Performance Evaluation of Data Intensive Logic Programs

Bancilhon, François; Ramakrishnan, Raghu

doi:10.1016/b978-0-934613-40-8.50016-6

Cited by 64 publications

(38 citation statements)

References 11 publications

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“…We have assumed that the base relations A, B and C, associated, respectively, with the predicates a, b and c, have a "cylindric structure" [6]. We represent the a We are assuming that it is known that the database is acyclic.…”

Section: Resultsmentioning

confidence: 99%

“…The effectiveness of the bottom-up execution for bound queries is based on optimizations techniques that transform the original program into an equivalent one that efficiently exploits bindings during fixpoint-based computation [5,6,8,14,22,23,26,31]. These rewriting techniques give the bottom-up computation a wider applicability range than the top-down computation typical of Prolog, and have been used successfully in several deductive database prototypes.…”

Section: Motivationsmentioning

confidence: 99%

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Grammars and Automata to Optimize Chain Logic Queries

Greco

Saccà

Zaniolo

1999

Int. J. Found. Comput. Sci.

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The critical problem of finding efficient implementations for recursive queries with bound arguments offers many open challenges of practical and theoretical import. In particular, we need methods that are effective for the general case, such as non-linear programs, as well as for specialized cases, such as left-recursive linear programs. In this paper, we propose a novel approach that solves this problem for chain queries, i.e., for queries where bindings are propagated from arguments in the head to arguments in the tail of the rules, in a chain-like fashion. The method, called pushdown method, is based on the fact that each chain query can be associated with a context-free language, and that a pushdown automaton recognizing this language can be emulated by rewriting the query as a particular factorized left-linear program. The proposed method generalizes and unifies previous techniques such as the 'counting' and 'right-, left-, mixed-linear' methods. It succeeds in reducing many non-linear programs to query-equivalent linear ones.

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Section: Resultsmentioning

confidence: 99%

Section: Motivationsmentioning

confidence: 99%

Grammars and Automata to Optimize Chain Logic Queries

Greco

Saccà

Zaniolo

1999

Int. J. Found. Comput. Sci.

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“…Note that in a bottom-up evaluation, the transformed program (the demand algorithm) will neverperform more work than the untransformed program (the exhaustive algorithm) would-modulo a small amount of overhead for computing magic facts, which are reported to be only a small fraction of the generated facts [4]. In practice, the demand algorithm usually performs far less work than the exhaustive algorithm.…”

Section: End Of Examplementioning

confidence: 99%

Solving demand versions of interprocedural analysis problems

Reps

1994

Lecture Notes in Computer Science

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This paper concerns the solution of demand versions of interprocedural analysis problems. In a demand version of a program-analysis problem, some piece of summary information (e.g.,t he dataflowf acts holding at a givenp oint) is to be reported only for a single program element of interest (or a small number of elements of interest). Because the summary information at one program point typically depends on summary information from other points, an important issue is to minimize the number of other points for which (transient) summary information is computed and/or the amount of information computed at those points. The paper describes howa lgorithms for demand versions of program-analysis problems can be obtained from their exhaustive counterparts essentially for free, by applying the so-called "magic-sets" transformation that was developed in the logic-programming and deductive-database communities.

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“…Most of these strategies rewrite the original program into a queryequivalent new program which can be evaluated more efficiently by the seminaive algorithm [2,14,4,3,9,10,12]. The improved efficiency of the rewritten program is due to the fact that it restricts the search to the portion of the underlying database that is relevant to the query.…”

Section: Introductionmentioning

confidence: 99%

“…These specialized techniques are important, since many programs of practical interest contain only linear recursive rules, to which these techniques apply, yielding an order of magnitude improvement in efficiency [16]. Comparisons between the magic-set method and the counting method can be found in [3,8].…”

Section: Introductionmentioning

confidence: 99%