Magic Functions: A Technique to Optimize Extended Datalog Recursive Programs.
Georges Gardarin:
Magic Functions: A Technique to Optimize Extended Datalog Recursive Programs.
VLDB 1987: 21-30@inproceedings{DBLP:conf/vldb/Gardarin87,
author = {Georges Gardarin},
editor = {Peter M. Stocker and
William Kent and
Peter Hammersley},
title = {Magic Functions: A Technique to Optimize Extended Datalog Recursive
Programs},
booktitle = {VLDB'87, Proceedings of 13th International Conference on Very
Large Data Bases, September 1-4, 1987, Brighton, England},
publisher = {Morgan Kaufmann},
year = {1987},
isbn = {0-934613-46-X},
pages = {21-30},
ee = {db/conf/vldb/Gardarin87.html},
crossref = {DBLP:conf/vldb/87},
bibsource = {DBLP, http://dblp.uni-trier.de}
}
Abstract
Several methods have been proposed to compile recursive
Datalog programs. The most well-known perform a
rewriting of rules using MAGIC or PROBLEM predicates
in order to push selections before recursion. Rewritten rule
systems are generally complex and difficult to translate into
optimized relational algebra programs. Moreover, they often
generate too many results; thus, the query must be applied
to the generated results to eliminate non relevant answers.
In this paper, after a survey of the existing compilation
techniques which points out their limitations, we develop
the magic function method introduced in [Gardarin-
DeMaindreville86]. It is based on an understanding of the
query as a function which maps columns of a relation to
other columns. A query against recursive rules is then
translated into a fixpoint functional equation. The
resolution of this fixpoint equation using Tarski's theorem
leads to efficient computation of the query answer. In
particular, the derived algorithms push selections through
recursion, because selections appear as function arguments.
They generate only relevant answers to a given query,
without redundant data computation. The purpose
of this paper is the introduction of a generalized method to
obtain and resolve the fixpoint functional equation.
The method is general enough to handle non-binary rules, cyclic
rules and function symbols. The main advantages of the
method are : (1) It directly generates an optimized relational
algebra program. (2) It performs a symbolic precomputation
which permits rule redundancy elimination.
(3) It fully supports function symbols and range queries.
Copyright © 1987 by the VLDB Endowment.
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is by the permission of the Very Large Data Base
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Online Paper
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Printed Edition
Peter M. Stocker, William Kent, Peter Hammersley (Eds.):
VLDB'87, Proceedings of 13th International Conference on Very Large Data Bases, September 1-4, 1987, Brighton, England.
Morgan Kaufmann 1987, ISBN 0-934613-46-X
Contents
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Copyright © Mon Mar 15 03:55:50 2010
by Michael Ley (ley@uni-trier.de)