Precomputing Datalog Evaluation Plans in Large-Scale Scenarios. Issue 5 (September 2019)

• Record Type: Journal Article
• Authors: FIORENTINO, ALESSIO; LEONE, NICOLA; MANNA, MARCO; PERRI, SIMONA; ZANGARI, JESSICA
• Is Part Of: Theory and practice of logic programming. Volume 19:Issue 5/6(2019)
• Page Start: 1073
• Page End: 1089
• Publication Date: 2019-09
• Subjects: Datalog, -- Query Answering, -- Ontologies, -- Query-plan, -- Data Indexing; Logic programming -- Periodicals; Artificial intelligence -- Computer programs -- Periodicals; Constraint programming (Computer science) -- Periodicals; 005.115
• DOI: 10.1017/S147106841900036X
• Languages: English
• ISSNs: 1471-0684

Abstract

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.