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OLAP 多维聚合函数
Hive OLAP 多维聚合函数是增强版的 Group By 语句。一般和 Group By 同时使用，用来进行多维分析。
本文总结 Hive 三种常用的多维聚合函数:With Cube 任意维度聚合、Grouping Sets 指定维度聚合、With Rollup 层级维度聚合。
测试数据
— 建表
create table student_scores(
id int,
studentId int,
language int,
math int,
english int,
classId string,
departmentId string
);
— 写入数据
insert into table student_scores values
(1,111,68,69,90,’class1′,’department1′),
(2,112,73,80,96,’class1′,’department1′),
(3,113,90,74,75,’class1′,’department1′),
(4,114,89,94,93,’class1′,’department1′),
(5,115,99,93,89,’class1′,’department1′),
(6,121,96,74,79,’class2′,’department1′),
(7,122,89,86,85,’class2′,’department1′),
(8,123,70,78,61,’class2′,’department1′),
(9,124,76,70,76,’class2′,’department1′),
(10,211,89,93,60,’class1′,’department2′),
(11,212,76,83,75,’class1′,’department2′),
(12,213,71,94,90,’class1′,’department2′),
(13,214,94,94,66,’class1′,’department2′),
(14,215,84,82,73,’class1′,’department2′),
(15,216,85,74,93,’class1′,’department2′),
(16,221,77,99,61,’class2′,’department2′),
(17,222,80,78,96,’class2′,’department2′),
(18,223,79,74,96,’class2′,’department2′),
(19,224,75,80,78,’class2′,’department2′),
(20,225,82,85,63,’class2′,’department2′);
With Cube 任意维度聚合
语法:GROUP BY a,b WITH CUBE。
作用: 根据 Group BY 维度的所有可能组合进行聚合。类似于 Apache Kylin 的 Cube 多维立方体概念。n 个维度会有 2 的 n 次方种组合。
select departmentid,classid,sum(math) as sumMath,count(distinct studentid) as uv
from student_scores group by departmentid,classid with cube;
结果
departmentid classid summath uv
NULL NULL 1654 20
NULL class1 930 11
NULL class2 724 9
department1 NULL 718 9
department1 class1 410 5
department1 class2 308 4
department2 NULL 936 11
department2 class1 520 6
department2 class2 416 5
等价于 union all:
— 0 个维度 - 没有维度
select null as departmentid,null classid,sum(math) as sumMath,count(distinct studentid) as uv
from student_scores
union all
— 1 个维度 -classid
select null as departmentid,classid,sum(math) as sumMath,count(distinct studentid) as uv
from student_scores group by classid
union all
— 1 个维度 -departmentid
select departmentid,null as classid,sum(math) as sumMath,count(distinct studentid) as uv
from student_scores group by departmentid
union all
— 2 个维度 -departmentid、classid
select departmentid,classid,sum(math) as sumMath,count(distinct studentid) as uv
from student_scores group by departmentid,classid;
Grouping Sets 指定维度聚合
语法:GROUP BY a,b GROUPING SETS (a,b)
作用: 根据 GROUPING SETS 指定维度组合进行聚合。是 Cube 的一部分。Grouping Sets 分组 (Grouping) 集 (Sets)，是多个分组的并集。等价于 Union ALL 单个分组结果。如 grouping sets(A,B) 等价于 …group by null,B union all …group by A,null。
select departmentid,classid,sum(math) as sumMath,count(distinct studentid) as uv
from student_scores
group by departmentid,classid grouping sets((departmentid,classid),departmentid);
结果:
departmentid classid summath uv
department1 NULL 718 9
department1 class1 410 5
department1 class2 308 4
department2 NULL 936 11
department2 class1 520 6
department2 class2 416 5
等价于 union all:
select departmentid,classid,sum(math) as sumMath,count(distinct studentid) as uv
from student_scores
group by departmentid,classid
union all
select departmentid,null as classid,sum(math) as sumMath,count(distinct studentid) as uv
from student_scores
group by departmentid,null;
With Rollup 层级维度聚合
语法:GROUP BY a,b,c WITH ROLLUP
作用: 以 GROUP BY 最左侧的维度为主，从该维度的角度去上卷、下钻。是 Cube 的一部分。
select departmentid,classid,sum(math) as sumMath,count(distinct studentid) as uv
from student_scores group by departmentid,classid with rollup;
结果
departmentid classid summath uv
NULL NULL 1654 20
department1 NULL 718 9
department1 class1 410 5
department1 class2 308 4
department2 NULL 936 11
department2 class1 520 6
department2 class2 416 5
等价于 union all:
— 下钻
select departmentid,classid,sum(math) as sumMath,count(distinct studentid) as uv from student_scores
group by departmentid,classid
union all
select departmentid,null as classid,sum(math) as sumMath,count(distinct studentid) as uv from student_scores
group by departmentid,null
— 上卷
union all
select null as departmentid,null as classid,sum(math) as sumMath,count(distinct studentid) as uv from student_scores
group by null,null;
：
