[Oracle] Group By 语句的扩展 - Rollup、Cube和Grouping Sets

经常写SQL语句的人应该知道Group by语句的主要用法是进行分类汇总，下面是一种它最常见的用法（根据部门、职位分别统计业绩）：

SELECT  a.dname,b.job,SUM(b.sal) sum_sal
FROM dept a,emp b
WHERE a.deptno = b.deptno
GROUP  BY a.dname,b.job;

DNAME          JOB          SUM_SAL
-------------- --------- ----------
SALES          MANAGER         2850
SALES          CLERK            950
SALES          SALESMAN        5600
ACCOUNTING     MANAGER         2450
ACCOUNTING     PRESIDENT       5000
ACCOUNTING     CLERK           1300
RESEARCH       MANAGER         2975
RESEARCH       ANALYST         6000
RESEARCH       CLERK           1900

这时候，如果有人跑过来跟你说：我除了以上数据之外，还要每个部门总的业绩以及所有部门加起来的业绩，这时候你很可能会想到如下的笨方法（union all）：

select * from (
SELECT  a.dname,b.job,SUM(b.sal) sum_sal
FROM dept a,emp b
WHERE a.deptno = b.deptno
GROUP  BY a.dname,b.job
UNION ALL
--实现了部门的小计
SELECT  a.dname,NULL, SUM(b.sal) sum_sal
FROM dept a,emp b
WHERE a.deptno = b.deptno
GROUP  BY a.dname
UNION ALL
--实现了所有部门总的合计
SELECT  NULL,NULL, SUM(b.sal) sum_sal
FROM dept a,emp b
WHERE a.deptno = b.deptno)
order by dname;

DNAME          JOB          SUM_SAL
-------------- --------- ----------
ACCOUNTING     CLERK           1300
ACCOUNTING     MANAGER         2450
ACCOUNTING     PRESIDENT       5000
ACCOUNTING                     8750
RESEARCH       CLERK           1900
RESEARCH       MANAGER         2975
RESEARCH       ANALYST         6000
RESEARCH                      10875
SALES          CLERK            950
SALES          MANAGER         2850
SALES          SALESMAN        5600
SALES                          9400
29025

union all 合并笨办法产生的执行计划
-------------------------------------------------------------------------------
Plan hash value: 2979078843
-------------------------------------------------------------------------------
| Id  | Operation              | Name | Rows  | Bytes | Cost (%CPU)| Time     |
-------------------------------------------------------------------------------
|   0 | SELECT STATEMENT       |      |    29 |   812 |    23  (22)| 00:00:01 |
|   1 |  SORT ORDER BY         |      |    29 |   812 |    23  (22)| 00:00:01 |
|   2 |   VIEW                 |      |    29 |   812 |    22  (19)| 00:00:01 |
|   3 |    UNION-ALL           |      |       |       |            |          |
|   4 |     HASH GROUP BY      |      |    14 |   756 |     8  (25)| 00:00:01 |
|*  5 |      HASH JOIN         |      |    14 |   756 |     7  (15)| 00:00:01 |
|   6 |       TABLE ACCESS FULL| DEPT |     4 |    88 |     3   (0)| 00:00:01 |
|   7 |       TABLE ACCESS FULL| EMP  |    14 |   448 |     3   (0)| 00:00:01 |
|   8 |     HASH GROUP BY      |      |    14 |   672 |     8  (25)| 00:00:01 |
|*  9 |      HASH JOIN         |      |    14 |   672 |     7  (15)| 00:00:01 |
|  10 |       TABLE ACCESS FULL| DEPT |     4 |    88 |     3   (0)| 00:00:01 |
|  11 |       TABLE ACCESS FULL| EMP  |    14 |   364 |     3   (0)| 00:00:01 |
|  12 |     SORT AGGREGATE     |      |     1 |    39 |            |          |
|* 13 |      HASH JOIN         |      |    14 |   546 |     7  (15)| 00:00:01 |
|  14 |       TABLE ACCESS FULL| DEPT |     4 |    52 |     3   (0)| 00:00:01 |
|  15 |       TABLE ACCESS FULL| EMP  |    14 |   364 |     3   (0)| 00:00:01 |
-------------------------------------------------------------------------------

其实，如果你知道Group By的Rollup扩展的话，这种需求只是小case：

SELECT  a.dname,b.job, SUM(b.sal) sum_sal
FROM dept a,emp b
WHERE a.deptno = b.deptno
GROUP  BY ROLLUP(a.dname,b.job);

DNAME          JOB          SUM_SAL
-------------- --------- ----------
SALES          CLERK            950
SALES          MANAGER         2850
SALES          SALESMAN        5600
SALES                          9400
RESEARCH       CLERK           1900
RESEARCH       ANALYST         6000
RESEARCH       MANAGER         2975
RESEARCH                      10875
ACCOUNTING     CLERK           1300
ACCOUNTING     MANAGER         2450
ACCOUNTING     PRESIDENT       5000
ACCOUNTING                     8750
29025

rollup写法产生的执行计划
-----------------------------------------------------------------------------
Plan hash value: 1037965942
-----------------------------------------------------------------------------
| Id  | Operation            | Name | Rows  | Bytes | Cost (%CPU)| Time     |
-----------------------------------------------------------------------------
|   0 | SELECT STATEMENT     |      |    14 |   756 |     8  (25)| 00:00:01 |
|   1 |  SORT GROUP BY ROLLUP|      |    14 |   756 |     8  (25)| 00:00:01 |
|*  2 |   HASH JOIN          |      |    14 |   756 |     7  (15)| 00:00:01 |
|   3 |    TABLE ACCESS FULL | DEPT |     4 |    88 |     3   (0)| 00:00:01 |
|   4 |    TABLE ACCESS FULL | EMP  |    14 |   448 |     3   (0)| 00:00:01 |
-----------------------------------------------------------------------------

可以发现，这种方法不但SQL书写方便，性能也能得到提高。
这时候，如果又有人跑过来说：除了以上数据，他还需要每个职位总的业绩，你只要把rollup换成cube就可以了，如下所示：

-- CUBE分组
SELECT  a.dname,b.job, SUM(b.sal) sum_sal
FROM dept a,emp b
WHERE a.deptno = b.deptno
GROUP  BY CUBE(a.dname,b.job);

DNAME          JOB          SUM_SAL
-------------- --------- ----------
29025
CLERK           4150
ANALYST         6000
MANAGER         8275
SALESMAN        5600
PRESIDENT       5000
SALES                          9400
SALES          CLERK            950
SALES          MANAGER         2850
SALES          SALESMAN        5600
RESEARCH                      10875
RESEARCH       CLERK           1900
RESEARCH       ANALYST         6000
RESEARCH       MANAGER         2975
ACCOUNTING                     8750
ACCOUNTING     CLERK           1300
ACCOUNTING     MANAGER         2450
ACCOUNTING     PRESIDENT       5000

从上面可以看出：cube比rollup的展现的粒度更细一些。
这时候，如果又有人跑过来说：他不需要那么细的数据，只需要汇总的数据，可以使用Grouping Sets：

---GROUPING SETS分组
SELECT to_char(b.hiredate,'yyyy') hire_year,a.dname,b.job, SUM(sal) sum_sal
FROM dept a,emp b
WHERE a.deptno = b.deptno
GROUP BY GROUPING SETS(to_char(b.hiredate,'yyyy'),a.dname,b.job);

HIRE DNAME          JOB          SUM_SAL
---- -------------- --------- ----------
1987                                4100
1980                                 800
1982                                1300
1981                               22825
ACCOUNTING                     8750
RESEARCH                      10875
SALES                          9400
CLERK           4150
SALESMAN        5600
PRESIDENT       5000
MANAGER         8275
ANALYST         6000