Oracle分组函数之CUBE魅力

Oracle的CUBE与ROLLUP功能很相似，也是在数据统计分析领域的一把好手。

关于ROLLUP的查询统计功能请参考文章《Oracle分组函数之ROLLUP魅力》(http://www.linuxidc.com/Linux/2012-08/67357.htm）。

1.先看一下ROLLUP的数据统计效果

1）创建测试表group_test

SECOOLER@ora11g> create table group_test (group_id int, job varchar2(10), name varchar2(10), salary int);

Table created.

2）初始化数据

insert into group_test values (10,'Coding',    'Bruce',1000);

insert into group_test values (10,'Programmer','Clair',1000);

insert into group_test values (10,'Architect', 'Gideon',1000);

insert into group_test values (10,'Director',  'Hill',1000);

insert into group_test values (20,'Coding',    'Jason',2000);

insert into group_test values (20,'Programmer','Joey',2000);

insert into group_test values (20,'Architect', 'Martin',2000);

insert into group_test values (20,'Director',  'Michael',2000);

insert into group_test values (30,'Coding',    'Rebecca',3000);

insert into group_test values (30,'Programmer','Rex',3000);

insert into group_test values (30,'Architect', 'Richard',3000);

insert into group_test values (30,'Director',  'Sabrina',3000);

insert into group_test values (40,'Coding',    'Samuel',4000);

insert into group_test values (40,'Programmer','Susy',4000);

insert into group_test values (40,'Architect', 'Tina',4000);

insert into group_test values (40,'Director',  'Wendy',4000);

commit;

3）初始化之后的数据情况如下：

SECOOLER@ora11g> set pages 100

SECOOLER@ora11g> select * from group_test;

GROUP_ID JOB        NAME           SALARY

---------- ---------- ---------- ----------

        10 Coding     Bruce            1000

        10 Programmer Clair            1000

        10 Architect  Gideon           1000

        10 Director   Hill             1000

        20 Coding     Jason            2000

        20 Programmer Joey             2000

        20 Architect  Martin           2000

        20 Director   Michael          2000

        30 Coding     Rebecca          3000

        30 Programmer Rex              3000

        30 Architect  Richard          3000

        30 Director   Sabrina          3000

        40 Coding     Samuel           4000

        40 Programmer Susy             4000

        40 Architect  Tina             4000

        40 Director   Wendy            4000

16 rows selected.

4）ROLLUP的数据统计效果

sec@ora10g> select group_id,job,grouping(GROUP_ID),grouping(JOB),sum(salary) from group_test group by rollup(group_id, job);

GROUP_ID JOB        GROUPING(GROUP_ID) GROUPING(JOB) SUM(SALARY)

---------- ---------- ------------------ ------------- -----------

        10 Coding                      0             0        1000

        10 Director                    0             0        1000

        10 Architect                   0             0        1000

        10 Programmer                  0             0        1000

        10                             0             1        4000

        20 Coding                      0             0        2000

        20 Director                    0             0        2000

        20 Architect                   0             0        2000

        20 Programmer                  0             0        2000

        20                             0             1        8000

        30 Coding                      0             0        3000

        30 Director                    0             0        3000

        30 Architect                   0             0        3000

        30 Programmer                  0             0        3000

        30                             0             1       12000

        40 Coding                      0             0        4000

        40 Director                    0             0        4000

        40 Architect                   0             0        4000

        40 Programmer                  0             0        4000

        40                             0             1       16000

                                       1             1       40000

21 rows selected.

2.进一步体验CUBE的魅力

sec@ora10g> select group_id,job,grouping(GROUP_ID),grouping(JOB),sum(salary) from group_test group by cube(group_id, job) order by 1;

GROUP_ID JOB        GROUPING(GROUP_ID) GROUPING(JOB) SUM(SALARY)

---------- ---------- ------------------ ------------- -----------

        10 Architect                   0             0        1000

        10 Coding                      0             0        1000

        10 Director                    0             0        1000

        10 Programmer                  0             0        1000

        10                             0             1        4000

        20 Architect                   0             0        2000

        20 Coding                      0             0        2000

        20 Director                    0             0        2000

        20 Programmer                  0             0        2000

        20                             0             1        8000

        30 Architect                   0             0        3000

        30 Coding                      0             0        3000

        30 Director                    0             0        3000

        30 Programmer                  0             0        3000

        30                             0             1       12000

        40 Architect                   0             0        4000

        40 Coding                      0             0        4000

        40 Director                    0             0        4000

        40 Programmer                  0             0        4000

        40                             0             1       16000

           Architect                   1             0       10000

           Coding                      1             0       10000

           Director                    1             0       10000

           Programmer                  1             0       10000

                                       1             1       40000

25 rows selected.

解释如上结果中GROUPING函数返回值“0”和“1”的含义。

  如果显示“1”表示CUBE函数对应的列（例如JOB字段）是由于CUBE函数所产生的空值对应的信息，即对此列进行汇总计算后的结果。

  如果显示“0”表示此行对应的这列参未与ROLLUP函数分组汇总活动。

  如果还是没有理解清楚，请参见Oracle官方文档中的描述内容：“Using a single column as its argument,GROUPINGreturns 1 when it encounters aNULLvalue created by aROLLUPorCUBEoperation. That is, if theNULLindicates the row is a subtotal,GROUPINGreturns a 1. Any other type of value, including
a storedNULL, returns a 0.”

3.仔细观察一下，CUBE与ROLLUP之间的细微差别

rollup(a,b)   统计列包含：(a,b)、(a)、()

rollup(a,b,c) 统计列包含：(a,b,c)、(a,b)、(a)、()

……以此类推ing……

cube(a,b)     统计列包含：(a,b)、(a)、(b)、()

cube(a,b,c)   统计列包含：(a,b,c)、(a,b)、(a,c)、(b,c)、(a)、(b)、(c)、()

……以此类推ing……

So，上面例子中CUBE的结果比ROLLUP多了下面关于第一列GROUP_ID的统计信息：

           Architect                   1             0       10000

           Coding                      1             0       10000

           Director                    1             0       10000

4.小结

  CUBE在ROLLUP的基础上进一步从各种维度上给出细化的统计汇总结果。

  CUBE与GROUP BY的关系可以参考Oracle官方文档中的例子，链接如下：，链接如下：《CUBE Extension to GROUP BY》http://docs.oracle.com/cd/E11882_01/server.112/e25554/aggreg.htm#DWHSG8614