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DRSS: Distributed RDF SPARQL Streaming

Abstract : 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.
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Contributor : Amadou Fall Dia <>
Submitted on : Friday, July 7, 2017 - 2:01:06 PM
Last modification on : Monday, February 3, 2020 - 3:58:03 PM




Amadou Fall Dia, Zakia Kazi-Aoul, Aliou Boly, Elisabeth Metais. DRSS: Distributed RDF SPARQL Streaming. Studies in Computational Intelligence, 2017, ⟨10.1007/978-3-319-61388-8_8⟩. ⟨hal-01558287⟩



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