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| SELECT STATEMENT | | | HASH GROUP BY | | | HASH JOIN | | | TABLE ACCESS FULL | TIMES | | HASH JOIN | | | TABLE ACCESS BY INDEX ROWID| PRODUCTS | INDEX RANGE SCAN | PRODUCTS_PK | | TABLE ACCESS FULL | SALES |
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29 rows selected. SQL>
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CHAPTER 19 IM PR OVING DA TA BAS E PERFORM ANC E: S QL QUE RY OPTIMIZA TION
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The output shows that the SQL plan was captured automatically and is enabled and accepted. It also reveals that the plan isn t fixed.
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Tip When the SQL Tuning Advisor finds execution plans that are superior to the plans in the SQL plan baseline for that statement, it recommends a SQL profile. Once you accept the recommendation for implementing the SQL profile, the SQL Tuning Advisor adds the tuned plan to the SQL plan baseline.
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The database stores SQL plan baseline information in the SQL Management Base (SMB), which is stored in the Sysaux tablespace. You can control the sizing and retention period of the SMB by setting the parameters SPACE_BUDGE_PERCENT and PLAN_RETENTION_WEEKS, using the DBMS_SPM package. The following query reveals the current values of the two parameters: SQL> SELECT parameter_name, parameter_value FROM dba_sql_management_config; PARAMETER_NAME ----------------------SPACE_BUDGET_PERCENT PLAN_RETENTION_WEEKS SQL> The SPACE_BUDGET_PERCENT parameter controls the percentage of space the SMB can occupy in the Sysaux tablespace. The default is 10 percent, and you can set it anywhere between 1 and 50 percent. You can purge outdated SQL plan baselines or SQL profiles from the SMB to clear up space, or you can increase the size of the Sysaux tablespace. You can change the value of the SPACE_BUDGET_PERCENT parameter by executing the CONFIGURE parameter, as shown here: SQL> EXEC dbms_spm.configure ('space_budget_percent', 40); The CONFIGURE procedure specifies that the SPM can use up to 40 percent of the space in the Sysaux tablespace. The database executes a weekly purging job to remove unused SQL baselines. The database removes any SQL baselines that it hasn t used in over a year (53 weeks). You can adjust the plan retention period by executing the CONFIGURE procedure as shown here: SQL> exec dbms_spm.configure ('plan_retention_weeks', 105); You can also remove specific baselines from the SMBA, as shown in the following example: SQL> exec dbms_spm.purge_sql_plan_baseline(''SYS_SQL_PLAN_b5429511dd6ab0f'); You can query the DBA_SQL_MANAGEMENT_CONFIG view for the current space and retention settings of the SMB. PARAMETER_VALUE -----------------30 53
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Parallel execution of statements can make SQL run more quickly, and it s especially suitable for large warehouse-type databases. You can set the parallel option at the database or table level. If you increase the degree of parallelism of a table, Oracle could decide to perform more full table scans instead of
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CHAPTER 19 IMPROV IN G DA TA BAS E PERFORMAN CE: SQL QUERY OPTIMIZA TION
using an index, because the cost of a full table scan may now be lower than the cost of an index scan. If you want to use parallel operations in an OLTP environment, make sure you have enough processors on your machine so the CPU doesn t become a bottleneck.
Other DBA Tasks
The DBA must perform certain tasks regularly to optimize the performance of the application. Some of these fall under the routine administrative chores, and the following sections cover some of the important DBA tasks related to performance tuning.
Collecting System Statistics
Even if you re using the Automatic Optimizer Statistics Collection feature, Oracle won t collect system statistics. As explained earlier in this chapter, you must collect system statistics yourself, so the Oracle optimizer can accurately evaluate alternate execution plans.
Refreshing Statistics Frequently
This section applies only if you have turned off the automatic statistics collection process for some reason. Refreshing statistics frequently is extremely important if you re using the CBO and your data is subject to frequent changes. How often you run the DBMS_STATS package to collect statistics depends on the nature of your data. For applications with a moderate number of DML transactions, a weekly gathering of statistics will suffice. If you have reason to believe that your data changes substantially daily, schedule the statistics collection on a daily basis.
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