RDFViewS: A Storage Tuning Wizard for RDF Applications

Goasdoué, François, Karanasos, Konstantinos, Leblay, Julien, Manolescu, Ioana

arXiv.org Artificial Intelligence 

In recent years, the significant growth of RDF data used in numerous applications has made its efficient and scalable manipulation an important issue. In this paper, we present RDFViewS, a system capable of choosing the most suitable views to materialize, in order to minimize the query response time for a specific SPARQL query workload, while taking into account the view maintenance cost and storage space constraints. Our system employs practical algorithms and heuristics to navigate through the search space of potential view configurations, and exploits the possibly available semantic information - expressed via an RDF Schema - to ensure the completeness of the query evaluation.

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