QSMat: Query-Based Materialization for Efficient RDF Stream Processing View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2017-10-18

AUTHORS

Christian Mathieu , Matthias Klusch , Birte Glimm

ABSTRACT

This paper presents a novel approach, 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. More... »

PAGES

159-174

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-69548-8_12

DOI

http://dx.doi.org/10.1007/978-3-319-69548-8_12

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1092251930


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