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Predicate Migration: Optimizing Queries with Expensive Predicates (1993)

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by Joseph M. Hellerstein , Michael Stonebraker
Citations:135 - 7 self
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BibTeX

@INPROCEEDINGS{Hellerstein93predicatemigration:,
    author = {Joseph M. Hellerstein and Michael Stonebraker},
    title = {Predicate Migration: Optimizing Queries with Expensive Predicates},
    booktitle = {},
    year = {1993},
    pages = {267--276}
}

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Abstract

. The traditional focus of relational query optimization schemes has been on the choice of join methods and join orders. Restrictions have typically been handled in query optimizers by "predicate pushdown" rules, which apply restrictions in some random order before as many joins as possible. These rules work under the assumption that restriction is essentially a zero-time operation. However, today's extensible and object-oriented database systems allow users to define time-consuming functions, which may be used in a query's restriction and join predicates. Furthermore, SQL has long supported subquery predicates, which may be arbitrarily time-consuming to check. Thus restrictions should not be considered zero-time operations, and the model of query optimization must be enhanced. In this paper we develop a theory for moving expensive predicates in a query plan so that the total cost of the plan --- including the costs of both joins and restrictions --- is minimal. We present an algorithm to implement the theory, as well as results of our implementation in POSTGRES. Our experience with the newly enhanced POSTGRES query optimizer demonstrates that correctly optimizing queries with expensive predicates often produces plans that are orders of magnitude faster than plans generated by a traditional query optimizer. The additional complexity of considering expensive predicates during optimization is found to be manageably small. 1

Citations

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371 The implementation of Postgres - Stonebraker, Rowe, et al. - 1990
155 Indexing in an ObjectOriented DBMS - Maier, Stein - 1986
139 Various optimizers for single---stage production - Smith - 1956
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99 The Sequoia 2000 Storage Benchmark - Stonebraker, Frew, et al. - 1993
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92 The postgres data model - Rowe, Stonebraker - 1987
56 Development and Implementation of an Object-Oriented DBMS - Maier, Stein - 1987
54 Statistical estimators for relational algebra expressions - Hou, Özsoyoglu, et al. - 1988
50 The Iris Architecture and Implementation - Wilkinson, Lyngbaek, et al. - 1990
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36 Sequencing with series-parallel precedence constraints - Monma, Sidney - 1979
35 On the optimal nesting for computing N-relational joins - Ibaraki, Kameda - 1984
34 Efficient sampling strategies for relational database operations - LIPTON, NAUGHTON, et al. - 1993
33 SEQUOIA 2000: Large Capacity Object Servers to Support Global Change Research - Stonebraker, Dozier - 1992
31 Managing persistent objects in a multi-level store - Stonebraker - 1991
30 A Polynomial Time Algorithm for Optimizing Join Queries - Swami, Iyer - 1992
29 Towards an open architecture for LDL - Chimenti, Gamboa, et al. - 1989
20 A performance study of query optimization algorithms on a database system supporting procedures - Jhingran - 1988
20 Extensible/Rulebased Query Rewrite Optimization in Starburst - Pirahesh, Hellerstein, et al. - 1992
14 Extending the POSTGRES database system to manage tertiary storage - Olson - 1992
11 As3ap - a comparative relational database benchmark - Turbyfill, Orji, et al. - 1989
10 An Optimal Evaluation of Boolean Expressions in an Online Query System - Hanani - 1977
7 Optimization of nested queries in a distributed relational database - Lohman, Daniels, et al. - 1984
6 Revisiting DBMS Benchmarks. Datamation - O'Neil - 1989
3 ONTOS Object SQL Guide - ONTOS - 1992
2 et al. The story of O - Deux - 1990
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