Adaptive Selectivity Estimation Using Query Feedback.
Chung-Min Chen, Nick Roussopoulos:
Adaptive Selectivity Estimation Using Query Feedback.
SIGMOD Conference 1994: 161-172@inproceedings{DBLP:conf/sigmod/ChenR94,
author = {Chung-Min Chen and
Nick Roussopoulos},
editor = {Richard T. Snodgrass and
Marianne Winslett},
title = {Adaptive Selectivity Estimation Using Query Feedback},
booktitle = {Proceedings of the 1994 ACM SIGMOD International Conference on
Management of Data, Minneapolis, Minnesota, May 24-27, 1994},
publisher = {ACM Press},
year = {1994},
pages = {161-172},
ee = {http://doi.acm.org/10.1145/191839.191874, db/conf/sigmod/ChenR94.html},
crossref = {DBLP:conf/sigmod/94},
bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX
Abstract
In this paper, we propose a novel approach for estimating the
record selectivities of database queries. The real attribute
value distribution is adaptively approximated by a curve-fitting
function using a query feedback mechanism. This approach has
the advantages of requiring no extra database access overhead for
gathering statistics and of being able to continuously adapt the
value distribution through queries and updates. Experimental
results show that the estimation accuracy of this approach is
comparable to traditional methods based on statistics gathering.
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BibTeX
Printed Edition
Richard T. Snodgrass, Marianne Winslett (Eds.):
Proceedings of the 1994 ACM SIGMOD International Conference on Management of Data, Minneapolis, Minnesota, May 24-27, 1994.
ACM Press 1994 BibTeX
,
SIGMOD Record 23(2),
June 1994
Contents
[Abstract and Index Terms]
[Full Text in PDF Format, 1098 KB]
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Referenced by
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Combining Histograms and Parametric Curve Fitting for Feedback-Driven Query Result-size Estimation.
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BibTeX
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