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;