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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
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