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ICDE
2004
IEEE

Selectivity Estimation for String Predicates: Overcoming the Underestimation Problem

12 years 11 months ago
Selectivity Estimation for String Predicates: Overcoming the Underestimation Problem
Queries with (equality or LIKE) selection predicates over string attributes are widely used in relational databases. However, state-of-the-art techniques for estimating selectivities of string predicates are often biased towards severely underestimating selectivities. In this paper, we develop accurate selectivity estimators for string predicates that adapt to data and query characteristics, and which can exploit and build on a variety of existing estimators. A thorough experimental evaluation over real data sets demonstrates the resilience of our estimators to variations in both data and query characteristics.
Surajit Chaudhuri, Venkatesh Ganti, Luis Gravano
Added 01 Nov 2009
Updated 01 Nov 2009
Type Conference
Year 2004
Where ICDE
Authors Surajit Chaudhuri, Venkatesh Ganti, Luis Gravano
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