Probabilistic Optimization of Top N Queries.

Donko Donjerkovic, Raghu Ramakrishnan: Probabilistic Optimization of Top N Queries. VLDB 1999: 411-422

@inproceedings{DBLP:conf/vldb/DonjerkovicR99,
  author    = {Donko Donjerkovic and
               Raghu Ramakrishnan},
  editor    = {Malcolm P. Atkinson and
               Maria E. Orlowska and
               Patrick Valduriez and
               Stanley B. Zdonik and
               Michael L. Brodie},
  title     = {Probabilistic Optimization of Top N Queries},
  booktitle = {VLDB'99, Proceedings of 25th International Conference on Very
               Large Data Bases, September 7-10, 1999, Edinburgh, Scotland,
               UK},
  publisher = {Morgan Kaufmann},
  year      = {1999},
  isbn      = {1-55860-615-7},
  pages     = {411-422},
  ee        = {db/conf/vldb/DonjerkovicR99.html},
  crossref  = {DBLP:conf/vldb/99},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

Abstract

The problem of finding the best answers to a query quickly, rather than finding all answers, is of increasing importance as relational databases are applied in multimedia and decision-support domains. An approach to efficiently answering such "Top N" queries is to augment the query with an additional selection that prunes away the unwanted portion of the answer set. The risk is that if the selection returns fewer than the desired number of answers, the execution must be restarted (with a less selective filter). We propose a new, probabilistic approach to query optimization that quantifies this risk and seeks to minimize overall cost including the cost of possible restarts. We also present an experimental study to demonstrate that probabilistic Top N query optimization can significantly reduce the average query execution time with relatively modest increase in the optimization time.

Copyright © 1999 by the VLDB Endowment. Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the VLDB copyright notice and the title of the publication and its date appear, and notice is given that copying is by the permission of the Very Large Data Base Endowment. To copy otherwise, or to republish, requires a fee and/or special permission from the Endowment.

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Malcolm P. Atkinson, Maria E. Orlowska, Patrick Valduriez, Stanley B. Zdonik, Michael L. Brodie (Eds.): VLDB'99, Proceedings of 25th International Conference on Very Large Data Bases, September 7-10, 1999, Edinburgh, Scotland, UK. Morgan Kaufmann 1999, ISBN 1-55860-615-7
Contents

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