The Fittest Survives: An Adaptive Approach to Query Optimization.

Hongjun Lu, Kian-Lee Tan, Son Dao: The Fittest Survives: An Adaptive Approach to Query Optimization. VLDB 1995: 251-262

@inproceedings{DBLP:conf/vldb/LuTD95,
  author    = {Hongjun Lu and
               Kian-Lee Tan and
               Son Dao},
  editor    = {Umeshwar Dayal and
               Peter M. D. Gray and
               Shojiro Nishio},
  title     = {The Fittest Survives: An Adaptive Approach to Query Optimization},
  booktitle = {VLDB'95, Proceedings of 21th International Conference on Very
               Large Data Bases, September 11-15, 1995, Zurich, Switzerland},
  publisher = {Morgan Kaufmann},
  year      = {1995},
  isbn      = {1-55860-379-4},
  pages     = {251-262},
  ee        = {db/conf/vldb/LuTD95.html},
  crossref  = {DBLP:conf/vldb/95},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

Abstract

Traditionally, optimizers are "programmed" to optimize queries following aset of build- in procedures. However, optimizers should be robust to its changing environment to generate the fittest query execution plans. To realize adaptiveness, we propose and design an adaptive optimizer with two features. First, the search space and search strategy of the optimizer can be tuned by parameters to allow the optimizer to pick the one that fits best duringthe optimization process. Second, the optimizer features a "learning" capability for canned queries that allows existing plans to be incrementally replaced by "fitter" ones. An experimental study on large multi- join queries based on an analytical model is used to demonstrate the effectiveness of such an approach.

Copyright © 1995 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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Printed Edition

Umeshwar Dayal, Peter M. D. Gray, Shojiro Nishio (Eds.): VLDB'95, Proceedings of 21th International Conference on Very Large Data Bases, September 11-15, 1995, Zurich, Switzerland. Morgan Kaufmann 1995, ISBN 1-55860-379-4
Contents

References

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