本篇主要介绍了大数据开发基础：Hive的开窗函数，通过具体的内容展示，希望对大数据开发Hive的学习有一定的帮助。

Hive的开窗函数

一、窗口函数 ROW_NUMBER,RANK,DENSE_RANK

1、数据准备

cookie1,2021-06-10,1

cookie1,2021-06-11,5

cookie1,2021-06-12,7

cookie1,2021-06-13,3

cookie1,2021-06-14,2

cookie1,2021-06-15,4

cookie1,2021-06-16,4

cookie2,2021-06-10,2

cookie2,2021-06-11,3

cookie2,2021-06-12,5

cookie2,2021-06-13,6

cookie2,2021-06-14,3

cookie2,2021-06-15,9

cookie2,2021-06-16,7

CREATE TABLE it_t1 (

cookieid string,

createtime string,   --day

pv INT

) ROW FORMAT DELIMITED FIELDS TERMINATED BY ',';

-- 加载数据：

load data local inpath '/export/data/hivedatas/it_t2.txt' into table it_t1;

2、ROW_NUMBER

ROW_NUMBER()  从1开始，按照顺序，生成分组内记录的序列

SELECT 

  cookieid,

  createtime,

  pv,

  ROW_NUMBER() OVER(PARTITION BY cookieid ORDER BY pv desc) AS rn

  FROM it_t1;

3、RANK 和 DENSE_RANK

RANK() 生成数据项在分组中的排名，排名相等会在名次中留下空位

DENSE_RANK() 生成数据项在分组中的排名，排名相等会在名次中不会留下空位

SELECT 

cookieid,

createtime,

pv,

RANK() OVER(PARTITION BY cookieid ORDER BY pv desc) AS rn1,

DENSE_RANK() OVER(PARTITION BY cookieid ORDER BY pv desc) AS rn2,

ROW_NUMBER() OVER(PARTITION BY cookieid ORDER BY pv DESC) AS rn3

FROM it_t1

WHERE cookieid = 'cookie1';

二、Hive分析窗口函数 SUM,AVG,MIN,MAX

1、数据准备

--建表语句:

create table it_t2(

cookieid string,

createtime string,   --day

pv int

) row format delimited

fields terminated by ',';

--加载数据：

load data local inpath '/root/hivedata/ it_t2.txt' into table it_t2;

--开启智能本地模式

SET hive.exec.mode.local.auto=true;

2、SUM（结果和ORDER BY相关,默认为升序）

select cookieid,createtime,pv,

sum(pv) over(partition by cookieid order by createtime) as pv1

from it_t2;

select cookieid,createtime,pv,

sum(pv) over(partition by cookieid order by createtime rows between unbounded preceding and current row) as pv2

from it_t2;

select cookieid,createtime,pv,

sum(pv) over(partition by cookieid) as pv3

from it_t2;  --如果没有order  by排序语句  默认把分组内的所有数据进行sum操作

select cookieid,createtime,pv,

sum(pv) over(partition by cookieid order by createtime rows between 3 preceding and current row) as pv4

from it_t2;

select cookieid,createtime,pv,

sum(pv) over(partition by cookieid order by createtime rows between 3 preceding and 1 following) as pv5

from it_t2;

select cookieid,createtime,pv,

sum(pv) over(partition by cookieid order by createtime rows between current row and unbounded following) as pv6

from it_t2;

--pv1: 分组内从起点到当前行的pv累积，如，11号的pv1=10号的pv+11号的pv, 12号=10号+11号+12号

--pv2: 同pv1

--pv3: 分组内(cookie1)所有的pv累加

--pv4: 分组内当前行+往前3行，如，11号=10号+11号， 12号=10号+11号+12号，

                       13号=10号+11号+12号+13号， 14号=11号+12号+13号+14号

--pv5: 分组内当前行+往前3行+往后1行，如，14号=11号+12号+13号+14号+15号=5+7+3+2+4=21

--pv6: 分组内当前行+往后所有行，如，13号=13号+14号+15号+16号=3+2+4+4=13，

 14号=14号+15号+16号=2+4+4=10

/*

- 如果不指定rows between,默认为从起点到当前行;

- 如果不指定order by，则将分组内所有值累加;

- 关键是理解rows between含义,也叫做window子句：

  - preceding：往前

  - following：往后

  - current row：当前行

  - unbounded：起点

  - unbounded preceding 表示从前面的起点

  - unbounded following：表示到后面的终点

 */ 

3、AVG，MIN，MAX

AVG,MIN,MAX和SUM用法一样

select cookieid,createtime,pv,

avg(pv) over(partition by cookieid order by createtime rows between unbounded preceding and current row) as pv2

from it_t2;

select cookieid,createtime,pv,

max(pv) over(partition by cookieid order by createtime rows between unbounded preceding and current row) as pv2

from it_t2;

select cookieid,createtime,pv,

min(pv) over(partition by cookieid order by createtime rows between unbounded preceding and current row) as pv2

from it_t2;

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