關聯查詢時使用樹狀查詢要小心
很多人為了方便經常將幾個表的關聯查詢和樹狀查詢合在一起，這樣做很可能產生一些並不需要的記錄。
如果在查詢的時候兩張或兩張以上的表進行關聯查詢，同時需要對其中一張執行CONNECT BY操作，那麼建議要不然將CONNECT BY放到查詢最裡層，要不然將CONNECT BY放到查詢最外層，而不要將CONNECT BY與多表連線放在一起。
透過一個例子來說明這個問題吧：
SQL> CREATE TABLE T (ID NUMBER, FID NUMBER, NAME VARCHAR2(30));
表已建立。
SQL> ALTER TABLE T ADD CONSTRAINT PK_T PRIMARY KEY (ID);
表已更改。
SQL> INSERT INTO T VALUES (1, 0, 'TABLE');
已建立 1 行。
SQL> INSERT INTO T VALUES (2, 0, 'INDEX');
已建立 1 行。
SQL> INSERT INTO T SELECT 10000 + ROWNUM, 1, TABLE_NAME FROM DBA_TABLES;
已建立1624行。
SQL> INSERT INTO T SELECT 20000 + ROWNUM, 2, INDEX_NAME FROM DBA_INDEXES;
已建立2401行。
SQL> CREATE INDEX IND_T_FID ON T(FID);
索引已建立。
SQL> CREATE TABLE T1 (ID NUMBER, USERNAME VARCHAR2(30), TID NUMBER);
表已建立。
SQL> ALTER TABLE T1 ADD CONSTRAINT PK_T1 PRIMARY KEY (ID);
表已更改。
SQL> INSERT INTO T1 VALUES (1, 'YANGTK', 1);
已建立 1 行。
SQL> INSERT INTO T1 VALUES (2, 'YANGTK', 10005);
已建立 1 行。
SQL> INSERT INTO T1 VALUES (3, 'YANGTK', 10006);
已建立 1 行。
SQL> INSERT INTO T1 VALUES (4, 'TEST', 1);
已建立 1 行。
SQL> CREATE INDEX IND_T1_NAME ON T1(USERNAME);
索引已建立。
構造一個很簡單的樹型結構的表，並構造一張關聯表，下面執行一個簡單的連線查詢：
SQL> SELECT T.ID, FID, NAME, USERNAME
2 FROM T, T1
3 WHERE T.ID = T1.TID
4 AND T1.USERNAME = 'YANGTK';
ID FID NAME USERNAME
---------- ---------- ------------------------------ -------------------
1 0 TABLE YANGTK
10005 1 FILE$ YANGTK
10006 1 UET$ YANGTK
如果在這個查詢的基礎上加上一個樹型查詢，START WITH FID = 0，看看執行的結果：
SQL> SELECT T.ID, FID, NAME, USERNAME
2 FROM T, T1
3 WHERE T.ID = T1.TID
4 AND T1.USERNAME = 'YANGTK'
5 START WITH FID = 0
6 CONNECT BY PRIOR T.ID = FID;
ID FID NAME USERNAME
---------- ---------- ------------------------------ -----------------
1 0 TABLE YANGTK
10005 1 FILE$ YANGTK
10006 1 UET$ YANGTK
10005 1 FILE$ YANGTK
10006 1 UET$ YANGTK
現在結果變成了5條，為什麼不加樹型查詢得到3條記錄，而新增了樹型查詢結果變成了5條呢。
觀察一下執行計劃：
SQL> SET AUTOT ON EXP
SQL> SELECT T.ID, FID, NAME, USERNAME
2 FROM T, T1
3 WHERE T.ID = T1.TID
4 AND T1.USERNAME = 'YANGTK'
5 START WITH FID = 0
6 CONNECT BY PRIOR T.ID = FID;
ID FID NAME USERNAME
---------- ---------- ------------------------------ ------------------------------
1 0 TABLE YANGTK
10005 1 FILE$ YANGTK
10006 1 UET$ YANGTK
10005 1 FILE$ YANGTK
10006 1 UET$ YANGTK
執行計劃
----------------------------------------------------------
Plan hash value: 1198160839
-----------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
-----------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 4 | 292 | 3 (0)| 00:00:01 |
|* 1 | FILTER | | | | | |
|* 2 | CONNECT BY WITH FILTERING | | | | | |
|* 3 | FILTER | | | | | |
| 4 | COUNT | | | | | |
| 5 | NESTED LOOPS | | 4 | 292 | 3 (0)| 00:00:01 |
| 6 | TABLE ACCESS FULL | T1 | 4 | 120 | 2 (0)| 00:00:01 |
| 7 | TABLE ACCESS BY INDEX ROWID| T | 1 | 43 | 1 (0)| 00:00:01 |
|* 8 | INDEX UNIQUE SCAN | PK_T | 1 | | 1 (0)| 00:00:01 |
|* 9 | HASH JOIN | | | | | |
| 10 | CONNECT BY PUMP | | | | | |
| 11 | COUNT | | | | | |
| 12 | NESTED LOOPS | | 4 | 292 | 3 (0)| 00:00:01 |
| 13 | TABLE ACCESS FULL | T1 | 4 | 120 | 2 (0)| 00:00:01 |
| 14 | TABLE ACCESS BY INDEX ROWID| T | 1 | 43 | 1 (0)| 00:00:01 |
|* 15 | INDEX UNIQUE SCAN | PK_T | 1 | | 1 (0)| 00:00:01 |
| 16 | COUNT | | | | | |
| 17 | NESTED LOOPS | | 4 | 292 | 3 (0)| 00:00:01 |
| 18 | TABLE ACCESS FULL | T1 | 4 | 120 | 2 (0)| 00:00:01 |
| 19 | TABLE ACCESS BY INDEX ROWID | T | 1 | 43 | 1 (0)| 00:00:01 |
|* 20 | INDEX UNIQUE SCAN | PK_T | 1 | | 1 (0)| 00:00:01 |
-----------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - filter("T1"."USERNAME"='YANGTK')
2 - filter("FID"=0)
3 - filter("FID"=0)
8 - access("T"."ID"="T1"."TID")
9 - access("FID"=NULL)
15 - access("T"."ID"="T1"."TID")
20 - access("T"."ID"="T1"."TID")
Note
-----
- dynamic sampling used for this statement
Oracle先進行的連線，然後是CONNECT BY，最後使用filter("T1"."USERNAME"='YANGTK')來進行過濾。
這就是造成資料重複的原因。
實際上這個SQL相當於先執行了一個：
SQL> SELECT T.ID, FID, NAME, USERNAME
2 FROM T, T1
3 WHERE T.ID = T1.TID
4 START WITH FID = 0
5 CONNECT BY PRIOR T.ID = FID;
ID FID NAME USERNAME
---------- ---------- ------------------------------ ------------------------------
1 0 TABLE YANGTK
10005 1 FILE$ YANGTK
10006 1 UET$ YANGTK
1 0 TABLE TEST
10005 1 FILE$ YANGTK
10006 1 UET$ YANGTK
已選擇6行。
執行計劃
----------------------------------------------------------
Plan hash value: 2039799266
----------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
----------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 4 | 292 | 3 (0)| 00:00:01 |
|* 1 | CONNECT BY WITH FILTERING | | | | | |
|* 2 | FILTER | | | | | |
| 3 | COUNT | | | | | |
| 4 | NESTED LOOPS | | 4 | 292 | 3 (0)| 00:00:01 |
| 5 | TABLE ACCESS FULL | T1 | 4 | 120 | 2 (0)| 00:00:01 |
| 6 | TABLE ACCESS BY INDEX ROWID| T | 1 | 43 | 1 (0)| 00:00:01 |
|* 7 | INDEX UNIQUE SCAN | PK_T | 1 | | 1 (0)| 00:00:01 |
|* 8 | HASH JOIN | | | | | |
| 9 | CONNECT BY PUMP | | | | | |
| 10 | COUNT | | | | | |
| 11 | NESTED LOOPS | | 4 | 292 | 3 (0)| 00:00:01 |
| 12 | TABLE ACCESS FULL | T1 | 4 | 120 | 2 (0)| 00:00:01 |
| 13 | TABLE ACCESS BY INDEX ROWID| T | 1 | 43 | 1 (0)| 00:00:01 |
|* 14 | INDEX UNIQUE SCAN | PK_T | 1 | | 1 (0)| 00:00:01 |
| 15 | COUNT | | | | | |
| 16 | NESTED LOOPS | | 4 | 292 | 3 (0)| 00:00:01 |
| 17 | TABLE ACCESS FULL | T1 | 4 | 120 | 2 (0)| 00:00:01 |
| 18 | TABLE ACCESS BY INDEX ROWID | T | 1 | 43 | 1 (0)| 00:00:01 |
|* 19 | INDEX UNIQUE SCAN | PK_T | 1 | | 1 (0)| 00:00:01 |
----------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - filter("FID"=0)
2 - filter("FID"=0)
7 - access("T"."ID"="T1"."TID")
8 - access("FID"=NULL)
14 - access("T"."ID"="T1"."TID")
19 - access("T"."ID"="T1"."TID")
Note
-----
- dynamic sampling used for this statement
然後再次基礎上執行了T1.USERNAME = 'YANGTK'。
直接的關聯加樹型查詢等價於下面的SQL：
SQL> SELECT * FROM
2 (
3 SELECT T.ID, FID, NAME, USERNAME
4 FROM T, T1
5 WHERE T.ID = T1.TID
6 START WITH FID = 0
7 CONNECT BY PRIOR T.ID = FID
8 )
9 WHERE USERNAME = 'YANGTK';
ID FID NAME USERNAME
---------- ---------- ------------------------------ ------------------------------
1 0 TABLE YANGTK
10005 1 FILE$ YANGTK
10006 1 UET$ YANGTK
10005 1 FILE$ YANGTK
10006 1 UET$ YANGTK
執行計劃
----------------------------------------------------------
Plan hash value: 778818883
-----------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
-----------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 4 | 240 | 3 (0)| 00:00:01 |
|* 1 | VIEW | | 4 | 240 | 3 (0)| 00:00:01 |
|* 2 | CONNECT BY WITH FILTERING | | | | | |
|* 3 | FILTER | | | | | |
| 4 | COUNT | | | | | |
| 5 | NESTED LOOPS | | 4 | 292 | 3 (0)| 00:00:01 |
| 6 | TABLE ACCESS FULL | T1 | 4 | 120 | 2 (0)| 00:00:01 |
| 7 | TABLE ACCESS BY INDEX ROWID| T | 1 | 43 | 1 (0)| 00:00:01 |
|* 8 | INDEX UNIQUE SCAN | PK_T | 1 | | 1 (0)| 00:00:01 |
|* 9 | HASH JOIN | | | | | |
| 10 | CONNECT BY PUMP | | | | | |
| 11 | COUNT | | | | | |
| 12 | NESTED LOOPS | | 4 | 292 | 3 (0)| 00:00:01 |
| 13 | TABLE ACCESS FULL | T1 | 4 | 120 | 2 (0)| 00:00:01 |
| 14 | TABLE ACCESS BY INDEX ROWID| T | 1 | 43 | 1 (0)| 00:00:01 |
|* 15 | INDEX UNIQUE SCAN | PK_T | 1 | | 1 (0)| 00:00:01 |
| 16 | COUNT | | | | | |
| 17 | NESTED LOOPS | | 4 | 292 | 3 (0)| 00:00:01 |
| 18 | TABLE ACCESS FULL | T1 | 4 | 120 | 2 (0)| 00:00:01 |
| 19 | TABLE ACCESS BY INDEX ROWID | T | 1 | 43 | 1 (0)| 00:00:01 |
|* 20 | INDEX UNIQUE SCAN | PK_T | 1 | | 1 (0)| 00:00:01 |
-----------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - filter("USERNAME"='YANGTK')
2 - filter("FID"=0)
3 - filter("FID"=0)
8 - access("T"."ID"="T1"."TID")
9 - access("FID"=NULL)
15 - access("T"."ID"="T1"."TID")
20 - access("T"."ID"="T1"."TID")
Note
-----
- dynamic sampling used for this statement
而這個結果顯然不是希望得到的。
對於這種即包含關聯又包含樹型查詢的SQL，最好的方法是先做一個，再做另一個，這樣可以確保得到預期的結果：
SQL> SELECT * FROM
2 (
3 SELECT T.ID, FID, NAME, USERNAME
4 FROM T, T1
5 WHERE T.ID = T1.TID
6 AND T1.USERNAME = 'YANGTK'
7 )
8 START WITH FID = 0
9 CONNECT BY PRIOR ID = FID;
ID FID NAME USERNAME
---------- ---------- ------------------------------ ------------------------------
1 0 TABLE YANGTK
10005 1 FILE$ YANGTK
10006 1 UET$ YANGTK
執行計劃
----------------------------------------------------------
Plan hash value: 3886537187
-----------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
-----------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 3 | 219 | 2 (0)| 00:00:01 |
|* 1 | CONNECT BY WITH FILTERING | | | | | |
|* 2 | FILTER | | | | | |
| 3 | COUNT | | | | | |
| 4 | NESTED LOOPS | | 3 | 219 | 2 (0)| 00:00:01 |
| 5 | TABLE ACCESS BY INDEX ROWID| T1 | 3 | 90 | 1 (0)| 00:00:01 |
|* 6 | INDEX RANGE SCAN | IND_T1_NAME | 3 | | 1 (0)| 00:00:01 |
| 7 | TABLE ACCESS BY INDEX ROWID| T | 1 | 43 | 1 (0)| 00:00:01 |
|* 8 | INDEX UNIQUE SCAN | PK_T | 1 | | 1 (0)| 00:00:01 |
|* 9 | HASH JOIN | | | | | |
| 10 | CONNECT BY PUMP | | | | | |
| 11 | COUNT | | | | | |
| 12 | NESTED LOOPS | | 3 | 219 | 2 (0)| 00:00:01 |
| 13 | TABLE ACCESS BY INDEX ROWID| T1 | 3 | 90 | 1 (0)| 00:00:01 |
|* 14 | INDEX RANGE SCAN | IND_T1_NAME | 3 | | 1 (0)| 00:00:01 |
| 15 | TABLE ACCESS BY INDEX ROWID| T | 1 | 43 | 1 (0)| 00:00:01 |
|* 16 | INDEX UNIQUE SCAN | PK_T | 1 | | 1 (0)| 00:00:01 |
| 17 | COUNT | | | | | |
| 18 | NESTED LOOPS | | 3 | 219 | 2 (0)| 00:00:01 |
| 19 | TABLE ACCESS BY INDEX ROWID | T1 | 3 | 90 | 1 (0)| 00:00:01 |
|* 20 | INDEX RANGE SCAN | IND_T1_NAME | 3 | | 1 (0)| 00:00:01 |
| 21 | TABLE ACCESS BY INDEX ROWID | T | 1 | 43 | 1 (0)| 00:00:01 |
|* 22 | INDEX UNIQUE SCAN | PK_T | 1 | | 1 (0)| 00:00:01 |
-----------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - filter("FID"=0)
2 - filter("FID"=0)
6 - access("T1"."USERNAME"='YANGTK')
8 - access("T"."ID"="T1"."TID")
9 - access("FID"=NULL)
14 - access("T1"."USERNAME"='YANGTK')
16 - access("T"."ID"="T1"."TID")
20 - access("T1"."USERNAME"='YANGTK')
22 - access("T"."ID"="T1"."TID")
Note
-----
- dynamic sampling used for this statement
剛才是先做關聯，然後做樹型查詢，也可以反過來，先做樹型查詢：
SQL> SELECT T.ID, FID, NAME, USERNAME
2 FROM
3 (
4 SELECT ID, FID, NAME
5 FROM T
6 START WITH FID = 0
7 CONNECT BY PRIOR ID = FID
8 ) T, T1
9 WHERE T.ID = T1.TID
10 AND T1.USERNAME = 'YANGTK';
ID FID NAME USERNAME
---------- ---------- ------------------------------ ------------------------------
1 0 TABLE YANGTK
10005 1 FILE$ YANGTK
10006 1 UET$ YANGTK
執行計劃
----------------------------------------------------------
Plan hash value: 973607771
-----------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
-----------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 40 | 2920 | 3 (34)| 00:00:01 |
|* 1 | HASH JOIN | | 40 | 2920 | 3 (34)| 00:00:01 |
| 2 | TABLE ACCESS BY INDEX ROWID | T1 | 3 | 90 | 1 (0)| 00:00:01 |
|* 3 | INDEX RANGE SCAN | IND_T1_NAME | 3 | | 1 (0)| 00:00:01 |
| 4 | VIEW | | 40 | 1720 | 1 (0)| 00:00:01 |
|* 5 | CONNECT BY WITH FILTERING | | | | | |
| 6 | TABLE ACCESS BY INDEX ROWID | T | | | | |
|* 7 | INDEX RANGE SCAN | IND_T_FID | 2 | 26 | 1 (0)| 00:00:01 |
| 8 | NESTED LOOPS | | | | | |
| 9 | BUFFER SORT | | | | | |
| 10 | CONNECT BY PUMP | | | | | |
| 11 | TABLE ACCESS BY INDEX ROWID| T | 40 | 1720 | 1 (0)| 00:00:01 |
|* 12 | INDEX RANGE SCAN | IND_T_FID | 16 | | 1 (0)| 00:00:01 |
|* 13 | TABLE ACCESS FULL | T | 40 | 1720 | 1 (0)| 00:00:01 |
-----------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - access("T"."ID"="T1"."TID")
3 - access("T1"."USERNAME"='YANGTK')
5 - filter("FID"=0)
7 - access("FID"=0)
12 - access("FID"=NULL)
13 - access("FID"=NULL)
Note
-----
- dynamic sampling used for this statement
兩種方法選擇那種，就需要根據具體情況進行分析了。
來自 “ ITPUB部落格 ” ，連結：http://blog.itpub.net/4227/viewspace-69444/，如需轉載，請註明出處，否則將追究法律責任。
相關文章
- Hierarchical Queries 級聯查詢(樹狀結構查詢)
- mysql樹狀查詢（轉）MySql
- 巢狀關聯會查詢兩次巢狀
- 區分關聯子查詢和非關聯子查詢
- exist-in和關聯子查詢-非關聯子查詢
- MyBatis關聯查詢MyBatis
- thinkphp關聯查詢PHP
- 關聯查詢子查詢效率簡單比照
- MyBatis(六) sql片段定義、級聯查詢、巢狀查詢MyBatisSQL巢狀
- Mongodb 關聯表查詢MongoDB
- MySQL多表關聯查詢MySql
- JPA多表關聯查詢
- B樹查詢，磁碟查詢資料
- [冷楓推薦]：資料庫操作，內外聯查詢，分組查詢，巢狀查詢，交叉查詢，多表查詢，語句小結。資料庫巢狀
- Mysql 實現樹狀遞迴查詢MySql遞迴
- 資料庫 - 連線查詢、巢狀查詢、集合查詢資料庫巢狀
- 多路查詢樹
- 平衡查詢樹
- oracle 樹查詢Oracle
- 樹形查詢
- mysql 三表關聯查詢MySql
- mysql三表關聯查詢MySql
- mysql關聯查詢優化MySql優化
- 關聯子查詢 Correlated Subqueries
- MySQL聯結查詢和子查詢MySql
- B樹(多路查詢樹)
- 資料庫查詢優化：巢狀查詢資料庫優化巢狀
- 如何做多表關聯查詢
- mysql三張表關聯查詢MySql
- mysql中的多表關聯查詢MySql
- thinkphp中的多表關聯查詢PHP
- SQL三表左關聯查詢SQL
- 關聯子查詢的用處
- 求助：DetachedCriteria關聯查詢問題~~
- 兩表關聯查詢：sql、mybatisSQLMyBatis
- oracle樹形查詢Oracle
- ThinkPHP5.0 使用 model 關聯查詢筆記PHP筆記
- 【Django】關聯查詢set.all() 方法的使用Django