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Fast, Randomized Join-Order Selection - Why Use Transformations?

César A. Galindo-Legaria, Arjan Pellenkoft, Martin L. Kersten: Fast, Randomized Join-Order Selection - Why Use Transformations? VLDB 1994: 85-95
@inproceedings{DBLP:conf/vldb/Galindo-LegariaPK94,
  author    = {C{\'e}sar A. Galindo-Legaria and
               Arjan Pellenkoft and
               Martin L. Kersten},
  editor    = {Jorge B. Bocca and
               Matthias Jarke and
               Carlo Zaniolo},
  title     = {Fast, Randomized Join-Order Selection - Why Use Transformations?},
  booktitle = {VLDB'94, Proceedings of 20th International Conference on Very
               Large Data Bases, September 12-15, 1994, Santiago de Chile, Chile},
  publisher = {Morgan Kaufmann},
  year      = {1994},
  isbn      = {1-55860-153-8},
  pages     = {85-95},
  ee        = {db/conf/vldb/vldb94-85.html},
  crossref  = {DBLP:conf/vldb/94},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX

Abstract

We study the effectiveness of probabilistic selection of join-query evaluation plans, without reliance on tree transformation rules. Instead, each candidate plan is chosen uniformly at random from the space of valid evaluation orders. This leads to a transformation-free strategy where a sequence of random plans is generated and the plans are compared on their estimated costs. The success of this strategy depends on the ratio of ``good'' evaluation plans in the space of alternatives, the efficient generation of random candidates, and an accurate estimation of their cost. To avoid a biased exploration of the space, we solved the open problem of efficiently generating random, uniformly-distributed evaluation orders, for queries with acyclic graphs. This benefits any optimization or sampling scheme in which a random choice of (initial) query plans is required. A direct comparison with iterative improvement and simulated annealing, using a proven cost-evaluator, shows that our transformation-free strategy converges faster and yields solutions of comparable cost.

Copyright © 1994 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.


Online Paper

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Printed Edition

Jorge B. Bocca, Matthias Jarke, Carlo Zaniolo (Eds.): VLDB'94, Proceedings of 20th International Conference on Very Large Data Bases, September 12-15, 1994, Santiago de Chile, Chile. Morgan Kaufmann 1994, ISBN 1-55860-153-8
Contents BibTeX

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Referenced by

  1. Navin Kabra, David J. DeWitt: OPT++: An Object-Oriented Implementation for Extensible Database Query Optimization. VLDB J. 8(1): 55-78(1999)
  2. Ramana Yerneni, Chen Li, Jeffrey D. Ullman, Hector Garcia-Molina: Optimizing Large Join Queries in Mediation Systems. ICDT 1999: 348-364
  3. Michael Steinbrunn, Guido Moerkotte, Alfons Kemper: Heuristic and Randomized Optimization for the Join Ordering Problem. VLDB J. 6(3): 191-208(1997)
  4. Arjan Pellenkoft, César A. Galindo-Legaria, Martin L. Kersten: Duplicate-Free Generation of Alternatives in Transformation-Based Optimizers. DASFAA 1997: 117-124
  5. Myra Spiliopoulou, Michael Hatzopoulos, Yannis Cotronis: Parallel Optimization of Large Join Queries with Set Operators and Aggregates in a Parallel Environment Supporting Pipeline. IEEE Trans. Knowl. Data Eng. 8(3): 429-445(1996)
  6. William J. McKenna, Louis Burger, Chi Hoang, Melissa Truong: EROC: A Toolkit for Building NEATO Query Optimizers. VLDB 1996: 111-121
  7. Bennet Vance, David Maier: Rapid Bushy Join-order Optimization with Cartesian Products. SIGMOD Conference 1996: 35-46
  8. César A. Galindo-Legaria, Arjan Pellenkoft, Martin L. Kersten: Uniformly-Distributed Random Generation of Join Orders. ICDT 1995: 280-293
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