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Chapter 9
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Performance Management Enterprise wide endeavor Research and ascertain all performance problems – not just DBMS Five factors influence DB performance
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DB performance Five factors –Workload – combination of online transactions, batch jobs, ad hoc queries, datawarehousing analysis and system –Throughput – overall capability of the computer to process data –Resources – hardware and software tools at the disposal of the system
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Performance continued –Optimization – to optimize such things as queries, SQL formulation, database parameters –Contention – condition where two or more components of the workload are attempting to use a single resources in a conflicting way (dual updates to same piece of data, etc.)
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Poor performance Table scans Lack of appropriate indexes Improper indexing choices Not using the available indexes Outdated database statistics Tables joined in a suboptimal order
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Poor Performance continued Application joins instead of more efficient SQL joins Improper join method (nested loops, etc.) Efficient SQL inside of inefficient application code (loops)
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Poor performance continued Inefficient subquery formulation (exists, not exists, etc.) Unnecessary sorting
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80/20 Rule Pareto Principle –80% o the results come from 20% of the effort –DBA should concentrate on the most likely causes of performance problems first, because he will receive a high return on his tuning investment
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Other potential problems Memory allocation (buffer/cache) Logging options (log cache, log size, rollback statements) I/O efficiency (separation of tables and indexes on disk, database size, fragmented and extended files)
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Problems continued Overall application & database workload on server Database schema definitions
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Performance Management Three specific components –Monitoring – scanning the environment, reviewing the output of instrumentation facilities, and watching the system as it runs (identifies problems) –Analysis – looking at what was collected from monitoring – done by DBA or others
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Performance continued –Optimization – corrective action; some may be done automatically by the system, others are generated
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Management Reactive performance management –Planning for the unplanned performance problems –Manual –Time consuming
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Management continued Proactive performance management –Combined forethought, planning and automation to minimize reactive monitoring and tuning –Reduces amount of time, effort and human error
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Life Cycle Life cycle needs to be monitored from the beginning Problems caught earlier on are less costly and easier to fix
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Historical Trending Capturing and analyzing resource usage trends and performance statistics over time Predict needs for hardware upgrades Track key performance statistics (put in tracker tables)
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Service Level Management Disciplined, proactive methodology and procedures used to ensure that adequate levels of service are delivered to all IT users at acceptable costs –Problems with silos
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Performance Tuning System tuning Database tuning Application tuning
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Tuning tools Performance monitors –Realtime, near time (intervals) and trends Performance estimation tools Capacity planning tools –Includes what if scenarios
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Tools continued SQL analysis and tuning tools Advisory tools Systems analysis and tuning tools
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Database tuning tools Reorganization tools (rebuild) Compression tools Sorting tools
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Performance Basics Do not over-tune Remain focused Do not panic Communicate clearly Accept reality
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