hive 中的grouping set,cube,roll up函数

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GROUPING SETS

GROUPING SETS作为GROUP BY的子句,允许开发人员在GROUP BY语句后面指定多个统计选项,可以简单理解为多条group by语句通过union all把查询结果聚合起来结合起来,下面是几个实例可以帮助我们了解,

以acorn_3g.test_xinyan_reg为例:

[dp@YZSJHL19-87 xjob]$ hive -e "use acorn_3g;desc test_xinyan_reg;"
user_id                 bigint                  None                 
device_id               int                     None   手机,平板             
os_id                   int                     None   操作系统类型             
app_id                  int                     None   手机app_id             
client_version          string                  None   客户端版本             
from_id                 int                     None   四级渠道
 
 
grouping sets语句 等价hive语句
select device_id,os_id,app_id,count(user_id) from  test_xinyan_reg group by device_id,os_id,app_id grouping sets((device_id))  SELECT device_id,null,null,count(user_id) FROM test_xinyan_reg group by device_id
select device_id,os_id,app_id,count(user_id) from  test_xinyan_reg group by device_id,os_id,app_id grouping sets((device_id,os_id)) SELECT device_id,os_id,null,count(user_id) FROM test_xinyan_reg group by device_id,os_id
select device_id,os_id,app_id,count(user_id) from  test_xinyan_reg group by device_id,os_id,app_id grouping sets((device_id,os_id),(device_id)) SELECT device_id,os_id,null,count(user_id) FROM test_xinyan_reg group by device_id,os_id 
UNION ALL 
SELECT device_id,null,null,count(user_id) FROM test_xinyan_reg group by device_id
select device_id,os_id,app_id,count(user_id) from  test_xinyan_reg group by device_id,os_id,app_id grouping sets((device_id),(os_id),(device_id,os_id),()) SELECT device_id,null,null,count(user_id) FROM test_xinyan_reg group by device_id 
UNION ALL 
SELECT null,os_id,null,count(user_id) FROM test_xinyan_reg group by os_id 
UNION ALL 
SELECT device_id,os_id,null,count(user_id) FROM test_xinyan_reg group by device_id,os_id  
UNION ALL 
SELECT null,null,null,count(user_id) FROM test_xinyan_reg

 

CUBE

 

cube简称数据魔方,可以实现hive多个任意维度的查询,cube(a,b,c)则首先会对(a,b,c)进行group by,然后依次是(a,b),(a,c),(a),(b,c),(b),(c),最后在对全表进行group by,他会统计所选列中值的所有组合的聚合

select device_id,os_id,app_id,client_version,from_id,count(user_id) 
from test_xinyan_reg 
group by device_id,os_id,app_id,client_version,from_id with cube;

等价于以下sql

SELECT device_id,null,null,null,null ,count(user_id) FROM test_xinyan_reg group by device_id
UNION ALL
SELECT null,os_id,null,null,null ,count(user_id) FROM test_xinyan_reg group by os_id
UNION ALL
SELECT device_id,os_id,null,null,null ,count(user_id) FROM test_xinyan_reg group by device_id,os_id
UNION ALL
SELECT null,null,app_id,null,null ,count(user_id) FROM test_xinyan_reg group by app_id
UNION ALL
SELECT device_id,null,app_id,null,null ,count(user_id) FROM test_xinyan_reg group by device_id,app_id
UNION ALL
SELECT null,os_id,app_id,null,null ,count(user_id) FROM test_xinyan_reg group by os_id,app_id
UNION ALL
SELECT device_id,os_id,app_id,null,null ,count(user_id) FROM test_xinyan_reg group by device_id,os_id,app_id
UNION ALL
SELECT null,null,null,client_version,null ,count(user_id) FROM test_xinyan_reg group by client_version
UNION ALL
SELECT device_id,null,null,client_version,null ,count(user_id) FROM test_xinyan_reg group by device_id,client_version
UNION ALL
SELECT null,os_id,null,client_version,null ,count(user_id) FROM test_xinyan_reg group by os_id,client_version
UNION ALL
SELECT device_id,os_id,null,client_version,null ,count(user_id) FROM test_xinyan_reg group by device_id,os_id,client_version
UNION ALL
SELECT null,null,app_id,client_version,null ,count(user_id) FROM test_xinyan_reg group by app_id,client_version
UNION ALL
SELECT device_id,null,app_id,client_version,null ,count(user_id) FROM test_xinyan_reg group by device_id,app_id,client_version
UNION ALL
SELECT null,os_id,app_id,client_version,null ,count(user_id) FROM test_xinyan_reg group by os_id,app_id,client_version
UNION ALL
SELECT device_id,os_id,app_id,client_version,null ,count(user_id) FROM test_xinyan_reg group by device_id,os_id,app_id,client_version
UNION ALL
SELECT null,null,null,null,from_id ,count(user_id) FROM test_xinyan_reg group by from_id
UNION ALL
SELECT device_id,null,null,null,from_id ,count(user_id) FROM test_xinyan_reg group by device_id,from_id
UNION ALL
SELECT null,os_id,null,null,from_id ,count(user_id) FROM test_xinyan_reg group by os_id,from_id
UNION ALL
SELECT device_id,os_id,null,null,from_id ,count(user_id) FROM test_xinyan_reg group by device_id,os_id,from_id
UNION ALL
SELECT null,null,app_id,null,from_id ,count(user_id) FROM test_xinyan_reg group by app_id,from_id
UNION ALL
SELECT device_id,null,app_id,null,from_id ,count(user_id) FROM test_xinyan_reg group by device_id,app_id,from_id
UNION ALL
SELECT null,os_id,app_id,null,from_id ,count(user_id) FROM test_xinyan_reg group by os_id,app_id,from_id
UNION ALL
SELECT device_id,os_id,app_id,null,from_id ,count(user_id) FROM test_xinyan_reg group by device_id,os_id,app_id,from_id
UNION ALL
SELECT null,null,null,client_version,from_id ,count(user_id) FROM test_xinyan_reg group by client_version,from_id
UNION ALL
SELECT device_id,null,null,client_version,from_id ,count(user_id) FROM test_xinyan_reg group by device_id,client_version,from_id
UNION ALL
SELECT null,os_id,null,client_version,from_id ,count(user_id) FROM test_xinyan_reg group by os_id,client_version,from_id
UNION ALL
SELECT device_id,os_id,null,client_version,from_id ,count(user_id) FROM test_xinyan_reg group by device_id,os_id,client_version,from_id
UNION ALL
SELECT null,null,app_id,client_version,from_id ,count(user_id) FROM test_xinyan_reg group by app_id,client_version,from_id
UNION ALL
SELECT device_id,null,app_id,client_version,from_id ,count(user_id) FROM test_xinyan_reg group by device_id,app_id,client_version,from_id
UNION ALL
SELECT null,os_id,app_id,client_version,from_id ,count(user_id) FROM test_xinyan_reg group by os_id,app_id,client_version,from_id
UNION ALL
SELECT device_id,os_id,app_id,client_version,from_id ,count(user_id) FROM test_xinyan_reg group by device_id,os_id,app_id,client_version,from_id
UNION ALL
SELECT null,null,null,null,null ,count(user_id) FROM test_xinyan_reg

ROLL UP

rollup可以实现从右到做递减多级的统计,显示统计某一层次结构的聚合。

 select device_id,os_id,app_id,client_version,from_id,count(user_id) 
from test_xinyan_reg 
group by device_id,os_id,app_id,client_version,from_id with rollup;

等价于以下sql

 select device_id,os_id,app_id,client_version,from_id,count(user_id) 
from test_xinyan_reg 
group by device_id,os_id,app_id,client_version,from_id 
grouping sets ((device_id,os_id,app_id,client_version,from_id),(device_id,os_id,app_id,client_version),(device_id,os_id,app_id),(device_id,os_id),(device_id),());

Grouping_ID

当我们没有统计某一列时,它的值显示为null,这可能与列本身就有null值冲突,这就需要一种方法区分是没有统计还是值本来就是null。(grouping_id其实就是所统计各列二进制和)

Column1 (key) Column2 (value)
1 NULL
1 1
2 2
3 3
3 NULL
4 5

hsql:

  SELECT key, value, GROUPING__ID, count(*) from T1 GROUP BY key, value WITH ROLLUP

结果:

NULL NULL 0     00 6
1 NULL 1     10 2
1 NULL 3     11 1
1 1 3     11 1
2 NULL 1     10 1
2 2 3     11 1
3 NULL 1     10 2
3 NULL 3     11 1
3 3 3     11 1
4 NULL 1     10 1
4 5 3     11 1

GROUPING__ID转变为二进制,如果对应位上有值为null,说明这列本身值就是null。

转载于:https://my.oschina.net/u/2000675/blog/2050360

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