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SPARQLGX: Efficient Distributed Evaluation of SPARQL with Apache Spark

Damien Graux 1 Louis Jachiet 1 Pierre Genevès 1, * Nabil Layaïda 1 
* Corresponding author
1 TYREX - Types and Reasoning for the Web
Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d'Informatique de Grenoble
Abstract : sparql is the w3c standard query language for querying data expressed in the Resource Description Framework (rdf). The increasing amounts of rdf data available raise a major need and research interest in building efficient and scalable distributed sparql query eval-uators. In this context, we propose sparqlgx: our implementation of a distributed rdf datastore based on Apache Spark. sparqlgx is designed to leverage existing Hadoop infrastructures for evaluating sparql queries. sparqlgx relies on a translation of sparql queries into exe-cutable Spark code that adopts evaluation strategies according to (1) the storage method used and (2) statistics on data. We show that spar-qlgx makes it possible to evaluate sparql queries on billions of triples distributed across multiple nodes, while providing attractive performance figures. We report on experiments which show how sparqlgx compares to related state-of-the-art implementations and we show that our approach scales better than these systems in terms of supported dataset size. With its simple design, sparqlgx represents an interesting alternative in several scenarios.
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Submitted on : Tuesday, July 12, 2016 - 6:57:25 PM
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Damien Graux, Louis Jachiet, Pierre Genevès, Nabil Layaïda. SPARQLGX: Efficient Distributed Evaluation of SPARQL with Apache Spark. The 15th International Semantic Web Conference, Oct 2016, Kobe, Japan. ⟨10.1007/978-3-319-46547-0_9⟩. ⟨hal-01344915⟩



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