Cost-based Optimization of Complex Scientific Queries

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Cost-based Optimization of Complex Scientific Queries
High energy physics scientists analyze large amounts of data looking for interesting events when particles collide. These analyses are easily expressed using complex queries that filter events. We developed a cost model for aggregation operators and other functions used in such queries and show that it substantially improves performance. However, the query optimizer still produces suboptimal plans because of estimate errors. Furthermore, the optimization is very slow because of the large query size. We improved the optimization by a profiled grouping strategy where the scientific query is first automatically fragmented into subqueries based on application knowledge. Each fragment is then independently profiled on a sample of events to measure real execution cost and cardinality. An optimized fragmented query is shown to execute faster than a query optimized with the cost model alone. Furthermore, the total optimization time, including fragmentation and profiling, is substantially impr...
Ruslan Fomkin, Tore Risch
Added 04 Jun 2010
Updated 04 Jun 2010
Type Conference
Year 2007
Authors Ruslan Fomkin, Tore Risch
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