Inproceedings3762

PRoST: Distributed Execution of SPARQL Queries Using Mixed Partitioning Strategies

Matteo Cossu, Michael Färber, Georg Lausen

Published: 2018

Buchtitel: Proceedings of the 21st International Conference on Extending Database Technology (EDBT 2018)
Seiten: 469-472
Verlag: OpenProceedings.org

Referierte Veröffentlichung

BibTeX

Kurzfassung
The rapidly growing size of RDF graphs in recent years necessitates distributed storage and parallel processing strategies. To obtain efficient query processing using computer clusters a wide variety of different approaches have been proposed. Related tothe approach presented in the current paper are systems built on top of Hadoop HDFS, for example using Apache Accumulo or using Apache Spark. We present a new RDF store called PRoST (Partitioned RDF on Spark Tables) based on Apache Spark. PRoST introduces an innovative strategy that combines the Vertical Partitioning approach with the Property Table, two preexisting models for storing RDF datasets. We demonstrate that our proposal outperforms state-of-the-art systems w.r.t. the runtime for a wide range of query types and without any extensive precomputing phase.

ISSN: 2367-2005
Download: Media:PRoST_EDBT2018.pdf
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Forschungsgruppe

Web Science

Forschungsgebiet

Information Retrieval, Skalierbares Data Mining