DRSS: Distributed RDF SPARQL Streaming

  • Amadou Fall Dia
  • Zakia Kazi-Aoul
  • Aliou Boly
  • Elisabeth Métais
Part of the Studies in Computational Intelligence book series (SCI, volume 722)


In this work, we present DRSS, a distributed and scalable engine for RDF streams processing. DRSS proposes a new query syntax for continuous querying of RDF data streams. The system includes among others three efficient algorithms for (1) rewriting continuous queries sharing common sub-structures (2), SPARQL query partitioning across multiple computer nodes according to an efficient distribution strategy and (3) query-based data distribution for local processing of sub-queries minimizing data exchanged across nodes. Our system combines both real-time data from multiple sources and stored RDF processing. DRSS and its all algorithms are implemented using the real-time data processing platform Storm Framework, which provides parallelization mechanisms of query operators. The DRSS evaluation is conducted on a real dataset containing up to 1 million RDF graphs. Experiments and obtained results confirm the scalability and the effectiveness of our system.


DRSS RDF graphs streams Distributed sparql 



This work was performed under the FUI Waves project. This project aims to design and develop a distributed processing platform of massive data streams. The case study concerns the real-time monitoring of a drinking water distribution network.


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Amadou Fall Dia
    • 1
  • Zakia Kazi-Aoul
    • 1
  • Aliou Boly
    • 2
  • Elisabeth Métais
    • 3
  1. 1.LISITE LabISEPParisFrance
  2. 2.LID LabUCADDakar-FannSenegal
  3. 3.CEDRIC LabCNAMParisFrance

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