Optimization of dynamic query evaluation plans
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Efficient mid-query re-optimization of sub-optimal query execution plans
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Cost-based query scrambling for initial delays
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Learning table access cardinalities with LEO
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Dynamic Optimization of Index Scans Restricted by Booleans
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
LEO - DB2's LEarning Optimizer
Proceedings of the 27th International Conference on Very Large Data Bases
VLDB '92 Proceedings of the 18th International Conference on Very Large Data Bases
Query processing and optimization in Oracle Rdb
The VLDB Journal — The International Journal on Very Large Data Bases
Efficient query processing for data integration
Efficient query processing for data integration
Robust query processing through progressive optimization
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
LEO: An autonomic query optimizer for DB2
IBM Systems Journal
A framework for enforcing application policies in database systems
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Automatic SQL tuning in oracle 10g
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Efficient and scalable statistics gathering for large databases in Oracle 11g
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
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Execution plans for SQL statements have a significant impact on the overall performance of database systems. New optimizer statistics, configuration parameter changes, software upgrades and hardware resource utilization are among a multitude of factors that may cause the query optimizer to generate new plans. While most of these plan changes are beneficial or benign, a few rogue plans can potentially wreak havoc on system performance or availability, affecting critical and time-sensitive business application needs. The normally desirable ability of a query optimizer to adapt to system changes may sometimes cause it to pick a sub-optimal plan compromising the stability of the system. In this paper, we present the new SQL Plan Management feature in Oracle 11g. It provides a comprehensive solution for managing plan changes to provide stable and optimal performance for a set of SQL statements. Two of its most important goals are preventing sub-optimal plans from being executed while allowing new plans to be used if they are verifiably better than previous plans. This feature is tightly integrated with Oracle's query optimizer. SQL Plan Management is available to users via both command-line and graphical interfaces. We describe the feature and then, using an industrial-strength application suite, present experimental results that show that SQL Plan Management provides stable and optimal performance for SQL statements with no performance regressions.