Inside the 11g SQL Performance Advisor
This is a preview from the forthcoming book “Oracle 11g New Features”, by Rampant TechPress, featuring John Garmany, plus Oracle ACE’s Steve Karam, Lutz Hartmann, and VJ Jain.
The declarative nature of the SQL syntax has always made it difficult to perform SQL tuning. The basic tenet of cost-based SQL optimization is that the person who writes a SQL query simply "declares" what columns they want to see (the SELECT clause), the tables where the columns reside (the FROM clause), and the filtering conditions (the WHERE clause). It's up to the SQL optimizer to always determine the optimal execution plan. This is a formidable challenge, especially in a dynamic environment, which is why Oracle introduced the 10g new feature of CBO dynamic sampling.
Oracle tuning consultants have know for many years that the best way to tune an Oracle system is to take a top-down approach, finding the optimal configuration for external factors (i.e. OS kernel settings, disk I/O subsystem), and determining the best overall setting for the Oracle instance (i.e. init.ora parameters).
Holistic tuning involves tuning a representative workload, adjusting global parameters in order to optimize as much SQL as possible. Only then, is it prudent to start tuning individual SQL statements. Many Oracle professional who adopt a bottom-up approach (tune the SQL first), find all of their hard-work un-done when a change is made to a global setting, such as one of the SQL optimizer parameters or recomputing optimizer statistics.
Oracle’s holistic SQL tuning approach is new, and given the misleading marketing name "fully automated SQL tuning". Holistic tuning is well-known to working DBA's who have been doing manual workload-based optimization since Oracle6. Now in 11g, Oracle gives us an automated method.
The Oracle 11g SQL Performance Analyzer (SPA), is primarily designed to speed up the holistic SQL tuning process, automating much of the tedium.
Once you create a workload (called a SQL Tuning Set, or STS), Oracle will repeatedly execute the workload, using sophisticated predictive models (using a regression testing approach) to accurately identify the salient changes to execution plans, based on your environmental changes.
Using SPA, we can predict the impact of system changes on a workload, and we can forecast changes in response times for SQL after making any change, like parameter changes, schema changes, hardware changes, OS changes, or Oracle upgrades; any change that influence SQL plans is a good candidate for SPA.
Read more here: http://www.dba-oracle.com/oracle11g/oracle_11g_sql_performance_advisor.htm
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