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On Efficient Processing of Linked Stream Data

  • Conference paper
On the Move to Meaningful Internet Systems: OTM 2014 Conferences (OTM 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8841))

Abstract

Today, many application areas require continuous processing of data streams in an efficient manner and real-time fashion. Processing these continuous flows of data, integrating dynamic data with other data sources, and providing the required semantics lead to real challenges. Thus, Linked Stream Data (LSD) has been proposed which combines two concepts: Linked Open Data and Data Stream Processing (DSP). Recently, several LSD engines have been developed, including C-SPARQL and CQELS, which are based on SPARQL extensions for continuous query processing. However, this SPARQL-centric view makes it difficult to express complex processing pipelines. In this paper, we propose a LSD engine based on a more general stream processing approach. Instead of a variant of SPARQL, our engine provides a dataflow specification language called PipeFlow which is compiled into native code. PipeFlow supports native stream processing operators (e.g., window, aggregates, and joins), complex event processing as well as RDF data transformation operators such as tuplifier and triplifier to efficiently support LSD queries and provide a higher degree of expressiveness. We discuss the main concepts addressing the challenges of LSD processing and describe the usage of these concepts for processing queries from LSBench and SRBench. We show the effectiveness of our system in terms of query execution times through a comparison with existing systems as well as through a detailed performance analysis of our system implementation.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Automation, Technische Universität Ilmenau, Germany

    Omran Saleh & Kai-Uwe Sattler

Authors
  1. Omran Saleh
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  2. Kai-Uwe Sattler
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Editor information

Editors and Affiliations

  1. TU Graz, Rechbauerstraße 12, 8010, Graz, Austria

    Robert Meersman

  2. CRAN, Campus Sciences, University of Lorraine, BP 70239, 54506, Vandoevre-les-Nancy, France

    Hervé Panetto

  3. Computer Science and Computer Engineering, La Trobe University, 3086, Melbourne, VIC, Australia

    Tharam Dillon

  4. Laboratory for Enterprise Knowledge and Systems (LEKS), IASI - CNR, Viale Manzoni 30, 00185, Rome, Italy

    Michele Missikoff

  5. School of Software, Tsinghua University, 100084, Beijing, China

    Lin Liu

  6. PROS Research Center, Camino de Vera, Universidad Politècnica de València, 46022, Valencia, Spain

    Oscar Pastor

  7. Department of Electronics, Computer Science and Systems, Univeristy of Calabria, Via P. Bucci, 41C, 87036, Rende, Cosenza, Italy

    Alfredo Cuzzocrea

  8. School of Computer Science and Information Technology, RMIT, Australia

    Timos Sellis

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Saleh, O., Sattler, KU. (2014). On Efficient Processing of Linked Stream Data. In: Meersman, R., et al. On the Move to Meaningful Internet Systems: OTM 2014 Conferences. OTM 2014. Lecture Notes in Computer Science, vol 8841. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45563-0_43

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  • DOI: https://doi.org/10.1007/978-3-662-45563-0_43

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-45562-3

  • Online ISBN: 978-3-662-45563-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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