Precomputing Datalog Evaluation Plans in Large-Scale Scenarios

Author:

FIORENTINO ALESSIOORCID,LEONE NICOLA,MANNA MARCOORCID,PERRI SIMONAORCID,ZANGARI JESSICAORCID

Abstract

AbstractWith 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.

Publisher

Cambridge University Press (CUP)

Subject

Artificial Intelligence,Computational Theory and Mathematics,Hardware and Architecture,Theoretical Computer Science,Software

Reference21 articles.

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