SRBench: a streaming RDF/SPARQL benchmark

  • Authors:
  • Ying Zhang;Pham Minh Duc;Oscar Corcho;Jean-Paul Calbimonte

  • Affiliations:
  • Centrum Wiskunde & Informatica, Amsterdam, The Netherlands;Centrum Wiskunde & Informatica, Amsterdam, The Netherlands;Universidad Politécnica de Madrid, Spain;Universidad Politécnica de Madrid, Spain

  • Venue:
  • ISWC'12 Proceedings of the 11th international conference on The Semantic Web - Volume Part I
  • Year:
  • 2012

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Abstract

We introduce SRBench, a general-purpose benchmark primarily designed for streaming RDF/SPARQL engines, completely based on real-world data sets from the Linked Open Data cloud. With the increasing problem of too much streaming data but not enough tools to gain knowledge from them, researchers have set out for solutions in which Semantic Web technologies are adapted and extended for publishing, sharing, analysing and understanding streaming data. To help researchers and users comparing streaming RDF/SPARQL (strRS) engines in a standardised application scenario, we have designed SRBench, with which one can assess the abilities of a strRS engine to cope with a broad range of use cases typically encountered in real-world scenarios. The data sets used in the benchmark have been carefully chosen, such that they represent a realistic and relevant usage of streaming data. The benchmark defines a concise, yet comprehensive set of queries that cover the major aspects of strRS processing. Finally, our work is complemented with a functional evaluation on three representative strRS engines: SPARQLStream, C-SPARQL and CQELS. The presented results are meant to give a first baseline and illustrate the state-of-the-art.