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YABench: A Comprehensive Framework for RDF Stream Processor Correctness and Performance Assessment

  • Maxim Kolchin
  • Peter Wetz
  • Elmar Kiesling
  • A Min Tjoa
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9671)

Abstract

RDF stream processing (RSP) has become a vibrant area of research in the semantic web community. Recent advances have resulted in the development of several RSP engines that leverage semantics to facilitate reasoning over flows of incoming data. These engines vary greatly in terms of implemented query syntax, their evaluation and operational semantics, and in various performance dimensions. Existing benchmarks tackle particular aspects such as functional coverage, result correctness, or performance. None of them, however, assess RSP engine behavior comprehensively with respect to all these dimensions. In this paper, we introduce YABench, a novel benchmarking framework for RSP engines. YABench extends the concept of correctness checking and provides a flexible and comprehensive tool set to analyze and evaluate RSP engine behavior. It is highly configurable and provides quantifiable and reproducible results on correctness and performance characteristics. To validate our approach, we replicate results of the existing CSRBench benchmark with YABench. We then assess two well-established RSP engines, CQELS and C-SPARQL, through more comprehensive experiments. In particular, we measure precision, recall, performance, and scalability characteristics while varying throughput and query complexity. Finally, we discuss implications on the development of future stream processing engines and benchmarks.

Keywords

Operational Semantic Query Result Smart City Memory Consumption Input Stream 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

The work done by Peter Wetz was partially funded by TU Wien through the Doctoral College Environmental Informatics. The work done by Maxim Kolchin was partially funded by the Government of the Russian Federation, Grant 074-U01.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Maxim Kolchin
    • 1
  • Peter Wetz
    • 2
  • Elmar Kiesling
    • 2
  • A Min Tjoa
    • 2
  1. 1.ITMO UniversitySaint PetersburgRussia
  2. 2.TU WienViennaAustria

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