Oralce 高级 sql 之 rollup 与 cube
在 oracle sql 查询中，oracle 提供了一些高级功能能够简化 sql 查询语句以及提高查询性能。下面将介绍 rollup，cube的用法与区别。
1. rollup
1.2 rollup 例子
如果想用一条 sql 语句统计每个部门每个职位的总薪水，每个部门的总薪水以及所有部门的总薪水的话，势必要再用一个 group by 语句统计每个部门的总薪水然后再与上面的结果 union 起来才能得到最后的结果，但是这样写的话除了书写会复杂一点外，另外肯定还要多扫描几次 emp 与 dept 表，现在 oracle 提供了 rollup 子句，我们可以先来看看 rollup 子句的结果：
从上面的结果可以看出，group by cube(b.dname, a.job) 语句首先统计所有部门的总薪水，然后统计每个职位(a.job)的总薪水，然后统计每个部门(b.dname)的总薪水,最后统计每个部门每个职位(b.dname, a.job)的总薪水。
1. rollup
rollup 能够在 select 语句中计算指定分组字段的多个层次的小计以及合计. rollup 非常容易使用并且非常高效。
rollup 从右到左扫描分组字段, 逐步创建更高级别的小计. 最后再创建一行总计. rollup 将创建 n + 1 个层次(级别)的小计, n 指的是 rollup 中的字段数.
1.1 什么时候使用 rollup
- 对于一些层次维度的小计(统计某些层次字段的小计及总计)
- 对于数据仓库中的统计汇总表, rollup 能够简化统计汇总表并且提高查询统计汇总表的速度
首先构造两个基本表 emp(员工表) 与 dept(部门表)：
SQL> create table emp as select * from scott.emp;
Table created.
SQL> create table dept as select * from scott.dept;
Table created.
SQL> select * from emp;
EMPNO ENAME JOB MGR HIREDATE SAL COMM DEPTNO
---------- ---------- --------- ---------- --------- ---------- ---------- ----------
7369 SMITH CLERK 7902 17-DEC-80 800 20
7499 ALLEN SALESMAN 7698 20-FEB-81 1600 300 30
7521 WARD SALESMAN 7698 22-FEB-81 1250 500 30
7566 JONES MANAGER 7839 02-APR-81 2975 20
7654 MARTIN SALESMAN 7698 28-SEP-81 1250 1400 30
7698 BLAKE MANAGER 7839 01-MAY-81 2850 30
7782 CLARK MANAGER 7839 09-JUN-81 2450 10
7788 SCOTT ANALYST 7566 19-APR-87 3000 20
7839 KING PRESIDENT 17-NOV-81 5000 10
7844 TURNER SALESMAN 7698 08-SEP-81 1500 0 30
7876 ADAMS CLERK 7788 23-MAY-87 1100 20
7900 JAMES CLERK 7698 03-DEC-81 950 30
7902 FORD ANALYST 7566 03-DEC-81 3000 20
7934 MILLER CLERK 7782 23-JAN-82 1300 10
14 rows selected.
SQL> select * from dept;
DEPTNO DNAME LOC
---------- -------------- -------------
10 ACCOUNTING NEW YORK
20 RESEARCH DALLAS
30 SALES CHICAGO
40 OPERATIONS BOSTON
如果想统计每个部门每个职位的总薪水，sql 语句如下：
SQL> select b.dname, a.job, sum(a.sal)
2 from emp a, dept b
3 where a.deptno = b.deptno
4 group by b.dname, a.job;
DNAME JOB SUM(A.SAL)
-------------- --------- ----------
SALES MANAGER 2850
SALES CLERK 950
ACCOUNTING MANAGER 2450
ACCOUNTING PRESIDENT 5000
ACCOUNTING CLERK 1300
SALES SALESMAN 5600
RESEARCH MANAGER 2975
RESEARCH ANALYST 6000
RESEARCH CLERK 1900
9 rows selected.如果想用一条 sql 语句统计每个部门每个职位的总薪水，每个部门的总薪水以及所有部门的总薪水的话，势必要再用一个 group by 语句统计每个部门的总薪水然后再与上面的结果 union 起来才能得到最后的结果，但是这样写的话除了书写会复杂一点外，另外肯定还要多扫描几次 emp 与 dept 表，现在 oracle 提供了 rollup 子句，我们可以先来看看 rollup 子句的结果：
SQL> select b.dname, a.job, sum(a.sal)
2 from emp a, dept b
3 where a.deptno = b.deptno
4 group by rollup(b.dname, a.job);
DNAME JOB SUM(A.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从上面的结果中可以看出，rollup 子句会为每个部门增加一行小计以及为所有部门增加一行总计，即统计了每个部门的总薪水以及所有部门的总薪水。
通常来说，rollup 往往同 group by 语句一起使用，它是 group by 语句的一种扩展。
- 如果语句为 group by rollup(a, b)，oracle 将会从右到左先对字段 a 和 b 先进行 group by，然后对字段 A 进行 group by，最后对全表进行 group by。
- 如果语句为 group by rollup(a, b, c), oracle 将从右到左先会对字段 a 和 b 和 c 先进行 group by, 然后对字段 a 和 b 进行 group by，然后对字段 a 进行 group by，最后对全表进行 group by。
下面我们将演示一个 rollup 三个字段的例子：
SQL> select b.dname, a.job, to_char(hiredate, 'yyyy'), sum(sal)
2 from emp a, dept b
3 where a.deptno = b.deptno
4 group by b.dname, a.job, to_char(hiredate, 'yyyy')
5 order by 1, 2, 3;
DNAME JOB TO_C SUM(SAL)
-------------- --------- ---- ----------
ACCOUNTING CLERK 1982 1300
ACCOUNTING MANAGER 1981 2450
ACCOUNTING PRESIDENT 1981 5000
RESEARCH ANALYST 1981 3000
RESEARCH ANALYST 1987 3000
RESEARCH CLERK 1980 800
RESEARCH CLERK 1987 1100
RESEARCH MANAGER 1981 2975
SALES CLERK 1981 950
SALES MANAGER 1981 2850
SALES SALESMAN 1981 5600
11 rows selected.
SQL> select b.dname, a.job, to_char(hiredate, 'yyyy'), sum(sal)
2 from emp a, dept b
3 where a.deptno = b.deptno
4 group by rollup(b.dname, a.job, to_char(hiredate, 'yyyy'));
DNAME JOB TO_C SUM(SAL)
-------------- --------- ---- ----------
SALES CLERK 1981 950
SALES CLERK 950
SALES MANAGER 1981 2850
SALES MANAGER 2850
SALES SALESMAN 1981 5600
SALES SALESMAN 5600
SALES 9400
RESEARCH CLERK 1980 800
RESEARCH CLERK 1987 1100
RESEARCH CLERK 1900
RESEARCH ANALYST 1981 3000
RESEARCH ANALYST 1987 3000
RESEARCH ANALYST 6000
RESEARCH MANAGER 1981 2975
RESEARCH MANAGER 2975
RESEARCH 10875
ACCOUNTING CLERK 1982 1300
ACCOUNTING CLERK 1300
ACCOUNTING MANAGER 1981 2450
ACCOUNTING MANAGER 2450
ACCOUNTING PRESIDENT 1981 5000
ACCOUNTING PRESIDENT 5000
ACCOUNTING 8750
29025
24 rows selected.1.3 部分 rollup(Partial rollup)
当你只想统计部分字段时, 可以使用部分 rollup. 例如, group by a, rollup(b, c), 这条语句将创建三个(2 + 1)级别的小计. 分别为级别 (a, b, c), 级别 (a, b) 以及级别 (a).
SQL> select b.dname, a.job, to_char(hiredate, 'yyyy'), sum(sal)
2 from emp a, dept b
3 where a.deptno = b.deptno
4 group by b.dname, rollup(a.job, to_char(hiredate, 'yyyy'));
DNAME JOB TO_C SUM(SAL)
-------------- --------- ---- ----------
SALES CLERK 1981 950
SALES CLERK 950
SALES MANAGER 1981 2850
SALES MANAGER 2850
SALES SALESMAN 1981 5600
SALES SALESMAN 5600
SALES 9400
RESEARCH CLERK 1980 800
RESEARCH CLERK 1987 1100
RESEARCH CLERK 1900
RESEARCH ANALYST 1981 3000
RESEARCH ANALYST 1987 3000
RESEARCH ANALYST 6000
RESEARCH MANAGER 1981 2975
RESEARCH MANAGER 2975
RESEARCH 10875
ACCOUNTING CLERK 1982 1300
ACCOUNTING CLERK 1300
ACCOUNTING MANAGER 1981 2450
ACCOUNTING MANAGER 2450
ACCOUNTING PRESIDENT 1981 5000
ACCOUNTING PRESIDENT 5000
ACCOUNTING 8750
23 rows selected.从上面的结果中可以看出，部分 rollup 产生的结果:
- 普通的汇总行是由 group by 产生而不是 rollup
- 不会产生总计
2. cube
cube 可以为指定的列创建各种不同组合的小计. 如果指定的列的数量为 n, group by cube 将创建 2 * n 个层次的小计. cube 是一种比 rollup 更细粒度的分组统计语句。先看看 cube 语句的结果：
2.1 什么时候使用 cube
- 当需求中有类似 cross-tabular report (交叉报表)时
- 对于数据仓库中的统计汇总表, rollup 能够简化统计汇总表并且提高查询统计汇总表的速度
2.2 cube 例子
SQL> select b.dname, a.job, sum(a.sal)
2 from emp a, dept b
3 where a.deptno = b.deptno
4 group by cube(b.dname, a.job);
DNAME JOB SUM(A.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
18 rows selected.
从上面的结果可以看出，group by cube(b.dname, a.job) 语句首先统计所有部门的总薪水，然后统计每个职位(a.job)的总薪水，然后统计每个部门(b.dname)的总薪水,最后统计每个部门每个职位(b.dname, a.job)的总薪水。
- 如果语句为 group by cube(a, b)，oracle 首先对字段 a 和 b 进行 group by，然后对字段 a 进行 group by，然后对字段 b 进行 group by，最后对全表进行 group by。
- 如果语句为 group by cube(a, b, c)，oracle 进行分组的字段分别为 (a, b, c)，(a, b)，(a, c)，(b, c)，(a)，(b)，(c)，最后对全表的总计
下面演示 cube 三个字段的例子：
SQL> select b.dname, a.job, to_char(hiredate, 'yyyy'), sum(sal)
2 from emp a, dept b
3 where a.deptno = b.deptno
4 group by cube(b.dname, a.job, to_char(hiredate, 'yyyy'));
DNAME JOB TO_C SUM(SAL)
-------------- --------- ---- ----------
29025
1980 800
1981 22825
1982 1300
1987 4100
CLERK 4150
CLERK 1980 800
CLERK 1981 950
CLERK 1982 1300
CLERK 1987 1100
ANALYST 6000
ANALYST 1981 3000
ANALYST 1987 3000
MANAGER 8275
MANAGER 1981 8275
SALESMAN 5600
SALESMAN 1981 5600
PRESIDENT 5000
PRESIDENT 1981 5000
SALES 9400
SALES 1981 9400
SALES CLERK 950
SALES CLERK 1981 950
SALES MANAGER 2850
SALES MANAGER 1981 2850
SALES SALESMAN 5600
SALES SALESMAN 1981 5600
RESEARCH 10875
RESEARCH 1980 800
RESEARCH 1981 5975
RESEARCH 1987 4100
RESEARCH CLERK 1900
RESEARCH CLERK 1980 800
RESEARCH CLERK 1987 1100
RESEARCH ANALYST 6000
RESEARCH ANALYST 1981 3000
RESEARCH ANALYST 1987 3000
RESEARCH MANAGER 2975
RESEARCH MANAGER 1981 2975
ACCOUNTING 8750
ACCOUNTING 1981 7450
ACCOUNTING 1982 1300
ACCOUNTING CLERK 1300
ACCOUNTING CLERK 1982 1300
ACCOUNTING MANAGER 2450
ACCOUNTING MANAGER 1981 2450
ACCOUNTING PRESIDENT 5000
ACCOUNTING PRESIDENT 1981 5000
48 rows selected.
2.3 部分 cube (partial cube)
部分 cube 类似于部分 rollup, 把列放在 cube 操作符的外面能够限制生成列组合的小计. 例如, group by a, cube(b, c), 这条语句将产生 4 (2 * 2) 个层次的小计, 分别为层次 (a, b, c), 层次 (a, b), 层次 (a, c), 层次 (a).
SQL> select b.dname, a.job, to_char(hiredate, 'yyyy'), sum(sal)
2 from emp a, dept b
3 where a.deptno = b.deptno
4 group by b.dname, cube(a.job, to_char(hiredate, 'yyyy'));
DNAME JOB TO_C SUM(SAL)
-------------- --------- ---- ----------
SALES 9400
SALES 1981 9400
SALES CLERK 950
SALES CLERK 1981 950
SALES MANAGER 2850
SALES MANAGER 1981 2850
SALES SALESMAN 5600
SALES SALESMAN 1981 5600
RESEARCH 10875
RESEARCH 1980 800
RESEARCH 1981 5975
RESEARCH 1987 4100
RESEARCH CLERK 1900
RESEARCH CLERK 1980 800
RESEARCH CLERK 1987 1100
RESEARCH ANALYST 6000
RESEARCH ANALYST 1981 3000
RESEARCH ANALYST 1987 3000
RESEARCH MANAGER 2975
RESEARCH MANAGER 1981 2975
ACCOUNTING 8750
ACCOUNTING 1981 7450
ACCOUNTING 1982 1300
ACCOUNTING CLERK 1300
ACCOUNTING CLERK 1982 1300
ACCOUNTING MANAGER 2450
ACCOUNTING MANAGER 1981 2450
ACCOUNTING PRESIDENT 5000
ACCOUNTING PRESIDENT 1981 5000
29 rows selected.