Cardinality estimation using sample views with quality assurance

Accurate cardinality estimation is critically important to high-quality query optimization. It is well known that conventional cardinality estimation based on histograms or similar statistics may produce extremely poor estimates in a variety of situations, for example, queries with complex predicates, correlation among columns, or predicates containing user-defined functions. In this paper, we propose a new, general cardinality estimation technique that combines random sampling and materialized view technology to produce accurate estimates even in these situations. As a major innovation, we exploit feedback information from query execution and process control techniques to assure that estimates remain statistically valid when the underlying data changes. Experimental results based on a prototype implementation in Microsoft SQL Server demonstrate the practicality of the approach and illustrate the dramatic effects improved cardinality estimates may have. Categories and Subject Descript...

• Type: Conference
• Year: 2007
• Where: SIGMOD
• Authors: Per-Åke Larson, Wolfgang Lehner, Jingren Zhou, Peter Zabback
• Keywords: Accurate Cardinality Estimation, Cardinality Estimation Technique, Conventional Cardinality Estimation, Database, SIGMOD 2007