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Precomputing Datalog Evaluation Plans in Large-Scale Scenarios

Published online by Cambridge University Press:  20 September 2019

ALESSIO FIORENTINO Open the ORCID record for ALESSIO FIORENTINO [Opens in a new window] ,
NICOLA LEONE ,
MARCO MANNA Open the ORCID record for MARCO MANNA [Opens in a new window] ,
SIMONA PERRI Open the ORCID record for SIMONA PERRI [Opens in a new window]  and
JESSICA ZANGARI Open the ORCID record for JESSICA ZANGARI [Opens in a new window]
ALESSIO FIORENTINO
Affiliation:
Department of Mathematics and Computer Science, University of Calabria, Rende, Italy (e-mail: lastname@mat.unical.it) - https://www.mat.unical.it
NICOLA LEONE
Affiliation:
Department of Mathematics and Computer Science, University of Calabria, Rende, Italy (e-mail: lastname@mat.unical.it) - https://www.mat.unical.it
MARCO MANNA
Affiliation:
Department of Mathematics and Computer Science, University of Calabria, Rende, Italy (e-mail: lastname@mat.unical.it) - https://www.mat.unical.it
SIMONA PERRI
Affiliation:
Department of Mathematics and Computer Science, University of Calabria, Rende, Italy (e-mail: lastname@mat.unical.it) - https://www.mat.unical.it
JESSICA ZANGARI
Affiliation:
Department of Mathematics and Computer Science, University of Calabria, Rende, Italy (e-mail: lastname@mat.unical.it) - https://www.mat.unical.it
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Abstract

With the more and more growing demand for semantic Web services over large databases, an efficient evaluation of Datalog queries is arousing a renewed interest among researchers and industry experts. In this scenario, to reduce memory consumption and possibly optimize execution times, the paper proposes novel techniques to determine an optimal indexing schema for the underlying database together with suitable body-orderings for the Datalog rules. The new approach is compared with the standard execution plans implemented in DLV over widely used ontological benchmarks. The results confirm that the memory usage can be significantly reduced without paying any cost in efficiency.

Keywords

DatalogQuery AnsweringOntologiesQuery-planData Indexing
Type
Original Article
Information
Theory and Practice of Logic Programming , Volume 19 , Special Issue 5-6: 35th International Conference on Logic Programming , September 2019 , pp. 1073 - 1089
Copyright
© Cambridge University Press 2019 

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