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Department of Computer Science

University of California, Santa Barbara

Abstract

Query Estimation By Adaptive Sampling

by: Yi-Leh Wu, Divyakant Agrawal, Amr El Abbadi

Abstract:

The ability to provide accurate and efficient result estimations of user queriesis very important for the query optimizer in database systems.In this paper, we show that the traditional estimation techniques with data reductionpoints of view do not produce satisfiable estimation results ifthe query patterns are dynamically changing.We further show that to reduce query estimation error, instead ofaccurately capturing the data distribution, it is moreeffective to capture the user query patterns.In this paper, we propose query estimation techniques that canadapt to user query patterns for more accurateestimates of the size of selection or range queriesover databases.

Keywords:

adaptive sampling, cumulative frequency distribution, query estimation, range query

Date:

19 November 2001

Document: 2001-19

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