hive之窗口函数

窗口函数

1.相关函数说明

COVER():指定分析函数工作的数据窗口大小,这个数据窗口大小可能会随着行的变而变化

CURRENT ROW:当前行

n PRECEDING:往前n行数据

n FOLLOWING:往后n行数据

UNBOUNDED:起点,UNBOUNDED PRECEDING 表示从前面的起点, UNBOUNDED FOLLOWING表示到后面的终点

LAG(col,n):往前第n行数据

LEAD(col,n):往后第n行数据

 

NTILE(n):把有序分区中的行分发到指定数据的组中,各个组有编号,编号从1开始,对于每一行,NTILE返回此行所属的组的编号。注意:n必须为int类型。

2.数据准备:name,orderdate,cost

jack,2017-01-01,10

tony,2017-01-02,15

jack,2017-02-03,23

tony,2017-01-04,29

jack,2017-01-05,46

jack,2017-04-06,42

tony,2017-01-07,50

jack,2017-01-08,55

mart,2017-04-08,62

mart,2017-04-09,68

neil,2017-05-10,12

mart,2017-04-11,75

neil,2017-06-12,80

mart,2017-04-13,94

 

3.需求

(1)查询在2017年4月份购买过的顾客及总人数

(2)查询顾客的购买明细及月购买总额

(3)上述的场景,要将cost按照日期进行累加

(4)查询顾客上次的购买时间

(5)查询前20%时间的订单信息

4.创建本地business.txt,导入数据

[atguigu@hadoop102 datas]$ vi business.txt

5.创建hive表并导入数据

create table business(

name string,

orderdate string,

cost int

) ROW FORMAT DELIMITED FIELDS TERMINATED BY ',';

 

load data local inpath "/opt/module/datas/business.txt" into table business;

6.按需求查询数据

(1)查询在2017年4月份购买过的顾客及总人数

select name,count(*) over ()

from business 

where substring(orderdate,1,7) = '2017-04'

group by name;

(2)查询顾客的购买明细及月购买总额

select name,orderdate,cost,sum(cost) over(partition by month(orderdate)) from

 business;

(3)上述的场景,要将cost按照日期进行累加

select name,orderdate,cost,

sum(cost) over() as sample1,--所有行相加

sum(cost) over(partition by name) as sample2,--按name分组,组内数据相加

sum(cost) over(partition by name order by orderdate) as sample3,--按name分组,组内数据累加

sum(cost) over(partition by name order by orderdate rows between UNBOUNDED PRECEDING and current row ) as sample4 ,--和sample3一样,由起点到当前行的聚合

sum(cost) over(partition by name order by orderdate rows between 1 PRECEDING and current row) as sample5, --当前行和前面一行做聚合

sum(cost) over(partition by name order by orderdate rows between 1 PRECEDING AND 1 FOLLOWING ) as sample6,--当前行和前边一行及后面一行

sum(cost) over(partition by name order by orderdate rows between current row and UNBOUNDED FOLLOWING ) as sample7 --当前行及后面所有行

from business;

(4)查看顾客上次的购买时间

select name,orderdate,cost,

lag(orderdate,1,'1900-01-01') over(partition by name order by orderdate ) as time1, lag(orderdate,2) over (partition by name order by orderdate) as time2

from business;

(5)查询前20%时间的订单信息

select * from (

    select name,orderdate,cost, ntile(5) over(order by orderdate) sorted

    from business

) t

where sorted = 1;

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