如何手动创建profile维持sql计划的稳定性
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发布时间：2022-04-10 08:00
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时间：2022-04-10 12:22
SQL调优工具包DBMS_SQLTUNE的使用方法
oracle 提供了优化建议功能包DBMS_SQLTUNE，该包可以帮助我们分析SQL，并提供优化建议。
原有执行计划
alter session set statistics_level=all;
set serveroutput off
select * from test.emp where ename=‘SCOTT‘ and DEPTNO=20;
SELECT * FROM table(dbms_xplan.display_cursor(NULL,NULL,‘runstats_last‘));
PLAN_TABLE_OUTPUT
------------------------------------------------------------------------------------------------------------------------
SQL_ID 8k1gbrapm7zpd, child number 0
-------------------------------------
select * from test.emp where ename=‘SCOTT‘ and DEPTNO=20
Plan hash value: 3956160932
------------------------------------------------------------------------------------
| Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers |
------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | | 1 |00:00:00.01 | 4 |
|* 1 | TABLE ACCESS FULL| EMP | 1 | 1 | 1 |00:00:00.01 | 4 |
-------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - filter(("ENAME"=‘SCOTT‘ AND "DEPTNO"=20))
下面就用DBMS_SQLTUNE优化该SQL
--1.赋予用户ADVISOR权限
grant ADVISOR to test;
--2.创建sql tuning任务
conn test/test
DECLARE
my_task_name VARCHAR2(30);
my_sqltext CLOB;
BEGIN
my_sqltext := ‘select * from emp where ename= :name and DEPTNO= :deptno‘;
my_task_name := DBMS_SQLTUNE.CREATE_TUNING_TASK(
sql_text => my_sqltext,
bind_list => sql_binds(anydata.convertvarchar2(10),anydata.convertnumber(2)),
user_name => ‘TEST‘,
scope => ‘COMPREHENSIVE‘,
time_limit => 60,
task_name => ‘test_sql_tuning‘,
description => ‘Task to tune a query on emp‘);
END;
/
参数说明：
bind_list：多个绑定变量以‘,‘逗号分隔。参数值一定要根据绑定变量对应的列的类型书写.
如：emp.ename类型是VARCHAR2(10)，那么就要写成
bind_list =>sql_binds(anydata.convertvarchar2(10)),
time_limit：执行的最长时间，默认是60。
scope：
LIMITED，用大概1秒时间去优化SQL语句，但是并不进行SQL Profiling分析。
COMPREHENSIVE，进行全面分析，包含SQL Profiling分析；比LIMITED用时更长。
**也可以用sql_id创建sql tunning任务，比用sql_text方便很多
FUNCTION CREATE_TUNING_TASK RETURNS VARCHAR2
Argument Name Type In/Out Default?
------------------------------ ----------------------- ------ --------
SQL_ID VARCHAR2 IN
PLAN_HASH_VALUE NUMBER IN DEFAULT
SCOPE VARCHAR2 IN DEFAULT
TIME_LIMIT NUMBER IN DEFAULT
TASK_NAME VARCHAR2 IN DEFAULT
DESCRIPTION VARCHAR2 IN DEFAULT
DECLARE
my_task_name VARCHAR2(30);
BEGIN
my_task_name := DBMS_SQLTUNE.CREATE_TUNING_TASK(
SQL_ID => ‘ddw7j6yfnw0vz‘,
scope => ‘COMPREHENSIVE‘,
time_limit => 60,
task_name => ‘tunning_task_ddw7j6yfnw0vz‘,
description => ‘Task to tune a query on ddw7j6yfnw0vz‘);
END;
/
/*2014-4-8日增加 end*/
--3.查看任务名 SELECT TASK_NAME
FROM DBA_ADVISOR_LOG
WHERE OWNER = ‘TEST‘;
TASK_NAME
------------------------------
test_sql_tuning
--4.执行sql tuning任务
BEGIN
DBMS_SQLTUNE.EXECUTE_TUNING_TASK( task_name => ‘test_sql_tuning‘ );
END;
/
--5.查看sql tunning任务状态
SELECT status
FROM USER_ADVISOR_TASKS
WHERE task_name = ‘test_sql_tuning‘;
STATUS
-----------
COMPLETED
--6.展示sql tunning结果
SET LONG 10000
SET LONGCHUNKSIZE 1000
SET LINESIZE 100
SELECT DBMS_SQLTUNE.REPORT_TUNING_TASK(‘test_sql_tuning‘)
FROM DUAL;
DBMS_SQLTUNE.REPORT_TUNING_TASK(‘TEST_SQL_TUNING‘)
----------------------------------------------------------------------------------------------------
GENERAL INFORMATION SECTION
-------------------------------------------------------------------------------
Tuning Task Name : test_sql_tuning
Tuning Task Owner : TEST
Workload Type : Single SQL Statement
Scope : COMPREHENSIVE
Time Limit(seconds): 60
Completion Status : COMPLETED
Started at : 04/01/2014 16:45:16
Completed at : 04/01/2014 16:45:17
DBMS_SQLTUNE.REPORT_TUNING_TASK(‘TEST_SQL_TUNING‘)
----------------------------------------------------------------------------------------------------
-------------------------------------------------------------------------------
Schema Name: TEST
SQL ID : 95fv6dbj64d0f
SQL Text : select * from emp where ename= :name and DEPTNO= :deptno
-------------------------------------------------------------------------------
FINDINGS SECTION (2 findings)
-------------------------------------------------------------------------------
1- Statistics Finding
---------------------
DBMS_SQLTUNE.REPORT_TUNING_TASK(‘TEST_SQL_TUNING‘)
----------------------------------------------------------------------------------------------------
Table "TEST"."EMP" was not analyzed.
Recommendation
--------------
- Consider collecting optimizer statistics for this table.
execute dbms_stats.gather_table_stats(ownname => ‘TEST‘, tabname =>
‘EMP‘, estimate_percent => DBMS_STATS.AUTO_SAMPLE_SIZE,
method_opt => ‘FOR ALL COLUMNS SIZE AUTO‘);
Rationale
---------
DBMS_SQLTUNE.REPORT_TUNING_TASK(‘TEST_SQL_TUNING‘)
----------------------------------------------------------------------------------------------------
The optimizer requires up-to-date statistics for the table in order to
select a good execution plan.
2- 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: 66.67%)
------------------------------------------
- Consider running the Access Advisor to improve the physical schema design
DBMS_SQLTUNE.REPORT_TUNING_TASK(‘TEST_SQL_TUNING‘)
----------------------------------------------------------------------------------------------------
or creating the recommended index.
create index TEST.IDX$$_00D80001 on TEST.EMP("ENAME","DEPTNO");
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‘)
----------------------------------------------------------------------------------------------------
-------------------------------------------------------------------------------
EXPLAIN PLANS SECTION
-------------------------------------------------------------------------------
1- Original
-----------
Plan hash value: 3956160932
--------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
--------------------------------------------------------------------------
DBMS_SQLTUNE.REPORT_TUNING_TASK(‘TEST_SQL_TUNING‘)
----------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 87 | 3 (0)| 00:00:01 |
|* 1 | TABLE ACCESS FULL| EMP | 1 | 87 | 3 (0)| 00:00:01 |
--------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - filter("ENAME"=:NAME AND "DEPTNO"=:DEPTNO)
2- Using New Indices
--------------------
DBMS_SQLTUNE.REPORT_TUNING_TASK(‘TEST_SQL_TUNING‘)
----------------------------------------------------------------------------------------------------
Plan hash value: 2106247215
----------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
----------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 87 | 1 (0)| 00:00:01 |
| 1 | TABLE ACCESS BY INDEX ROWID| EMP | 1 | 87 | 1 (0)| 00:00:01 |
|* 2 | INDEX RANGE SCAN | IDX$$_00D80001 | 1 | | 1 (0)| 00:00:01 |
----------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
DBMS_SQLTUNE.REPORT_TUNING_TASK(‘TEST_SQL_TUNING‘)
----------------------------------------------------------------------------------------------------
---------------------------------------------------
2 - access("ENAME"=:NAME AND "DEPTNO"=:DEPTNO)
-------------------------------------------------------------------------------
建议报告总结：
<1>收集EMP表的统计信息
execute dbms_stats.gather_table_stats(ownname => ‘TEST‘, tabname =>‘EMP‘, estimate_percent => DBMS_STATS.AUTO_SAMPLE_SIZE,method_opt => ‘FOR ALL COLUMNS SIZE AUTO‘);
<2>创建索引
create index TEST.IDX$$_00D80001 on TEST.EMP("ENAME","DEPTNO");
优化后执行计划
--------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers |
--------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | | 1 |00:00:00.01 | 3 |
| 1 | TABLE ACCESS BY INDEX ROWID| EMP | 1 | 1 | 1 |00:00:00.01 | 3 |
|* 2 | INDEX RANGE SCAN | IDX$$_00D80001 | 1 | 1 | 1 |00:00:00.01 | 2 |
--------------------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
2 - access("ENAME"=‘SCOTT‘ AND "DEPTNO"=20)
--7.完成后删除sql tunning任务
EXEC DBMS_SQLTUNE.DROP_TUNING_TASK(‘test_sql_tuning‘);
--8.其他
--sql tunning任务创建后，也可以修改参数
BEGIN
DBMS_SQLTUNE.SET_TUNING_TASK_PARAMETER(
task_name => ‘test_sql_tuning‘,
parameter => ‘TIME_LIMIT‘, value => 300);
END;
/
--查看SQL Tuning Advisor的进展（task执行很久）
col opname for a20
col ADVISOR_NAME for a20
SELECT SID,SERIAL#,USERNAME,OPNAME,ADVISOR_NAME,TARGET_DESC,START_TIME SOFAR, TOTALWORK
FROM V$ADVISOR_PROGRESS
WHERE USERNAME = ‘TEST‘;
以上根据oracle doc整理
http://docs.oracle.com/cd/E11882_01/server.112/e41573/sql_tune.htm#PFGRF94856
转载：
http://blog.chinaunix.net/uid-23284114-id-4192029.html
DBMS_SQLTUNE使用方法
标签：apm exec 建议 工具包 which dep list report set
热心网友
时间：2022-04-10 09:30
10g以后的sql tuning advisor(可以通过Enterprise Manager或DBMS_SQLTUNE包访问)会给出对于SQL的建议包括以下四种：
1. 收集最新的统计信息
2. 彻底重构该SQL语句
3. 创建推荐的索引
4. 启用SQL TUNING ADVISOR找到的SQL PROFILE
这里我们要注意的是在proction环境中显然不可能让我们在没有充分测试的前提下随意为SQL接受一个PROFILE，因为这可能为本来就性能糟糕而需要调优的系统引来变化。
但是如果恰巧没有合适的TEST环境，而你的SQL PROFILE又可能是性能压力的救命稻草时，我们可以使用以下方法在proction环境中局部测试SQL PROFILE，仅在session级别生效：
热心网友
时间：2022-04-10 10:48
