JOURNAL ARTICLE

On the rewriting and efficient computation of bound disjunctive datalog queries

Abstract

In this paper we present a technique for the optimization of bound queries over disjunctive deductive databases with constraints. The proposed approach consists of two distinct phases: i) the rewriting of queries for propagating bindings from the query goal into the program, and ii) the use of specialized algorithms computing rewritten queries. The rewriting of queries is based on the exploitation of a binding propagation technique which reduces the size of the data relevant to answer the query and, consequently, minimizes both the complexity of computing a single model and the whole number of models to be considered. As for general queries the rewriting technique does not ensure soundness, we present two sound and complete algorithms computing rewritten queries under brave and cautious reasoning. The efficiency of our algorithms has been proved by several experiments considering both classical search and optimization problems.

Keywords:
Rewriting Soundness Datalog Computer science Theoretical computer science Computation Query optimization Programming language Database

Metrics

1
Cited By
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FWCI (Field Weighted Citation Impact)
31
Refs
0.12
Citation Normalized Percentile
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Topics

Logic, Reasoning, and Knowledge
Physical Sciences →  Computer Science →  Artificial Intelligence
Semantic Web and Ontologies
Physical Sciences →  Computer Science →  Artificial Intelligence
Constraint Satisfaction and Optimization
Physical Sciences →  Computer Science →  Computer Networks and Communications
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