2017 | OriginalPaper | Buchkapitel
QSMat: Query-Based Materialization for Efficient RDF Stream Processing
verfasst von : Christian Mathieu, Matthias Klusch, Birte Glimm
Erschienen in: Knowledge Engineering and Semantic Web
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Abstract
QSMat
, for efficient RDF data stream querying with flexible query-based materialization. Previous work accelerates either the maintenance of a stream window materialization or the evaluation of a query over the stream. QSMat
exploits knowledge of a given query and entailment rule-set to accelerate window materialization by avoiding inferences that provably do not affect the evaluation of the query. We prove that stream querying over the resulting partial window materializations with QSMat
is sound and complete with regard to the query. A comparative experimental performance evaluation based on the Berlin SPARQL benchmark and with selected representative systems for stream reasoning shows that QSMat
can significantly reduce window materialization size, reasoning overhead, and thus stream query evaluation time.