激发顾问的方式有两种:使用 Enterprise Manager 或简单明了的命令行。
首先,让我们看看如何在命令行中使用它。我们通过调用提供的包 dbms_sqltune 来调用顾问。
declare
l_task_id varchar2(20);
l_sql varchar2(2000);
begin
l_sql := 'select account_no from accounts where old_account_no = 11';
dbms_sqltune.drop_tuning_task ('FOLIO_COUNT');
l_task_id := dbms_sqltune.create_tuning_task (
sql_text => l_sql,
user_name => 'ARUP',
scope => 'COMPREHENSIVE',
time_limit => 120,
task_name => 'FOLIO_COUNT'
);
dbms_sqltune.execute_tuning_task ('FOLIO_COUNT');
end;
/
这个包创建并执行了一个名为 FOLIO_COUNT 的调整任务。接下来,您将需要查看任务执行的结果(也就是说,查看建议)。
set serveroutput on size 999999
set long 999999
select dbms_sqltune.report_tuning_task ('FOLIO_COUNT') from dual;
列表 2 显示的是输出结果。仔细查看这些建议;顾问说您可以通过在 OLD_ACCOUNT_NO 列上创建一个索引来改进性能。更佳的是,如果创建索引,顾问计算了查询成本,从而使潜在的节省量
变得更加可定义、更加具体。
当然,考虑到本示例的简单性,通过手动检查也能得到这种结论。但是,可以想象出该工具对于那些更复杂的查询十分有用,因为对这些查询执行手动检查也许是不可能的或不实际的。
第一步:创建优化任务
通过调用函数CREATE_TUNING_TASK来创建优化任务,调用存储过程EXECUTE_TUNING_TASK执行该任务:
SQL> set autot off
SQL> set timing off
SQL> DECLARE
2 my_task_name VARCHAR2(30);
3 my_sqltext CLOB;
4 BEGIN
5 my_sqltext := 'select count(*) from bigtab a, smalltab b where a.object_name=b.table_name';
6 my_task_name := DBMS_SQLTUNE.CREATE_TUNING_TASK(
7 sql_text => my_sqltext,
8 user_name => 'DAVE', -- 注意是大写,不然会报错,用户无效
9 scope => 'COMPREHENSIVE',
10 time_limit => 60,
11 task_name => 'tuning_sql_test',
12 description => 'Task to tune a query on a specified table');
13
14 DBMS_SQLTUNE.EXECUTE_TUNING_TASK( task_name => 'tuning_sql_test');
15 END;
16 /
PL/SQL procedure successfully completed.
在函数CREATE_TUNING_TASK,sql_text是需要优化的语句,user_name是该语句通过哪个用户执行,scope是优化范围(limited或comprehensive),time_limit优化过程的时间限制,
task_name优化任务名称,description优化任务描述。
第二步: 执行优化任务
通过调用dbms_sqltune.execute_tuning_task过程来执行前面创建好的优化任务。
SQL> exec dbms_sqltune.execute_tuning_task('tuning_sql_test');
PL/SQL 过程已成功完成。
第三步:检查优化任务的状态
通过查看user_advisor_tasks/DBA_advisor_tasks视图可以查看优化任务的当前状态。
SQL> SELECT task_name,status FROM USER_ADVISOR_TASKS WHERE task_name ='tuning_sql_test';
TASK_NAME STATUS
------------------------------ -----------
tuning_sql_test COMPLETED
第四步:查看优化结果
通过dbms_sqltune.report_tning_task函数可以获得优化任务的结果。
SQL> SET LONG 999999
SQL> set serveroutput on size 999999
SQL> SET LINESIZE 100
SQL> SELECT DBMS_SQLTUNE.REPORT_TUNING_TASK( 'tuning_sql_test') from DUAL;
DBMS_SQLTUNE.REPORT_TUNING_TASK('TUNING_SQL_TEST')
----------------------------------------------------------------------------------------------------
GENERAL INFORMATION SECTION
-------------------------------------------------------------------------------
Tuning Task Name : tuning_sql_test
Tuning Task Owner : DEMO
Scope : COMPREHENSIVE
Time Limit(seconds) : 60
Completion Status : COMPLETED
Started at : 5/28/2010 13:16:43
Completed at : 5/28/2010 13:16:44
Number of Index Findings : 1
Schema Name: DEMO
SQL ID : 6p64dnnsqf9pm
SQL Text : select count(*) from bigtab a, smalltab b where
a.object_name=b.table_name
-------------------------------------------------------------------------------
FINDINGS SECTION (1 finding)
-------------------------------------------------------------------------------
1- Index Finding (see explain plans section below)
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 DEMO.IDX$$_06C50001 on SYS.SMALLTAB('TABLE_NAME');
- Consider running the Access Advisor to improve the physical schema design
or creating the recommended index.
create index DEMO.IDX$$_06C50002 on SYS.BIGTAB('OBJECT_NAME');
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.
EXPLAIN PLANS SECTION
-------------------------------------------------------------------------------
1- Original
-----------
Plan hash value: 3089226980
--------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
--------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 36 | 3550 (2)| 00:00:43 |
| 1 | SORT AGGREGATE | | 1 | 36 | | |
|* 2 | HASH JOIN | | 155K| 5462K| 3550 (2)| 00:00:43 |
| 3 | TABLE ACCESS FULL| SMALLTAB | 1223 | 22014 | 11 (0)| 00:00:01 |
| 4 | TABLE ACCESS FULL| BIGTAB | 1205K| 20M| 3526 (1)| 00:00:43 |
--------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
2 - access("A"."OBJECT_NAME"="B"."TABLE_NAME")
2- Using New Indices
--------------------
Plan hash value: 494801882
-----------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
-----------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 36 | 1108 (3)| 00:00:14 |
| 1 | SORT AGGREGATE | | 1 | 36 | | |
|* 2 | HASH JOIN | | 155K| 5462K| 1108 (3)| 00:00:14 |
| 3 | INDEX FAST FULL SCAN| IDX$$_06C50001 | 1223 | 22014 | 3 (0)| 00:00:01 |
| 4 | INDEX FAST FULL SCAN| IDX$$_06C50002 | 1205K| 20M| 1093 (2)| 00:00:14 |
-----------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
2 - access("A"."OBJECT_NAME"="B"."TABLE_NAME")
------------------------------------------------------------------------------
看一下这个优化建议报告:
第一部分是关于这次优化任务的基本信息:如任务名称、执行时间、范围、涉及到的语句等等。
第二部分是关于这次优化任务的所找到的问题以及给出的优化建议。前面先给出了问题描述:可以通过建立更多的所引来提高性能;然后是建议的具体内容:在表smalltab的字段table_name
上创建索引,在表bigtab的字段object_name上创建索引;最后是相关注意事项:此次优化虽然给出了创建索引的建议,但是最好通过SQL访问建议器(SQL Access Advisor SAA)结合整个数据
库的工作量来深入分析,那样就能给出考虑了索引维护和空间消耗等因素的更加合理的建议。
最后,报告还给出了原有的查询计划,以及采用优化建议以后的查询计划的对比。可以看出COST值大大下降。
五、删除优化任务
通过调用dbms_sqltuen.drop_tuning_task可以删除已经存在的优化任务
SQL>exec dbms_sqltune.drop_tuning_task('tuning_sql_test');
PL/SQL procedure successfully completed.
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