Sampling-based estimators for subset-based queries

Sampling-based estimators for subset-based queries We consider the problem of using sampling to estimate the result of an aggregation operation over a subset-based SQL query, where a subquery is correlated to an outer query by a NOT EXISTS, NOT IN, EXISTS or IN clause. We design an unbiased estimator for our query and prove that it is indeed unbiased. We then provide a second, biased estimator that makes use of the superpopulation concept from statistics to minimize the mean squared error of the resulting estimate. The two estimators are tested over an extensive set of experiments. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The VLDB Journal Springer Journals

Sampling-based estimators for subset-based queries

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Publisher
Springer-Verlag
Copyright
Copyright © 2009 by Springer-Verlag
Subject
Computer Science; Database Management
ISSN
1066-8888
eISSN
0949-877X
D.O.I.
10.1007/s00778-008-0095-0
Publisher site
See Article on Publisher Site

Abstract

We consider the problem of using sampling to estimate the result of an aggregation operation over a subset-based SQL query, where a subquery is correlated to an outer query by a NOT EXISTS, NOT IN, EXISTS or IN clause. We design an unbiased estimator for our query and prove that it is indeed unbiased. We then provide a second, biased estimator that makes use of the superpopulation concept from statistics to minimize the mean squared error of the resulting estimate. The two estimators are tested over an extensive set of experiments.

Journal

The VLDB JournalSpringer Journals

Published: Jan 1, 2009

References

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