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QSMat: Query-Based Materialization for Efficient RDF Stream Processing

  • Christian MathieuEmail author
  • Matthias Klusch
  • Birte Glimm
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 786)

Abstract

This paper presents a novel approach, QSMat, for efficient RDF data stream querying with flexible query-based materialization. Previous work accelerates either the maintenance of a stream window materialization or the evaluation of a query over the stream. QSMat exploits knowledge of a given query and entailment rule-set to accelerate window materialization by avoiding inferences that provably do not affect the evaluation of the query. We prove that stream querying over the resulting partial window materializations with QSMat is sound and complete with regard to the query. A comparative experimental performance evaluation based on the Berlin SPARQL benchmark and with selected representative systems for stream reasoning shows that QSMat can significantly reduce window materialization size, reasoning overhead, and thus stream query evaluation time.

Notes

Acknowledgments

This research was partially supported by the German Federal Ministry for Education and Research (BMB+F) in the project INVERSIV and the European Commission in the project CREMA.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Christian Mathieu
    • 1
    Email author
  • Matthias Klusch
    • 2
  • Birte Glimm
    • 3
  1. 1.Computer Science DepartmentSaarland UniversitySaarbrueckenGermany
  2. 2.German Research Center for Artificial IntelligenceSaarbrueckenGermany
  3. 3.Institute of Artificial Intelligence, University of UlmUlmGermany

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