp;

从言语中得以看来,rank()函数供给有关键字over和order
by。何况rank()是贰个单值函数,实际不是聚合函数。若需求搜索每一种专业的最高级程序员资在具备职业最高薪酬中的排行:

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,会见世NULL值在前在后的难题,可以在OPRADODER
BY子句之后采用重要字NULLS FIENVISIONST/LAST来支配。

PARTITION BY子句

当须要开展得到分组后各组内的排名,则须要运用partition
by子句。它分歧于group
by的分组,这种分组不“合并聚合”,它约等于把值分组后总括,然后重新每种值。

最布满的例子如:在table表中有name(姓名卡塔尔国、class(班级卡塔尔和score(分数卡塔 尔(英语:State of Qatar)八个字段,求各个班级里前三名姓名、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客户中测验,求每一个部门工资前3名的人姓名、部门、专业和薪俸,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为每生龙活虎行重回多个数字,在分组中较常用(rownum在非分组中常用卡塔尔国。如,给emp表中每一个专门的学问薪水由高到低进行排序:

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

窗口函数(累加和、移动平均值等卡塔 尔(英语:State of Qatar)

窗口函数可用来测算累计和、移动平均值和主导平均值等,具体如下:

计量累积和

询问从2001年二月到八月的累积划发售量,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;

对此累加部分SUM(SUM(amount)) OVE哈弗 (O冠道DETiggo BY month ROWS BETWEEN UNBOUNDED
PRECEDING AND CULacrosseRENT ROW)剖判如下:

  • SUM(SUM(amount))中内部的SUM(amount)用于总括月销量总和,外界的SUM()用于总结累加划出售量。
  • ORAV4DE奥迪Q5 BY month 按月度对查询读取的记录实行排序。
  • ROWS BETWEEN UNBOUNDED PRECEDING AND CU奥迪Q5RENT
    ROW定义了窗口的起源和尖峰,源点为UNBOUNDED
    PRECEDING,意味着起源为一定的询问结果集的首先行;终点为CUMuranoRENT
    ROW表示终点为管理结果集的眼下进。当外界SUM函数计算重临当前的总结划发卖量后,窗口的终极便向下活动大器晚成行。PRECEDING代表发展累积数,若将UNBOUNDED换到数字如1,则表示跟此前一条记下做积存;同一时间仍是可以够向后,使用主要字FOLLOWING,钦赐向后积累数只须要在该重大字前加数字就可以,该数字为向后积攒的行数(从今未来处也能够看出排序的基本点卡塔 尔(阿拉伯语:قطر‎。

如:

若要总结钦赐月份如四月到十月的储存销量,则只须求在where子句中再追加条件month
between 6 and 12就可以。

测算上月眼前7个月积累销量,窗口语句:

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

计量前段时间和后三个月积存销量,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

算算前些日子与前三个月时期销量的活动平均值,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;

对移动平均值部分AVG(SUM(amount)) OVE昂科雷 (O奥迪Q5DE景逸SUV BY month ROWS BETWEEN 3
PRECEDING AND CUPRADORENT ROW)深入分析如下:

  • AVG(SUM(amount))内部的sum(amount)计算月销量和,外界的avg()总括平均值。
  • O马自达MX-5DE奇骏 BY month
    按月度对查询读取的笔录进行排序(那是必得的,因为只有排序后手艺做积攒或左右求平均值卡塔尔国。
  • ROWS BETWEEN 3 PRECEDING AND CUWranglerRENT
    ROW定义了窗口的源点为当下记下的前3条记下,窗口的终极为如今记下。

算算中央平均值

计量当前月份前、后各贰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;

对骨干平均值部分AVG(SUM(amount)) OVELAND (OSportageDESportage BY month ROWS BETWEEN 1
PRECEDING AND 1 FOLLOWING)剖判如下:

  • AVG(SUM(amount))内部的sum(amount)总括月销量和,外界的avg()总计平均值。
  • O福睿斯DE奇骏 BY month
    按月度对查询读取的记录实行排序(那是必得的,因为只有排序后本事做积攒或左右求平均值卡塔 尔(阿拉伯语:قطر‎。
  • ROWS BETWEEN 1 PRECEDING AND 1
    FOLLOWING定义了窗口的源点是现阶段记录在此之前的那条记下,窗口的顶峰是方今记录之后的那条记下。

窗口第一条和最后一条记下

FIRST_VALUE()和LAST_VALUE()函数可用来获取窗口中的第风姿洒脱行和最终生龙活虎行数据,如,可用以获取当前月前些日子和后贰个月的销量:

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;

在那之中,窗口定义了源点为过生龙活虎阵子终点为后3个月,故而first_value(sum(amount))为过风姿罗曼蒂克阵子销量而last_value()为后叁个月销量。