本篇文章給大家分享的是有關怎樣理解Oracle分組函數中的CUBE，小編覺得挺實用的，因此分享給大家學習，希望大家閱讀完這篇文章后可以有所收獲，話不多說，跟著小編一起來看看吧。
Oracle的CUBE與ROLLUP功能很相似，也是在數據統計分析領域的一把好手。
1.先看一下ROLLUP的數據統計效果
1）創建測試表group_test
SECOOLER@ora11g> create table group_test (group_id int, job varchar2(10), name varchar2(10), salary int);
Table created.
2）初始化數據
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）初始化之后的數據情況如下：
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的數據統計效果
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.進一步體驗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.
解釋如上結果中GROUPING函數返回值“0”和“1”的含義。
如果顯示“1”表示CUBE函數對應的列（例如JOB字段）是由于CUBE函數所產生的空值對應的信息，即對此列進行匯總計算后的結果。
如果顯示“0”表示此行對應的這列參未與ROLLUP函數分組匯總活動。
如果還是沒有理解清楚，請參見Oracle官方文檔中的描述內容：“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.仔細觀察一下，CUBE與ROLLUP之間的細微差別
rollup(a,b) 統計列包含：(a,b)、(a)、()
rollup(a,b,c) 統計列包含：(a,b,c)、(a,b)、(a)、()
……以此類推ing……
cube(a,b) 統計列包含：(a,b)、(a)、(b)、()
cube(a,b,c) 統計列包含：(a,b,c)、(a,b)、(a,c)、(b,c)、(a)、(b)、(c)、()
……以此類推ing……
So，上面例子中CUBE的結果比ROLLUP多了下面關于第一列GROUP_ID的統計信息：
Architect 1 0 10000
Coding 1 0 10000
Director 1 0 10000
4.小結
CUBE在ROLLUP的基礎上進一步從各種維度上給出細化的統計匯總結果。
以上就是怎樣理解Oracle分組函數中的CUBE，小編相信有部分知識點可能是我們日常工作會見到或用到的。希望你能通過這篇文章學到更多知識。更多詳情敬請關注億速云行業資訊頻道。
免責聲明：本站發布的內容（圖片、視頻和文字）以原創、轉載和分享為主，文章觀點不代表本網站立場，如果涉及侵權請聯系站長郵箱：is@yisu.com進行舉報，并提供相關證據，一經查實，將立刻刪除涉嫌侵權內容。
