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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.

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:

finally { JDBCUtil.close( pstmt ); } } }

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.

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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Previously, we manually created the wrapper method corresponding to the method get_address() of the object type address. In this section, we ll look at how to do this automatically using JPublisher. To generate the wrapper method automatically, the only change we need to make is to modify the option methods=none to methods=all in prop_address.txt. This results in a new prop_address.txt file, the contents of which are as follows:. jpub.user=benchmark/benchmark jpub.methods=all jpub.builtintypes=jdbc jpub.numbertypes=objectjdbc jpub.usertypes=jdbc jpub.package=book.ch08.jpub jpub.input=input_address.txt For clarity, we specify the class names to be AddressAuto and MyAddressAuto in the file input_address.txt, which now looks as follows. input_address.txt results in two classes: a parent class called AddressAuto and a child class MyAddressAuto. SQL ADDRESS GENERATE AddressAuto AS MyAddressAuto The relevant portions of the generated parent class file AddressAuto.java (partially edited for clarity) are as follows: /*@lineinfo:filename=AddressAuto*//*@lineinfo:user-code*//*@lineinfo:1^1*/ package book.ch10.jpub; /* Some other imports deleted for clarity */ import oracle.jpub.runtime.MutableStruct; import sqlj.runtime.ref.DefaultContext; import sqlj.runtime.ConnectionContext; public class AddressAuto implements SQLData { public static final String _SQL_NAME = "BENCHMARK.ADDRESS"; public static final int _SQL_TYPECODE = OracleTypes.STRUCT; /* connection management */ protected DefaultContext __tx = null; protected Connection __onn = null;

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.

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.

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.

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