在oracle10g之前，想要最佳化一個sql語句是比較麻煩，但是在oracle10g這個版本推出的SQL Tuning Advisor這個工具，能大大減少sql調優的工作量，不過要想使用SQL Tuning Advisor，一定要保證你的最佳化器是CBO模式。
1.首先需要建立一個用於調優的使用者bamboo,並授予advisor給建立的使用者
SQL> create user bamboo identified by bamboo;
User created.
SQL> grant connect,resource to bamboo;
Grant succeeded.
SQL> grant advisor to bamboo;
Grant succeeded.

2.建立使用者做測試的2張表,大表裡面插入500萬條資料，小表裡面插入10萬條資料，其建立方法如下
SQL> create table bigtable (id number(10),name varchar2(100));
Table created.

SQL> begin
2 for i in 1..5000000 loop
3 insert into bigtable values(i,'test'||i);
4 end loop;
5 end;
6 /

PL/SQL procedure successfully completed.

SQL> commti;

SQL> create table smalltable (id number(10),name varchar2(100));
Table created.

SQL> begin
2 for i in 1..100000 loop
3 insert into smalltable values(i,'test'||i);
4 end loop;
5 end;
6 /

PL/SQL procedure successfully completed.

SQL> commti;

3.然後對bigtable和smalltable做一個等連線查詢，然後跟蹤其執行計劃
SQL> select a.id,a.name,b.id,b.name from bigtable a,smalltable b where a.id=b.id and a.id=40000;

ID NAME ID NAME
---------- ---------------------------------------- ---------- ----------------------------------------
40000 test40000 40000 test40000

Execution Plan
----------------------------------------------------------
Plan hash value: 1703851322

---------------------------------------------------------------------------------
| Id | Operation          | Name       | Rows | Bytes | Cost (%CPU)| Time     |
---------------------------------------------------------------------------------
|   0 | SELECT STATEMENT   |            |   839 |   106K| 3656   (5)| 00:00:44 |
|* 1 | HASH JOIN         |            |   839 |   106K| 3656   (5)| 00:00:44 |
|* 2 |   TABLE ACCESS FULL| SMALLTABLE |     5 |   325 |    71   (3)| 00:00:01 |
|* 3 |   TABLE ACCESS FULL| BIGTABLE   |   173 | 11245 | 3584   (5)| 00:00:44 |
---------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   1 - access("A"."ID"="B"."ID")
   2 - filter("B"."ID"=40000)
   3 - filter("A"."ID"=40000)

Note
-----
- dynamic sampling used for this statement

Statistics
----------------------------------------------------------
          9 recursive calls
          0 db block gets
      16151 consistent gets
      11469 physical reads
          0 redo size
        588 bytes sent via SQL*Net to client
        385 bytes received via SQL*Net from client
          2 SQL*Net roundtrips to/from client
          2 sorts (memory)
          0 sorts (disk)
          1 rows processed
熟悉執行計劃的就可以看出，這個sql執行是很慢的，2個表都做的是全表掃描，並且其物理讀是11469，按照最佳化的經驗，給2個表的id建立索引，減少查詢時候的物理讀,下面我們就看看透過最佳化器，oracle能我們什麼樣的建議呢？

4.下面就透過DBMS_SQLTUNE包的CREATE_TUNING_TASK來建立一個最佳化任務，然後透過DBMS_SQLTUNE.EXECUTE_TUNING_TASK來執行調優任務，生成調優建議
SQL> DECLARE
2    my_task_name VARCHAR2(30);
3    my_sqltext CLOB;
4 BEGIN
5    my_sqltext := 'select a.id,a.name,b.id,b.name from bigtable a,smalltable b where a.id=b.id and a.id=40000';
6
7    my_task_name := DBMS_SQLTUNE.CREATE_TUNING_TASK(
8                            sql_text => my_sqltext,
9                            user_name => 'SCOTT',
10                             scope => 'COMPREHENSIVE',
11                             time_limit => 60,
12                             task_name => 'test_sql_tuning_task1',
13                             description => 'Task to tune a query');
14     DBMS_SQLTUNE.EXECUTE_TUNING_TASK(task_name => 'test_sql_tuning_task1');
15 END;
16 /

5.執行的過程中，也可以透過user_advisor_tasks或者dba_advisor_tasks來檢視調優任務執行的狀況
SQL> select task_name,ADVISOR_NAME,STATUS from user_advisor_tasks;

TASK_NAME ADVISOR_NAME STATUS
------------------------------ ---------------------------------------- ---------------------------------
test_sql_tuning_task1 SQL Tuning Advisor COMPLETED
如果status是EXECUTING，則表示任務正在執行，如果為COMPLETED，則任務已經執行完畢

6.透過呼叫dbms_sqltune.report_tuning_task可以查詢調優的結果，不過在查詢結果之前，得設定sqlplus的環境，如果不設定，則查詢的結果出不來
SQL> set long 999999
SQL> set LONGCHUNKSIZE 999999
SQL> set serveroutput on size 999999
SQL> set linesize 200
SQL> select dbms_sqltune.report_tuning_task('test_sql_tuning_task1') from dual;

SQL> select dbms_sqltune.report_tuning_task('test_sql_tuning_task1') from dual;

DBMS_SQLTUNE.REPORT_TUNING_TASK('TEST_SQL_TUNING_TASK1')
---------------------------------------------------------------------------------------------------------------------------------
GENERAL INFORMATION SECTION
-------------------------------------------------------------------------------
Tuning Task Name                  : test_sql_tuning_task1
Tuning Task Owner                 : BAMBOO
Scope                             : COMPREHENSIVE
Time Limit(seconds)               : 60
Completion Status                 : COMPLETED
Started at                        : 10/13/2011 05:07:53
Completed at                      : 10/13/2011 05:08:18
Number of Statistic Findings      : 2
Number of Index Findings          : 1

DBMS_SQLTUNE.REPORT_TUNING_TASK('TEST_SQL_TUNING_TASK1')
----------------------------------------------------------------------------------------------------------------------------------
Schema Name: SCOTT
SQL ID     : 7arau1k5a3mv1
SQL Text   : select a.id,a.name,b.id,b.name from bigtable a,smalltable b
             where a.id=b.id and a.id=40000

-------------------------------------------------------------------------------
FINDINGS SECTION (3 findings)
-------------------------------------------------------------------------------

DBMS_SQLTUNE.REPORT_TUNING_TASK('TEST_SQL_TUNING_TASK1')
----------------------------------------------------------------------------------------------------------------------------------
1- Statistics Finding
---------------------
Table "SCOTT"."SMALLTABLE" was not analyzed.

Recommendation
--------------
- Consider collecting optimizer statistics for this table.
    execute dbms_stats.gather_table_stats(ownname => 'SCOTT', tabname =>
            'SMALLTABLE', estimate_percent => DBMS_STATS.AUTO_SAMPLE_SIZE,
            method_opt => 'FOR ALL COLUMNS SIZE AUTO');

DBMS_SQLTUNE.REPORT_TUNING_TASK('TEST_SQL_TUNING_TASK1')
----------------------------------------------------------------------------------------------------------------------------------
Rationale
---------
The optimizer requires up-to-date statistics for the table in order to
select a good execution plan.

2- Statistics Finding
---------------------
Table "SCOTT"."BIGTABLE" was not analyzed.

Recommendation
--------------

DBMS_SQLTUNE.REPORT_TUNING_TASK('TEST_SQL_TUNING_TASK1')
----------------------------------------------------------------------------------------------------------------------------------
- Consider collecting optimizer statistics for this table.
    execute dbms_stats.gather_table_stats(ownname => 'SCOTT', tabname =>
            'BIGTABLE', estimate_percent => DBMS_STATS.AUTO_SAMPLE_SIZE,
            method_opt => 'FOR ALL COLUMNS SIZE AUTO');

Rationale
---------
The optimizer requires up-to-date statistics for the table in order to
select a good execution plan.

3- Index Finding (see explain plans section below)

DBMS_SQLTUNE.REPORT_TUNING_TASK('TEST_SQL_TUNING_TASK1')
---------------------------------------------------------------------------------------------------------------------------------
The execution plan of this statement can be improved by creating one or more
indices.

Recommendation (estimated benefit: 100%)
----------------------------------------
- Consider running the Access Advisor to improve the physical schema design
or creating the recommended index.
create index SCOTT.IDX$$_00790001 on SCOTT.SMALLTABLE('ID');

- Consider running the Access Advisor to improve the physical schema design

DBMS_SQLTUNE.REPORT_TUNING_TASK('TEST_SQL_TUNING_TASK1')
----------------------------------------------------------------------------------------------------------------------------------
or creating the recommended index.
create index SCOTT.IDX$$_00790002 on SCOTT.BIGTABLE('ID');

Rationale
---------
    Creating the recommended indices significantly improves the execution plan
    of this statement. However, it might be preferable to run "Access Advisor"
    using a representative SQL workload as opposed to a single statement. This
    will allow to get comprehensive index recommendations which takes into
    account index maintenance overhead and additional space consumption.

DBMS_SQLTUNE.REPORT_TUNING_TASK('TEST_SQL_TUNING_TASK1')
----------------------------------------------------------------------------------------------------------------------------------
-------------------------------------------------------------------------------
EXPLAIN PLANS SECTION
-------------------------------------------------------------------------------

1- Original
-----------
Plan hash value: 1703851322

DBMS_SQLTUNE.REPORT_TUNING_TASK('TEST_SQL_TUNING_TASK1')
----------------------------------------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT   |            |   839 |   106K| 3656   (5)| 00:00:44 |
|* 1 | HASH JOIN         |            |   839 |   106K| 3656   (5)| 00:00:44 |
|* 2 |   TABLE ACCESS FULL| SMALLTABLE |     5 |   325 |    71   (3)| 00:00:01 |
|* 3 |   TABLE ACCESS FULL| BIGTABLE   |   173 | 11245 | 3584   (5)| 00:00:44 |
---------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

1 - access("A"."ID"="B"."ID")
2 - filter("B"."ID"=40000)

DBMS_SQLTUNE.REPORT_TUNING_TASK('TEST_SQL_TUNING_TASK1')
---------------------------------------------------------------------------------------------------------------------------------
3 - filter("A"."ID"=40000)

2- Using New Indices
--------------------
Plan hash value: 3720188830

------------------------------------------------------------------------------------------------
| Id | Operation                     | Name           | Rows | Bytes | Cost (%CPU)| Time     |
------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT              |                |     1 |   130 |     5   (0)| 00:00:01 |
|   1 | TABLE ACCESS BY INDEX ROWID | BIGTABLE       |     1 |    65 |     3   (0)| 00:00:01 |

DBMS_SQLTUNE.REPORT_TUNING_TASK('TEST_SQL_TUNING_TASK1')
---------------------------------------------------------------------------------------------------------------------------------
|   2 |   NESTED LOOPS                |                |     1 |   130 |     5   (0)| 00:00:01 |
|   3 |    TABLE ACCESS BY INDEX ROWID| SMALLTABLE     |     1 |    65 |     2   (0)| 00:00:01 |
|* 4 |     INDEX RANGE SCAN          | IDX$$_00790001 |     1 |       |     1   (0)| 00:00:01 |
|* 5 |    INDEX RANGE SCAN           | IDX$$_00790002 |     1 |       |     2   (0)| 00:00:01 |
------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

4 - access("B"."ID"=40000)
5 - access("A"."ID"=40000)

從上面的結果可以看到oracle的調優顧問給我們3條建議：
（1）SCOTT.SMALLTABLE表沒有做分析，需要做一下表結構的分析，並且給出一個分析的建議，如下所示
     execute dbms_stats.gather_table_stats(ownname => 'SCOTT', tabname =>
            'SMALLTABLE', estimate_percent => DBMS_STATS.AUTO_SAMPLE_SIZE,
            method_opt => 'FOR ALL COLUMNS SIZE AUTO');
（2）SCOTT.BIGTABLE表沒有做分析，需要做一下表結構的分析，並且給出一個分析的建議，如下所示
     execute dbms_stats.gather_table_stats(ownname => 'SCOTT', tabname =>
            'BIGTABLE', estimate_percent => DBMS_STATS.AUTO_SAMPLE_SIZE,
            method_opt => 'FOR ALL COLUMNS SIZE AUTO');
（3）oracle建議我們在表SCOTT.SMALLTABLE，SCOTT.BIGTABLE的id列建立一個bitree索引，給的建議如下
      create index SCOTT.IDX$$_00790002 on SCOTT.BIGTABLE('ID');
      create index SCOTT.IDX$$_00790001 on SCOTT.SMALLTABLE('ID');
    當然建立索引的名字可以改成別的名字
    透過以上檢視oracle的調優顧問給的建議，基本和我們在前面給出的調優方案是一致，因此當我們給一個大的ＳＱＬ做最佳化的時候，可以先使用oracle調優顧問，得到一些調優方案，然後根據實際情況做一些調整就可以。

以下就是執行oracle調優顧問的建議，重新執行select a.id,a.name,b.id,b.name from bigtable a,smalltable b where a.id=b.id and a.id=40000這天語句得到的執行計劃，可以看出查詢時間和物理讀大大減少
SQL> select a.id,a.name,b.id,b.name from bigtable a,smalltable b where a.id=b.id and a.id=40000;

ID NAME ID NAME
---------- ---------------------------------------- ---------- ----------------------------------------
40000 test40000 40000 test40000

Execution Plan
----------------------------------------------------------
Plan hash value: 777647921

-------------------------------------------------------------------------------------------------
| Id | Operation                     | Name            | Rows | Bytes | Cost (%CPU)| Time     |
-------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT              |                 |     1 |    31 |     5   (0)| 00:00:01 |
|   1 | TABLE ACCESS BY INDEX ROWID | BIGTABLE        |     1 |    17 |     3   (0)| 00:00:01 |
|   2 |   NESTED LOOPS                |                 |     1 |    31 |     5   (0)| 00:00:01 |
|   3 |    TABLE ACCESS BY INDEX ROWID| SMALLTABLE      |     1 |    14 |     2   (0)| 00:00:01 |
|* 4 |     INDEX RANGE SCAN          | I_ID_SAMLLTABLE |     1 |       |     1   (0)| 00:00:01 |
|* 5 |    INDEX RANGE SCAN           | I_ID_BIGTABLE   |     1 |       |     2   (0)| 00:00:01 |
-------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

4 - access("B"."ID"=40000)
5 - access("A"."ID"=40000)

Statistics
----------------------------------------------------------
          0 recursive calls
          0 db block gets
          9 consistent gets
          0 physical reads
          0 redo size
        588 bytes sent via SQL*Net to client
        385 bytes received via SQL*Net from client
          2 SQL*Net roundtrips to/from client
          0 sorts (memory)
          0 sorts (disk)
          1 rows processed

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SQL Tuning Advisor使用例項

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