如何用 SQL Tuning Advisor (STA) 優化SQL語句

在oracle10g以前,想要優化一個sql語句是比較麻煩,可是在oracle10g這個版本推出的SQL Tuning Advisor這個工具,能大大減小sql調優的工做量,不過要想使用SQL Tuning Advisor,必定要保證你的優化器是CBO模式。
1.首先須要建立一個用於調優的用戶bamboo,並授予advisor給建立的用戶
SQL> create user bamboo identified by bamboo;
User created.
SQL> grant connect,resource to bamboo;
Grant succeeded.
SQL> grant advisor to bamboo;
Grant succeeded.
sql

2.建立用戶作測試的2張表,大表裏面插入500萬條數據,小表裏面插入10萬條數據,其建立方法以下
SQL> create table bigtable (id number(10),name varchar2(100));
Table created.
oracle

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

PL/SQL procedure successfully completed.工具

SQL> commti;oop

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

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

PL/SQL procedure successfully completed.ui

SQL> commti;this

3.而後對bigtable和smalltable作一個等鏈接查詢,而後跟蹤其執行計劃
SQL> select a.id,a.name,b.id,b.name from bigtable a,smalltable b where a.id=b.id and a.id=40000;
spa

        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
熟悉執行計劃的就能夠看出,這個sql執行是很慢的,2個表都作的是全表掃描,而且其物理讀是11469,按照優化的經驗,給2個表的id建立索引,減小查詢時候的物理讀,下面咱們就看看經過優化器,oracle能咱們什麼樣的建議呢?

4.下面就經過DBMS_SQLTUNE包的CREATE_TUNING_TASK來建立一個優化任務,而後經過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.執行的過程當中,也能夠經過user_advisor_tasks或者dba_advisor_tasks來查看調優任務執行的情況
SQL> select task_name,ADVISOR_NAME,STATUS from user_advisor_tasks;

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

6.經過調用dbms_sqltune.report_tuning_task能夠查詢調優的結果,不過在查詢結果以前,得設置sqlplus的環境,若是不設置,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

---------------------------------------------------------------------------------
| Id  | Operation          | Name       | Rows  | Bytes | Cost (%CPU)| Time     |
---------------------------------------------------------------------------------

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)

  從上面的結果能夠看到oracle的調優顧問給咱們3條建議:
(1)SCOTT.SMALLTABLE表沒有作分析,須要作一下表結構的分析,而且給出一個分析的建議,以下所示
     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表沒有作分析,須要作一下表結構的分析,而且給出一個分析的建議,以下所示
     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建議咱們在表SCOTT.SMALLTABLE,SCOTT.BIGTABLE的id列建立一個bitree索引,給的建議以下
      create index SCOTT.IDX$$_00790002 on SCOTT.BIGTABLE('ID');  
      create index SCOTT.IDX$$_00790001 on SCOTT.SMALLTABLE('ID');
    固然建立索引的名字能夠改爲別的名字
    經過以上查看oracle的調優顧問給的建議,基本和咱們在前面給出的調優方案是一致,所以當咱們給一個大的SQL作優化的時候,能夠先使用oracle調優顧問,獲得一些調優方案,而後根據實際狀況作一些調整就能夠。

 如下就是執行oracle調優顧問的建議,從新執行select a.id,a.name,b.id,b.name from bigtable a,smalltable b where a.id=b.id and a.id=40000這天語句獲得的執行計劃,能夠看出查詢時間和物理讀大大減小
 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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