01528nas a2200241 4500008004100000245006600041210006300107260003500170300001400205490000900219520081200228653001201040653002501052653002601077653001101103100002301114700001701137700002101154700002001175700001901195700001701214856005501231 2013 eng d00aD-SPARQ: Distributed, Scalable and Efficient RDF Query Engine0 aDSPARQ Distributed Scalable and Efficient RDF Query Engine aSydney, AustraliabCEUR-WS.org a261–2640 v10353 a

We present D-SPARQ, a distributed RDF query engine that combines the MapReduce processing framework with a NoSQL distributed data store, MongoDB. The performance of processing SPARQL queries mainly depends on the efficiency of handling the join operations between the RDF triple patterns. Our system features two unique characteristics that enable efficiently tackling this challenge: 1) Identifying specific patterns of the input queries that enable improving the performance by running different parts of the query in a parallel mode. 2) Using the triple selectivity information for reordering the individual triples of the input query within the identified query patterns. The preliminary results demonstrate the scalability and efficiency of our distributed RDF query engine.

10aD-SPARQ10aDistributed Querying10aScalable RDF querying10aSPARQL1 aMutharaju, Raghava1 aSakr, Sherif1 aSala, Alessandra1 aHitzler, Pascal1 aBlomqvist, Eva1 aGroza, Tudor uhttp://ceur-ws.org/Vol-1035/iswc2013_poster_21.pdf