Processing SPARQL queries over distributed RDF graphs

Processing SPARQL queries over distributed RDF graphs We propose techniques for processing SPARQL queries over a large RDF graph in a distributed environment. We adopt a “partial evaluation and assembly” framework. Answering a SPARQL query Q is equivalent to finding subgraph matches of the query graph Q over RDF graph G . Based on properties of subgraph matching over a distributed graph, we introduce local partial match as partial answers in each fragment of RDF graph G . For assembly, we propose two methods: centralized and distributed assembly. We analyze our algorithms from both theoretically and experimentally. Extensive experiments over both real and benchmark RDF repositories of billions of triples confirm that our method is superior to the state-of-the-art methods in both the system’s performance and scalability. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The VLDB Journal Springer Journals

Processing SPARQL queries over distributed RDF graphs

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Publisher
Springer Berlin Heidelberg
Copyright
Copyright © 2016 by Springer-Verlag Berlin Heidelberg
Subject
Computer Science; Database Management
ISSN
1066-8888
eISSN
0949-877X
D.O.I.
10.1007/s00778-015-0415-0
Publisher site
See Article on Publisher Site

Abstract

We propose techniques for processing SPARQL queries over a large RDF graph in a distributed environment. We adopt a “partial evaluation and assembly” framework. Answering a SPARQL query Q is equivalent to finding subgraph matches of the query graph Q over RDF graph G . Based on properties of subgraph matching over a distributed graph, we introduce local partial match as partial answers in each fragment of RDF graph G . For assembly, we propose two methods: centralized and distributed assembly. We analyze our algorithms from both theoretically and experimentally. Extensive experiments over both real and benchmark RDF repositories of billions of triples confirm that our method is superior to the state-of-the-art methods in both the system’s performance and scalability.

Journal

The VLDB JournalSpringer Journals

Published: Apr 1, 2016

References

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