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can take steps to preserve SQL performance by using SQL Plan Management (SPM), which I discussed in 19. Or, you can employ the SQL Tuning Advisor to tune the potentially negatively impacted SQL statements. You can use either the production system or a test system to run the SQL Performance Analyzer. Of course, if you run the analysis on a test system, you can avoid overhead on your production system. You can capture the SQL workload on a production system and run the analyzer on the test system. You can use either the Enterprise Manger or components of the DBMS_SQLPA package to use the SQL Performance Analyzer. You capture the SQL workload in the production system by using a SQL Tuning Set (STS). Once you capture SQL information in the STS, you can export the STS to the test system to provide the data for the SQL Performance Analyzer analysis. You can use any of the following as sources of the statements you load into the STS: AWR snapshots AWR baselines A cursor cache Another STS The SQL Performance Analyzer executes SQL serially on the test server, ignoring the concurrency characteristics. It analyzes performance differences in the before- and after-change SQL workloads. The analyzer is integrated with the SQL Tuning Advisor for easy tuning of regressed statements. I explain the workflow of a SQL Performance Analyzer analysis by showing how to predict changes in SQL performance following an upgrade to Oracle Database 11g from Oracle Database Release 10.2.
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Capturing the Production SQL Workload
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Select a representative period to capture the SQL workload from the production database. The workload that you collect consists of the SQL text and information pertaining to bind variable values and execution frequency. Following are the steps in capturing the production SQL workload:
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Creating the SQL Tuning Set
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Create the STS by executing the CREATE_SQLSET procedure as shown here: SQL> exec dbms_sqltune.create_sqlset(sqlset_name => 'test_set', description => '11g upgrade workload'; The next step is to load the empty STS you created in this step.
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Loading the SQL Tuning Set
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Execute the DBMS_SQLTUNE SELECT_CURSOR_CACHE procedure to load the empty STS. declare mycur dbms_sqltune.sqlset_cursor; begin open mycur for select value (P) from table (dbms_sqltune.select_cursor_cache( 'parsing_schema_name <> ''SYS'' AND elapsed_time > 2500000',null,null,null,null,1,null, 'ALL')) P;
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CHAPTER 20 PERFOR MAN CE TUNING: TUNING THE INSTA NCE
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dbms_sqltune.load_sqlset(sqlset_name => 'upgrade_set', populate_cursor => cur); end; / PL/SQL procedure successfully completed. SQL> The database incrementally loads the STS from the cursor cache over a period of time.
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Transporting the SQL Tuning Set
Create a staging table first, in order to transport the STS to the test system. SQL> exec dbms_sqltune.create_stgtb_sqlset ( table_name => 'stagetab'); Export the STS to the staging table using the PACK_STGTAB_SQLSEET procedure. SQL> exec dbms_sqltune.pack_stgtab_sqlset(sqlset_name => 'test_sts', staging_table_name => 'stagetab'); In the next step, you ll import the staging table you created into the test system. Use Data Pump to import the staging table stagetab into the test system. Execute the UNPACK_STGTAB_SQLSET procedure to the import the STS into the test database. SQL> exec dbms_sqltune.unpack_stgtab_sqlset (sqlset_name = '%', replace => true, staging_table_name => ('stagetab'); Next, you ll create the SQL Performance Analyzer task.
Creating the SQL Performance Analyzer Task
Use the CREATE_ANALYSIS_TASK procedure to create a new SQL Performance Analyzer task, as shown here: SQL> exec dbms_sqlpa.create_analysis_task(sqlset_name => 'sts1', task_name => 'spa_task1'); The procedure you execute here enables you to create an analyzer job to analyze one or more SQL statements.
Analyzing the Prechange SQL Workload
The before-change SQL workload analysis analyzes the performance of SQL statements in an Oracle 10.2 environment. Make sure that the OPTIMIZER_FEATURES_ENABLE initialization parameter is correctly set. optimizer_features_enable=10.2.0 Execute the EXECUTE_ANALYSIS_TASK procedure to analyze the preupgrade performance of the SQL workload, as shown here: SQL> exec dbms_sqlpa.execute_analysis_task (task_name => 'spa_task1', execution_type => 'test_execute', execution_name= 'before_change');
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Note that the value of the EXECUTION_TYPE parameter is set to TEST_EXECUTE. This value ensures that the database executes all SQL statements in the workload and generates both the execution plans and execution statistics such as disk reads. You can assign two other values for the EXECUTION_TYPE parameter. The COMPARE_PERFORMANCE parameter will compare the performance based on a comparison of two different analyses. The value EXPLAIN_PLAN will generate SQL plans without executing them. Get a report of the preupgrade SQL performance by executing the REPORT_ANALYSIS_TASK function: SQL> select dbms_sqlpa.report_analysis_task (task_name => 'spa_task1', type => 'text', section=> 'summary') from dual; You now have a performance baseline with which to compare the after-upgrade SQL performance.
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