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Critical Oracle performance forecasting

 

Oracle is developing tools to predict upcoming performance bottlenecks, and Donald Burleson has outlined a possible approach to predict when an Oracle object might benefit from rebuilding:

 

http://dba-oracle.com/oracle_news/2005_2_17_table_index_rebuild_reorganization.htm

 

The goal is to create a reliable predictive model that will suggest tables and indexes which will measurably benefit from reorganization, predict the reduction in I/O (logical I/O - consistent gets and physical I/O - physical reads) after the reorganization, and suggest changes that will prevent a reoccurrence of the fragmentation (i.e. new pctfree, new blocksize, etc.):

 

http://www.dba-oracle.com/oracle_tips_predictive_modeling_10g.htm

 

In an OracleWorld 2003 presentation titled “Oracle Database 10g: The Self-Managing Database” by Sushil Kumar of Oracle Corporation, Kumar states that the Automatic Maintenance Tasks (AMT) Oracle10g feature will automatically detect and re-build sub-optimal indexes.“

 

In a superb paper titled “METRIC BASELINES: DETECTING AND EXPLAINING PERFORMANCE EVENTS IN EM 10GR2”, Presented at the RMOUG 2005 Training Days in Denver, John Beresniewicz of Oracle Corporation gives us a great preview into the new predictive modeling tools in Oracle 10g release 2 (10.2).

 

The metric baselines introduced in Enterprise Manager 10gR2 statistically characterize specific system metrics over time periods matched to system usage patterns. These statistical profiles of expected metric behavior are used to implement adaptive alert thresholds that can signal administrators when statistically unusual metric events occur.
 

Assuming that systems are normally stable and performance problems rare, it is reasonable to expect that actual performance events will be highly correlated with observed unusual values in some metric or other. Thus it is hoped that baseline-driven adaptive thresholds will both reduce configuration overhead for administrators and more reliably signal real problems than fixed alert thresholds.
 


 

 
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