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WAVES: Big Data Platform for Real-time RDF Stream Processing

Abstract : Processing data as they arrive has recently gained momentum to mine continuous, high-volume and unbounded sequence of data streams. Due to the heterogeneity and the multi-modality of this data, RDF is widely used to provide a unified metadata layer in streaming context. In response to this ever-increasing demand, a number of systems and languages were produced, aiming at RDF stream processing (RSP). However, most of them adopt a centralized execution approach which puts a barrier to ensure correct behavior and high scalability under certain circumstances such as concurrent queries and increasing input load. Only few systems sought to distribute processing, but their implementation is still in its infancy. None of them provide a full-fledged and production-ready RSP engine that is easy-to-use, supports all SPARQL 1.1 operators and adapted to industrial needs. As a solution, we present a distributed, fault-tolerant and scalable RSP system that exploits the Apache Storm framework.
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Submitted on : Thursday, March 22, 2018 - 9:31:52 AM
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  • HAL Id : hal-01740509, version 1


Houda Khrouf, Badre Belabbess, Laurent Bihanic, Gabriel Képéklian, Olivier Curé. WAVES: Big Data Platform for Real-time RDF Stream Processing. SR workshop at ISWC, 2016, Kobe, Japan. ⟨hal-01740509⟩



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