SPARQL query optimization on top of DHTs

Zoi Kaoudi, Kostis Kyzirakos, Manolis Koubarakis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

26 Citations (Scopus)

Abstract

We study the problem of SPARQL query optimization on top of distributed hash tables. Existing works on SPARQL query processing in such environments have never been implemented in a real system, or do not utilize any optimization techniques and thus exhibit poor performance. Our goal in this paper is to propose efficient and scalable algorithms for optimizing SPARQL basic graph pattern queries. We augment a known distributed query processing algorithm with query optimization strategies that improve performance in terms of query response time and bandwidth usage. We implement our techniques in the system Atlas and study their performance experimentally in a local cluster.

Original languageEnglish
Title of host publicationThe Semantic Web, ISWC 2010 - 9th International Semantic Web Conference, ISWC 2010, Revised Selected Papers
Pages418-435
Number of pages18
EditionPART 1
DOIs
Publication statusPublished - 1 Dec 2010
Externally publishedYes
Event9th International Semantic Web Conference, ISWC 2010 - Shanghai, China
Duration: 7 Nov 201011 Nov 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume6496 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other9th International Semantic Web Conference, ISWC 2010
CountryChina
CityShanghai
Period7/11/1011/11/10

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ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Kaoudi, Z., Kyzirakos, K., & Koubarakis, M. (2010). SPARQL query optimization on top of DHTs. In The Semantic Web, ISWC 2010 - 9th International Semantic Web Conference, ISWC 2010, Revised Selected Papers (PART 1 ed., pp. 418-435). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6496 LNCS, No. PART 1). https://doi.org/10.1007/978-3-642-17746-0_27