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Author Bruno, N. ♦ Chaudhuri, S. ♦ Ramamurthy, R.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2009
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Query processing ♦ Cost function ♦ Database systems ♦ Constraint optimization ♦ Data engineering ♦ USA Councils ♦ Relational databases ♦ Calibration ♦ Costing ♦ Hardware
Abstract Commercial database systems expose query hints to address situations in which the optimizer chooses a poor plan for a given query. However, current query hints are not flexible enough to deal with a variety of non-trivial scenarios. In this paper, we introduce a hinting framework that enables the specification of rich constraints to influence the optimizer to pick better plans. We show that while our framework unifies previous approaches, it goes considerably beyond existing hinting mechanisms, and can be implemented efficiently with moderate changes to current optimizers.
ISBN 9781424434220
ISSN 10844627
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2009-03-29
Publisher Place China
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Size (in Bytes) 532.11 kB
Page Count 12
Starting Page 469
Ending Page 480


Source: IEEE Xplore Digital Library