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GROUPING SETS

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对于经常需要对数据进行多维度的聚合分析的场景,您既需要对A列做聚合,也要对B列做聚合,同时要对A、B两列做聚合,因此需要多次使用union all。您可以使用grouping sets快速解决此类问题。本文为您介绍如何使用grouping sets进行多维聚合。

功能介绍

grouping sets是对select语句中group by子句的扩展,允许您采用多种方式对结果分组,而不必使用多个select语句再union all来实现。这样能够使MaxCompute的引擎给出更有效的执行计划,从而提高执行性能。

grouping sets相关联的语法如下。

类型

说明

cube

特殊的grouping sets,将指定列的所有可能组合作为grouping sets,也可以与grouping sets组合使用。

group by cube (a, b, c)  
--等效于以下语句。  
grouping sets ((a,b,c),(a,b),(a,c),(b,c),(a),(b),(c),())

group by cube ( (a, b), (c, d) ) 
--等效于以下语句。 
grouping sets (
    ( a, b, c, d ),
    ( a, b       ),
    (       c, d ),
    (            )
)
group by a, cube (b, c), grouping sets ((d), (e)) 
--等效于以下语句。 
group by grouping sets (
    (a, b, c, d), (a, b, c, e),
    (a, b, d),    (a, b, e),
    (a, c, d),    (a, c, e),
    (a, d),       (a, e)
)

rollup

特殊的grouping sets,以按层级聚合的方式产生grouping sets,也可以与grouping sets组合使用。

group by rollup (a, b, c)
--等效价于以下语句。  
grouping sets ((a,b,c),(a,b),(a), ())

group by rollup ( a, (b, c), d ) 
--等效于以下语句。
grouping sets (
    ( a, b, c, d ),
    ( a, b, c    ),
    ( a          ),
    (            )
)
group by grouping sets((b), (c), rollup(a,b,c)) 
--等效于以下语句。 
group by grouping sets (
    (b), (c),
    (a,b,c), (a,b), (a), ()
 )

grouping

grouping sets结果中使用NULL充当占位符,导致您会无法区分占位符NULL与数据中真正的NULL。因此,MaxCompute为您提供了groupinggrouping接受一个列名作为参数,如果结果对应行使用了参数列做聚合,返回0,此时意味着NULL来自输入数据。否则返回1,此时意味着NULL是grouping sets的占位符。

grouping_id

接受一个或多个列名作为参数。结果是将参数列的grouping结果按照Bitmap的方式组成整数。

grouping__id

grouping__id不带参数,用于兼容Hive查询。此表达方式在MaxCompute中等价于grouping_id(group by参数列表),参数与group by的顺序一致。

说明

MaxCompute和Hive 2.3.0及以上版本兼容该函数,在Hive 2.3.0以下版本中该函数输出不一致,因此并不推荐您使用此函数。

GROUPING SETS使用示例

grouping sets使用示例如下:

  1. 准备数据。

    create table requests lifecycle 20 as 
    select * from values 
        (1, 'windows', 'PC', 'Beijing'),
        (2, 'windows', 'PC', 'Shijiazhuang'),
        (3, 'linux', 'Phone', 'Beijing'),
        (4, 'windows', 'PC', 'Beijing'),
        (5, 'ios', 'Phone', 'Shijiazhuang'),
        (6, 'linux', 'PC', 'Beijing'),
        (7, 'windows', 'Phone', 'Shijiazhuang') 
    as t(id, os, device, city);
  2. 对数据进行分组。您可以通过如下两种方式进行分组:

    • 使用多个select语句进行分组。

      select NULL, NULL, NULL, count(*)
      from requests
      union all
      select os, device, NULL, count(*)
      from requests group by os, device
      union all
      select null, null, city, count(*)
      from requests group by city;
    • 使用grouping sets进行分组。

      select os,device, city ,count(*)
      from requests
      group by grouping sets((os, device), (city), ());

      返回结果如下:

      +------------+------------+------------+------------+
      | os         | device     | city       | _c3        |
      +------------+------------+------------+------------+
      | NULL       | NULL       | NULL       | 7          |
      | NULL       | NULL       | Beijing    | 4          |
      | NULL       | NULL       | Shijiazhuang | 3          |
      | ios        | Phone      | NULL       | 1          |
      | linux      | PC         | NULL       | 1          |
      | linux      | Phone      | NULL       | 1          |
      | windows    | PC         | NULL       | 3          |
      | windows    | Phone      | NULL       | 1          |
      +------------+------------+------------+------------+
    说明

    分组集中不使用的表达式,会使用NULL充当占位符,使得这些结果集可以做操作。例如结果第4~8行的city列。

CUBE | ROLLUP使用示例

基于grouping sets示例表,cuberollup使用示例如下:

  • 示例1:通过cube枚举os、device、city的所有可能列为grouping sets。命令示例如下:

    select os,device, city, count(*)
    from requests 
    group by cube (os, device, city);
    --等效于如下语句。
    select os,device, city, count(*)
    from requests 
    group by grouping sets ((os, device, city),(os, device),(os, city),(device,city),(os),(device),(city),());

    返回结果如下:

    +------------+------------+------------+------------+
    | os         | device     | city       | _c3        |
    +------------+------------+------------+------------+
    | NULL       | NULL       | NULL       | 7          |
    | NULL       | NULL       | Beijing    | 4          |
    | NULL       | NULL       | Shijiazhuang | 3          |
    | NULL       | PC         | NULL       | 4          |
    | NULL       | PC         | Beijing    | 3          |
    | NULL       | PC         | Shijiazhuang | 1          |
    | NULL       | Phone      | NULL       | 3          |
    | NULL       | Phone      | Beijing    | 1          |
    | NULL       | Phone      | Shijiazhuang | 2          |
    | ios        | NULL       | NULL       | 1          |
    | ios        | NULL       | Shijiazhuang | 1          |
    | ios        | Phone      | NULL       | 1          |
    | ios        | Phone      | Shijiazhuang | 1          |
    | linux      | NULL       | NULL       | 2          |
    | linux      | NULL       | Beijing    | 2          |
    | linux      | PC         | NULL       | 1          |
    | linux      | PC         | Beijing    | 1          |
    | linux      | Phone      | NULL       | 1          |
    | linux      | Phone      | Beijing    | 1          |
    | windows    | NULL       | NULL       | 4          |
    | windows    | NULL       | Beijing    | 2          |
    | windows    | NULL       | Shijiazhuang | 2          |
    | windows    | PC         | NULL       | 3          |
    | windows    | PC         | Beijing    | 2          |
    | windows    | PC         | Shijiazhuang | 1          |
    | windows    | Phone      | NULL       | 1          |
    | windows    | Phone      | Shijiazhuang | 1          |
    +------------+------------+------------+------------+
  • 示例2:通过cube枚举(os, device),(device, city)所有可能列为grouping sets。命令示例如下:

    select os,device, city, count(*) 
    from requests 
    group by cube ((os, device), (device, city));
    --等效于如下语句。
    select os,device, city, count(*) 
    from requests 
    group by grouping sets ((os, device, city),(os, device),(device,city),());

    返回结果如下:

    +------------+------------+------------+------------+
    | os         | device     | city       | _c3        |
    +------------+------------+------------+------------+
    | NULL       | NULL       | NULL       | 7          |
    | NULL       | PC         | Beijing    | 3          |
    | NULL       | PC         | Shijiazhuang | 1          |
    | NULL       | Phone      | Beijing    | 1          |
    | NULL       | Phone      | Shijiazhuang | 2          |
    | ios        | Phone      | NULL       | 1          |
    | ios        | Phone      | Shijiazhuang | 1          |
    | linux      | PC         | NULL       | 1          |
    | linux      | PC         | Beijing    | 1          |
    | linux      | Phone      | NULL       | 1          |
    | linux      | Phone      | Beijing    | 1          |
    | windows    | PC         | NULL       | 3          |
    | windows    | PC         | Beijing    | 2          |
    | windows    | PC         | Shijiazhuang | 1          |
    | windows    | Phone      | NULL       | 1          |
    | windows    | Phone      | Shijiazhuang | 1          |
    +------------+------------+------------+------------+
  • 示例3:通过rollup对os、device、city以按层级聚合的方式产生grouping sets。命令示例如下:

    select os,device, city, count(*)
    from requests 
    group by rollup (os, device, city);
    --等效于如下语句。
    select os,device, city, count(*)
    from requests 
    group by grouping sets ((os, device, city),(os, device),(os),());

    返回结果如下:

    +------------+------------+------------+------------+
    | os         | device     | city       | _c3        |
    +------------+------------+------------+------------+
    | NULL       | NULL       | NULL       | 7          |
    | ios        | NULL       | NULL       | 1          |
    | ios        | Phone      | NULL       | 1          |
    | ios        | Phone      | Shijiazhuang | 1          |
    | linux      | NULL       | NULL       | 2          |
    | linux      | PC         | NULL       | 1          |
    | linux      | PC         | Beijing    | 1          |
    | linux      | Phone      | NULL       | 1          |
    | linux      | Phone      | Beijing    | 1          |
    | windows    | NULL       | NULL       | 4          |
    | windows    | PC         | NULL       | 3          |
    | windows    | PC         | Beijing    | 2          |
    | windows    | PC         | Shijiazhuang | 1          |
    | windows    | Phone      | NULL       | 1          |
    | windows    | Phone      | Shijiazhuang | 1          |
    +------------+------------+------------+------------+
  • 示例4:通过rollupos, (os,device), city以按层级聚合的方式产生grouping sets。命令示例如下:

    select os,device, city, count(*)
    from requests 
    group by rollup (os, (os,device), city);
    --等效于如下语句。
    select os,device, city, count(*)
    from requests 
    group by grouping sets ((os, device, city),(os, device),(os),());

    返回结果如下:

    +------------+------------+------------+------------+
    | os         | device     | city       | _c3        |
    +------------+------------+------------+------------+
    | NULL       | NULL       | NULL       | 7          |
    | ios        | NULL       | NULL       | 1          |
    | ios        | Phone      | NULL       | 1          |
    | ios        | Phone      | Shijiazhuang | 1          |
    | linux      | NULL       | NULL       | 2          |
    | linux      | PC         | NULL       | 1          |
    | linux      | PC         | Beijing    | 1          |
    | linux      | Phone      | NULL       | 1          |
    | linux      | Phone      | Beijing    | 1          |
    | windows    | NULL       | NULL       | 4          |
    | windows    | PC         | NULL       | 3          |
    | windows    | PC         | Beijing    | 2          |
    | windows    | PC         | Shijiazhuang | 1          |
    | windows    | Phone      | NULL       | 1          |
    | windows    | Phone      | Shijiazhuang | 1          |
    +------------+------------+------------+------------+
  • 示例5:通过group bycubegrouping sets组合产生grouping sets。命令示例如下:

    select os,device, city, count(*)
    from requests 
    group by os, cube(os,device), grouping sets(city);
    --等效于如下语句。
    select os,device, city, count(*)
    from requests 
    group by grouping sets((os,device,city),(os,city),(os,device,city));

    返回结果如下:

    +------------+------------+------------+------------+
    | os         | device     | city       | _c3        |
    +------------+------------+------------+------------+
    | ios        | NULL       | Shijiazhuang | 1          |
    | ios        | Phone      | Shijiazhuang | 1          |
    | linux      | NULL       | Beijing    | 2          |
    | linux      | PC         | Beijing    | 1          |
    | linux      | Phone      | Beijing    | 1          |
    | windows    | NULL       | Beijing    | 2          |
    | windows    | NULL       | Shijiazhuang | 2          |
    | windows    | PC         | Beijing    | 2          |
    | windows    | PC         | Shijiazhuang | 1          |
    | windows    | Phone      | Shijiazhuang | 1          |
    +------------+------------+------------+------------+

GROUPING | GROUPING_ID使用示例

groupinggrouping_id使用示例如下:

select a,b,c,count(*),
grouping(a) ga, grouping(b) gb, grouping(c) gc, grouping_id(a,b,c) groupingid 
from values (1,2,3) as t(a,b,c)
group by cube(a,b,c);

返回结果如下:

+------------+------------+------------+------------+------------+------------+------------+------------+
| a          | b          | c          | _c3        | ga         | gb         | gc         | groupingid |
+------------+------------+------------+------------+------------+------------+------------+------------+
| NULL       | NULL       | NULL       | 1          | 1          | 1          | 1          | 7          |
| NULL       | NULL       | 3          | 1          | 1          | 1          | 0          | 6          |
| NULL       | 2          | NULL       | 1          | 1          | 0          | 1          | 5          |
| NULL       | 2          | 3          | 1          | 1          | 0          | 0          | 4          |
| 1          | NULL       | NULL       | 1          | 0          | 1          | 1          | 3          |
| 1          | NULL       | 3          | 1          | 0          | 1          | 0          | 2          |
| 1          | 2          | NULL       | 1          | 0          | 0          | 1          | 1          |
| 1          | 2          | 3          | 1          | 0          | 0          | 0          | 0          |
+------------+------------+------------+------------+------------+------------+------------+------------+

默认情况,group by列表中不被使用的列,会被填充为NULL。您可以通过grouping输出更有实际意义的值。基于grouping sets示例表,命令示例如下:

select
  if(grouping(os) == 0, os, 'ALL') as os,
  if(grouping(device) == 0, device, 'ALL') as device,
  if(grouping(city) == 0, city, 'ALL') as city, 
  count(*) as count 
from requests 
group by os, device, city grouping sets((os, device), (city), ());

返回结果如下:

+------------+------------+------------+------------+
| os         | device     | city       | count      |
+------------+------------+------------+------------+
| ALL        | ALL        | ALL        | 7          |
| ALL        | ALL        | Beijing    | 4          |
| ALL        | ALL        | Shijiazhuang | 3          |
| ios        | Phone      | ALL        | 1          |
| linux      | PC         | ALL        | 1          |
| linux      | Phone      | ALL        | 1          |
| windows    | PC         | ALL        | 3          |
| windows    | Phone      | ALL        | 1          |
+------------+------------+------------+------------+

GROUPING__ID使用示例

grouping__id不带参数的命令示例如下:

set odps.sql.hive.compatible=true;
select      
a, b, c, count(*), grouping__id 
from values (1,2,3) as t(a,b,c) 
group by a, b, c grouping sets ((a,b,c), (a));
--等效于如下语句。
select      
a, b, c, count(*), grouping_id(a,b,c)  
from values (1,2,3) as t(a,b,c) 
group by a, b, c grouping sets ((a,b,c), (a));

返回结果如下:

+------------+------------+------------+------------+------------+
| a          | b          | c          | _c3        | _c4        |
+------------+------------+------------+------------+------------+
| 1          | NULL       | NULL       | 1          | 3          |
| 1          | 2          | 3          | 1          | 0          |
+------------+------------+------------+------------+------------+
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