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2017 | OriginalPaper | Chapter

An Adaptive Framework for RDF Stream Processing

Authors : Qiong Li, Xiaowang Zhang, Zhiyong Feng

Published in: Web and Big Data

Publisher: Springer International Publishing

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Abstract

In this paper, we propose a novel framework for RDF stream processing named PRSP. Within this framework, the evaluation of C-SPARQL queries on RDF streams can be reduced to the evaluation of SPARQL queries on RDF graphs. We prove that the reduction is sound and complete. With PRSP, we implement several engines to support C-SPARQL queries by employing current SPARQL query engines such as Jena, gStore, and RDF-3X. The experiments show that PRSP can still maintain the high performance by applying those engines in RDF stream processing, although there are some slight differences among them. Moreover, taking advantage of PRSP, we can process large-scale RDF streams in a distributed context via distributed SPARQL engines, such as gStoreD and TriAD. Besides, we can evaluate the performance and correctness of existing SPARQL query engines in processing RDF streams in a unified way, which amends the evaluation of them ranging from static RDF data to dynamic RDF data.

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Metadata
Title
An Adaptive Framework for RDF Stream Processing
Authors
Qiong Li
Xiaowang Zhang
Zhiyong Feng
Copyright Year
2017
DOI
https://doi.org/10.1007/978-3-319-63579-8_33

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