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So, one row was successfully inserted into T and we duly received the message, I fired and updated 1 rows. The next INSERT statement violates the integrity constraint we have on T. The DBMS_OUTPUT message appeared the trigger on T in fact did fire and we have evidence of that. It performed its updates of T2 successfully. We would maybe expect T2 to have a value of 2 now, but we see it has a value of 1. Oracle made the original INSERT atomic the original INSERT INTO T is the statement, and any side effects of that original INSERT INTO T are considered part of that statement. Oracle achieves this statement-level atomicity by silently wrapping a SAVEPOINT around each of our calls to the database. The preceding two INSERTs were really treated like this: Savepoint statement1; Insert into t values ( If error then rollback to Savepoint statement2; Insert into t values ( If error then rollback to 1 ); statement1; -1 ); statement2;

Database Replay tests almost all of the database workload, unlike third-party tools, which can only simulate part of the real workload in an Oracle database Compared to the third-party tools, the Database Replay tool is faster, and therefore you can compile the replay in a much shorter time period..

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The SQL Performance Analyzer, which together with the Database Replay feature forms the Total Replay feature offered by Oracle, enables you to test the impact of major system changes such as a database upgrade on SQL workload response time. The SQL Performance Analyzer analyzes and compares SQL performance before and after the system change and provides suggestions to improve any deterioration in performance. You can use the SQL Performance Analyzer to analyze potential changes in SQL performance following system changes such as database, application, operating system, or hardware upgrades; changes in initialization parameter settings; SQL tuning actions; and statistics gathering and schema changes. The SQL Performance Analyzer lets you know, ahead of an actual database upgrade, which of your SQL statements is possibly going to regress in performance, so you can take care of them. You

For programmers used to Sybase or SQL Server, this may be confusing at first. In those databases exactly the opposite is true. The triggers in those systems execute independently of the firing statement. If they encounter an error, the triggers must explicitly roll back their own work and then raise another error to roll back the triggering statement. Otherwise, the work done by a trigger could persist even if the triggering statement, or some other part of the statement, ultimately fails. In Oracle, this statement-level atomicity extends as deep as it needs to. If in the preceding example, the INSERT INTO T fires a trigger that updates another table, and that table has a trigger that deletes from another table (and so on, and so on), either all of the work succeeds or none of it does. You do not need to code anything special to ensure this it is just the way it works.

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.

32/0.65 103/1.08 198/1.50 334/1.98 447/2.68 550/3.28 672/3.92 763/4.45 868/5.02 965/5.60

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