學習自《劍破冰山 Oracle開發藝術》第五章 報表開發之擴展GROUP BY
對于簡單group by陳述句很難對復雜維度進行分析，難以達到實際生產的復雜報表需求，group by的擴展特性就需要了，union陳述句也可以達到需求但是sql復雜且效率低
1 rollup多維匯總
rollup，分組先進行常規分組，然后在此基礎上，通過將列從右向左移動，然后進行更高一級的小計，最后合計，注意rollup分組和列的順序相關
指定n列，有n+1種分組方式
部分rollup可以剔除某些不需要的小計和合計
例子
[oracle@localhost ~]$ sqlplus scott/tiger;
SQL*Plus: Release 11.2.0.4.0 Production on Mon Mar 23 10:31:24 2020
Copyright (c) 1982, 2013, Oracle. All rights reserved.
Connected to:
Oracle Database 11g Enterprise Edition Release 11.2.0.4.0 - 64bit Production
With the Partitioning, OLAP, Data Mining and Real Application Testing options
10:31:24 SCOTT@edw> set autotrace on
10:31:30 SCOTT@edw> 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
13 rows selected.
Elapsed: 00:00:00.01
Execution Plan
----------------------------------------------------------
Plan hash value: 3067950682
-----------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
-----------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 14 | 392 | 7 (29)| 00:00:01 |
| 1 | SORT GROUP BY ROLLUP | | 14 | 392 | 7 (29)| 00:00:01 |
| 2 | MERGE JOIN | | 14 | 392 | 6 (17)| 00:00:01 |
| 3 | TABLE ACCESS BY INDEX ROWID| DEPT | 4 | 52 | 2 (0)| 00:00:01 |
| 4 | INDEX FULL SCAN | PK_DEPT | 4 | | 1 (0)| 00:00:01 |
|* 5 | SORT JOIN | | 14 | 210 | 4 (25)| 00:00:01 |
| 6 | TABLE ACCESS FULL | EMP | 14 | 210 | 3 (0)| 00:00:01 |
-----------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
5 - access("A"."DEPTNO"="B"."DEPTNO")
filter("A"."DEPTNO"="B"."DEPTNO")
Statistics
----------------------------------------------------------
0 recursive calls
0 db block gets
8 consistent gets
0 physical reads
0 redo size
913 bytes sent via SQL*Net to client
524 bytes received via SQL*Net from client
2 SQL*Net roundtrips to/from client
2 sorts (memory)
0 sorts (disk)
13 rows processed
10:31:34 SCOTT@edw>
可以看出僅僅dept和emp表均僅掃描一次，而如果是union來寫就會多次重復掃描，效率低
通過執行計劃看到有個隱藏操作SORT GROUP BY ROLLUP ,顯示結果有序，一般還是要顯示排序的，默認的排序不一定符合業務需求
rollup分組具有方向性
如果使用hint:expand_gset_to_union,則優化器會將rollup轉換為對應的union all操作，其他的grouping sets、cube也可以
部分rollup分組，將不需要小計的列從rollup拿出到group by中即可，當然合計也沒有了
例子
10:31:34 SCOTT@edw> set autotrace off 10:43:49 SCOTT@edw> SELECT to_char(b.hiredate,'yyyy') hire_year,a.dname,b.job,SUM(b.sal) sum_sal FROM dept a,emp b WHERE a.deptno=b.deptno GROUP BY to_char(b.hiredate,'yyyy'),a.dname,ROLLUP(b.job); HIRE DNAME JOB SUM_SAL ---- -------------- --------- ---------- 1980 RESEARCH CLERK 800 1980 RESEARCH 800 1981 SALES CLERK 950 1981 SALES MANAGER 2850 1981 SALES SALESMAN 5600 1981 SALES 9400 1981 RESEARCH ANALYST 3000 1981 RESEARCH MANAGER 2975 1981 RESEARCH 5975 1981 ACCOUNTING MANAGER 2450 1981 ACCOUNTING PRESIDENT 5000 1981 ACCOUNTING 7450 1982 ACCOUNTING CLERK 1300 1982 ACCOUNTING 1300 1987 RESEARCH CLERK 1100 1987 RESEARCH ANALYST 3000 1987 RESEARCH 4100 17 rows selected. Elapsed: 00:00:00.01 10:43:53 SCOTT@edw>
2 cube交叉報表
cube分組可以實作更精細復雜的統計，對不同維度的所以可能進行分析，生成交叉報表，cube分組，是從n列中先進行合計，即一個列不取，然后小計，即取1列到n-1列，最后n列全取，即標準分組
因為包含所有可能的組合，所以結果與列的順序無關，列順序僅僅影響默認的隱藏排序而已，如果用了顯示排序則無所謂了
cube分組增加一列，可能結果是指數級的增長，分組種類2的n次方
語法類似，例子
11:02:40 SCOTT@edw> set autotrace on
11:02:48 SCOTT@edw> 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
18 rows selected.
Elapsed: 00:00:00.01
Execution Plan
----------------------------------------------------------
Plan hash value: 2382666110
-------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
-------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 14 | 392 | 7 (29)| 00:00:01 |
| 1 | SORT GROUP BY | | 14 | 392 | 7 (29)| 00:00:01 |
| 2 | GENERATE CUBE | | 14 | 392 | 7 (29)| 00:00:01 |
| 3 | SORT GROUP BY | | 14 | 392 | 7 (29)| 00:00:01 |
| 4 | MERGE JOIN | | 14 | 392 | 6 (17)| 00:00:01 |
| 5 | TABLE ACCESS BY INDEX ROWID| DEPT | 4 | 52 | 2 (0)| 00:00:01 |
| 6 | INDEX FULL SCAN | PK_DEPT | 4 | | 1 (0)| 00:00:01 |
|* 7 | SORT JOIN | | 14 | 210 | 4 (25)| 00:00:01 |
| 8 | TABLE ACCESS FULL | EMP | 14 | 210 | 3 (0)| 00:00:01 |
-------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
7 - access("A"."DEPTNO"="B"."DEPTNO")
filter("A"."DEPTNO"="B"."DEPTNO")
Statistics
----------------------------------------------------------
1 recursive calls
0 db block gets
8 consistent gets
0 physical reads
0 redo size
1175 bytes sent via SQL*Net to client
535 bytes received via SQL*Net from client
3 SQL*Net roundtrips to/from client
3 sorts (memory)
0 sorts (disk)
18 rows processed
11:02:52 SCOTT@edw>
可以看執行計劃，結果也是有序的
部分cube分組，例子
11:06:24 SCOTT@edw> SELECT a.dname,b.job,SUM(b.sal) sum_sal FROM dept a,emp b WHERE a.deptno=b.deptno GROUP BY a.dname,CUBE(b.job); DNAME JOB SUM_SAL -------------- --------- ---------- 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 12 rows selected. Elapsed: 00:00:00.00 11:06:26 SCOTT@edw>
3 grouping sets實作小計
rollup和cube會產生各種標準分組、小計、合計，grouping sets則只關注指定維度的小計，n列的結果也是n種
如grouping sets(a,b,c)就是group by a、group by b和group by c的結果union all
例子
11:06:26 SCOTT@edw> set autotrace on
11:12:33 SCOTT@edw> SELECT to_char(b.hiredate,'yyyy') hire_year,a.dname,b.job,SUM(b.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
---- -------------- --------- ----------
CLERK 4150
SALESMAN 5600
PRESIDENT 5000
MANAGER 8275
ANALYST 6000
ACCOUNTING 8750
RESEARCH 10875
SALES 9400
1987 4100
1980 800
1982 1300
1981 22825
12 rows selected.
Elapsed: 00:00:00.01
Execution Plan
----------------------------------------------------------
Plan hash value: 2825031421
------------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
------------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 14 | 448 | 17 (24)| 00:00:01 |
| 1 | TEMP TABLE TRANSFORMATION | | | | | |
| 2 | LOAD AS SELECT | SYS_TEMP_0FD9D660D_29B9BB | | | | |
| 3 | MERGE JOIN | | 14 | 504 | 6 (17)| 00:00:01 |
| 4 | TABLE ACCESS BY INDEX ROWID| DEPT | 4 | 52 | 2 (0)| 00:00:01 |
| 5 | INDEX FULL SCAN | PK_DEPT | 4 | | 1 (0)| 00:00:01 |
|* 6 | SORT JOIN | | 14 | 322 | 4 (25)| 00:00:01 |
| 7 | TABLE ACCESS FULL | EMP | 14 | 322 | 3 (0)| 00:00:01 |
| 8 | LOAD AS SELECT | SYS_TEMP_0FD9D660E_29B9BB | | | | |
| 9 | HASH GROUP BY | | 5 | 60 | 3 (34)| 00:00:01 |
| 10 | TABLE ACCESS FULL | SYS_TEMP_0FD9D660D_29B9BB | 14 | 168 | 2 (0)| 00:00:01 |
| 11 | LOAD AS SELECT | SYS_TEMP_0FD9D660E_29B9BB | | | | |
| 12 | HASH GROUP BY | | 4 | 56 | 3 (34)| 00:00:01 |
| 13 | TABLE ACCESS FULL | SYS_TEMP_0FD9D660D_29B9BB | 14 | 196 | 2 (0)| 00:00:01 |
| 14 | LOAD AS SELECT | SYS_TEMP_0FD9D660E_29B9BB | | | | |
| 15 | HASH GROUP BY | | 1 | 8 | 3 (34)| 00:00:01 |
| 16 | TABLE ACCESS FULL | SYS_TEMP_0FD9D660D_29B9BB | 14 | 112 | 2 (0)| 00:00:01 |
| 17 | VIEW | | 5 | 160 | 2 (0)| 00:00:01 |
| 18 | TABLE ACCESS FULL | SYS_TEMP_0FD9D660E_29B9BB | 5 | 60 | 2 (0)| 00:00:01 |
------------------------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
6 - access("SYS_TBL_$2$"."DEPTNO"="SYS_TBL_$1$"."DEPTNO")
filter("SYS_TBL_$2$"."DEPTNO"="SYS_TBL_$1$"."DEPTNO")
Statistics
----------------------------------------------------------
23 recursive calls
33 db block gets
39 consistent gets
4 physical reads
2172 redo size
962 bytes sent via SQL*Net to client
524 bytes received via SQL*Net from client
2 SQL*Net roundtrips to/from client
1 sorts (memory)
0 sorts (disk)
12 rows processed
11:12:36 SCOTT@edw>
執行計劃可以看出，沒有默認排序了，無序，和列的順序也無關
同理部分grouping sets分組，例子
11:12:36 SCOTT@edw> set autotrace off 11:17:03 SCOTT@edw> SELECT a.dname,to_char(b.hiredate,'yyyy') hire_year,b.job,SUM(b.sal) sum_sal FROM dept a,emp b WHERE a.deptno=b.deptno GROUP BY a.dname,GROUPING SETS(to_char(b.hiredate,'yyyy'),b.job); DNAME HIRE JOB SUM_SAL -------------- ---- --------- ---------- SALES MANAGER 2850 SALES CLERK 950 ACCOUNTING MANAGER 2450 ACCOUNTING PRESIDENT 5000 ACCOUNTING CLERK 1300 RESEARCH MANAGER 2975 SALES SALESMAN 5600 RESEARCH ANALYST 6000 RESEARCH CLERK 1900 RESEARCH 1981 5975 SALES 1981 9400 RESEARCH 1987 4100 ACCOUNTING 1981 7450 ACCOUNTING 1982 1300 RESEARCH 1980 800 15 rows selected. Elapsed: 00:00:00.01 11:17:05 SCOTT@edw>
注意此時的含義有較大的變化
cube、rollup作為grouping sets的引數
grouping sets只提供單列分組，沒有合計功能，如果需要提供合計，則可以將rollup或cube作為引數，例子
11:23:59 SCOTT@edw> SELECT a.dname,b.job,SUM(b.sal) sum_sal FROM dept a,emp b WHERE a.deptno=b.deptno GROUP BY GROUPING sets(rollup(a.dname),ROLLUP(b.job));
DNAME JOB SUM_SAL
-------------- --------- ----------
CLERK 4150
SALESMAN 5600
PRESIDENT 5000
MANAGER 8275
ANALYST 6000
ACCOUNTING 8750
RESEARCH 10875
SALES 9400
29025
29025
10 rows selected.
Elapsed: 00:00:00.02
11:24:02 SCOTT@edw>
問題是產生了兩個合計行，因為rollup或cube作為grouping sets引數，相當于每個rollup或cube操作的union all，等價于
這就很好理解功能了
對于重復合計，使用distinct剔除即可，另外后面還有特殊的函式可以使用，group_id可以用來剔除重復分組(和distinct功能是不一樣的)
rollup和cube作為引數也可以混用，而且也可以使用其它擴展功能，如部分分組、復合列分組、連接分組等
rollup和cube不能接受grouping sets作為引數，rollup和cube互相作為引數也不行
4 組合列分組、連接分組、重置列分組
組合列分組、連接分組在復雜報表中用處很大，組合列分組用于剔除不必要的小計保留合計，連接分組按每個分組的笛卡爾積進行操作，分組更多更細，對于常規分組滿足不了的需求可以考慮
組合列即將多個列當做整體對待，下列對比表可以清晰展示不同之處
連接分組更強大，允許group by后出現多個rollup、cube和grouping sets操作，這樣分組級別更多，報表更精細，實作很復雜的需求
實際上不管是同型別的連接分組還是不通型別的連接分組之間，最后的分組級別種類都是每個擴展分組級別種類的乘積，分組級別是笛卡爾積，比如rollup(a,b),rollup(c)，最終3*2=6中分組級別
重復列分組也就是group by中允許重復列，比如group by rollup(a,(a,b))、group by a,rollup(a,b)
組合列分組
例子
14:48:13 SCOTT@edw> SELECT a.dname,to_char(b.hiredate,'yyyy') hire_year,b.job,SUM(b.sal) sum_sal FROM dept a,emp b WHERE a.deptno=b.deptno GROUP BY rollup(a.dname,(to_char(b.hiredate,'yyyy'),b.job));
DNAME HIRE JOB SUM_SAL
-------------- ---- --------- ----------
SALES 1981 CLERK 950
SALES 1981 MANAGER 2850
SALES 1981 SALESMAN 5600
SALES 9400
RESEARCH 1980 CLERK 800
RESEARCH 1981 ANALYST 3000
RESEARCH 1981 MANAGER 2975
RESEARCH 1987 CLERK 1100
RESEARCH 1987 ANALYST 3000
RESEARCH 10875
ACCOUNTING 1981 MANAGER 2450
ACCOUNTING 1981 PRESIDENT 5000
ACCOUNTING 1982 CLERK 1300
ACCOUNTING 8750
29025
15 rows selected.
Elapsed: 00:00:00.00
14:48:16 SCOTT@edw>
組合列分組可以實作部分rollup和部分cube分組類似效果并且加上合計
但是這個也比較麻煩，對于需要cube、rollup合計并剔除部分小計的需求用grouping_id或grouping函式
cube和rollup均可以轉換為對應的grouping sets
當然反向也可以，不過意義不大
連接分組
例子
14:48:16 SCOTT@edw> SELECT a.dname,to_char(b.hiredate,'yyyy') hire_year,b.job,SUM(b.sal) sum_sal FROM dept a,emp b WHERE a.deptno=b.deptno GROUP BY rollup(a.dname,b.job),ROLLUP(to_char(b.hiredate,'yyyy'));
DNAME HIRE 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
RESEARCH 1980 CLERK 800
RESEARCH 1980 800
1980 800
SALES 1981 CLERK 950
SALES 1981 MANAGER 2850
SALES 1981 SALESMAN 5600
SALES 1981 9400
RESEARCH 1981 ANALYST 3000
RESEARCH 1981 MANAGER 2975
RESEARCH 1981 5975
ACCOUNTING 1981 MANAGER 2450
ACCOUNTING 1981 PRESIDENT 5000
ACCOUNTING 1981 7450
1981 22825
ACCOUNTING 1982 CLERK 1300
ACCOUNTING 1982 1300
1982 1300
RESEARCH 1987 CLERK 1100
RESEARCH 1987 ANALYST 3000
RESEARCH 1987 4100
1987 4100
34 rows selected.
Elapsed: 00:00:00.01
14:57:57 SCOTT@edw>
相當于兩個rollup的笛卡爾積
理解了之后，利用連接分組，cube可以用rollup轉換，如cube(a,b,c)等于rollup(a),rollup(b),rollup(c)，但是對于rollup和grouping sets轉換為cube一般沒啥用
連接分組一般是同型別的，不通型別的連接分組一般不常用
重復列分組
例子
14:57:57 SCOTT@edw> SELECT a.dname,b.job,SUM(b.sal) sum_sal FROM dept a,emp b WHERE a.deptno=b.deptno GROUP BY a.dname,ROLLUP(a.dname,b.job); DNAME JOB SUM_SAL -------------- --------- ---------- SALES CLERK 950 SALES MANAGER 2850 SALES SALESMAN 5600 RESEARCH CLERK 1900 RESEARCH ANALYST 6000 RESEARCH MANAGER 2975 ACCOUNTING CLERK 1300 ACCOUNTING MANAGER 2450 ACCOUNTING PRESIDENT 5000 SALES 9400 RESEARCH 10875 ACCOUNTING 8750 SALES 9400 RESEARCH 10875 ACCOUNTING 8750 15 rows selected. Elapsed: 00:00:00.00 15:07:14 SCOTT@edw>
沒啥意義的例子，只不過說明語法允許
5 三個擴展分組函式:grouping、grouping_id、group_id
三個擴展分組函式:grouping、grouping_id、group_id在生成有意義的報表、結果進行過濾、排序中有很重要的作用，常用于復雜的報表查詢
注意grouping和grouping_id函式的引數不能是組合列
grouping函式用于制作有意義的報表
grouping_id函式對結果過濾以及排序
group_id函式剔除重復行
grouping函式
在擴展group by子句來說，null表示小計或者合計，但是如果資料中本來就有null值呢？grouping函式專門處理擴展group by分組中null問題：
它只接受一個引數，且引數來自rollup、cube、grouping sets中的列，當然也可以在group by而不在上述3個子句的列，不過結果肯定是0，沒有意義
grouping函式對于小計或合計的列回傳1，否則回傳0，用于區別是否原始資料中含null，常與decode一起使用，當然也可以確定分組級別從而過濾一些行，不過會很煩，一般用grouping_id替代
例子
15:34:01 SCOTT@edw> SELECT decode(GROUPING(a.dname),1,'全部部門',a.dname) dname,decode(grouping(b.mgr),1,'全部老板',b.mgr) mgr,SUM(b.sal) sum_sal FROM dept a,emp b WHERE a.deptno=b.deptno GROUP BY ROLLUP(a.dname,b.mgr); DNAME MGR SUM_SAL -------------- ---------------------------------------- ---------- SALES 7698 6550 SALES 7839 2850 SALES 全部老板 9400 RESEARCH 7566 6000 RESEARCH 7788 1100 RESEARCH 7839 2975 RESEARCH 7902 800 RESEARCH 全部老板 10875 ACCOUNTING 5000 ACCOUNTING 7782 1300 ACCOUNTING 7839 2450 ACCOUNTING 全部老板 8750 全部部門 全部老板 29025 13 rows selected. Elapsed: 00:00:00.01 15:34:12 SCOTT@edw>
grouping_id函式
用于過濾分組級別和排序結果
可以接受多個引數，來自rollup、cube、grouping sets中的列，按列從左往右順序計算，是分組列則0，是小計或合計列為1，然后組合成為一個二進制數字叫做位向量，位向量轉化為10進制即最后的結果，代表分組級別，如cube(a,b),那么grouping_id(a,b)代表的如下
grouping_id的好處是可以對多列進行計算得到分組級別
例子
15:46:26 SCOTT@edw> SELECT a.dname,b.mgr,b.job,SUM(b.sal) sum_sal FROM dept a,emp b WHERE a.deptno=b.deptno GROUP BY ROLLUP(a.dname,b.mgr,b.job) HAVING grouping_id(a.dname,b.mgr,b.job) IN (0,7);
DNAME MGR JOB SUM_SAL
-------------- ---------- --------- ----------
SALES 7698 CLERK 950
SALES 7698 SALESMAN 5600
SALES 7839 MANAGER 2850
RESEARCH 7566 ANALYST 6000
RESEARCH 7788 CLERK 1100
RESEARCH 7839 MANAGER 2975
RESEARCH 7902 CLERK 800
ACCOUNTING PRESIDENT 5000
ACCOUNTING 7782 CLERK 1300
ACCOUNTING 7839 MANAGER 2450
29025
11 rows selected.
Elapsed: 00:00:00.00
15:46:29 SCOTT@edw>
group_id函式
group_id無引數，因為擴展group by子句允許多種復雜分組操作，有時候為了實作復雜報表，可能出現重復統計，而group_id函式可以區分重復分組結果，第一次出現為0，以后每次出現增1，group_id在select中出現沒啥意義，通常用于having子句剔除重復統計
例子
15:46:29 SCOTT@edw> SELECT a.dname,b.job,SUM(b.sal) sum_sal,group_id() gi FROM dept a,emp b WHERE a.deptno=b.deptno GROUP BY GROUPING SETS(ROLLUP(a.dname),ROLLUP(b.job)) HAVING group_id()=0;
DNAME JOB SUM_SAL GI
-------------- --------- ---------- ----------
CLERK 4150 0
SALESMAN 5600 0
PRESIDENT 5000 0
MANAGER 8275 0
ANALYST 6000 0
ACCOUNTING 8750 0
RESEARCH 10875 0
SALES 9400 0
29025 0
9 rows selected.
Elapsed: 00:00:00.01
15:55:55 SCOTT@edw>
轉載請註明出處，本文鏈接：https://www.uj5u.com/shujuku/7304.html
標籤：Oracle