Abstract
We study the problem of SPARQL query optimization on top of distributed hash tables. Existing works on SPARQL query processing in such environments have never been implemented in a real system, or do not utilize any optimization techniques and thus exhibit poor performance. Our goal in this paper is to propose efficient and scalable algorithms for optimizing SPARQL basic graph pattern queries. We augment a known distributed query processing algorithm with query optimization strategies that improve performance in terms of query response time and bandwidth usage. We implement our techniques in the system Atlas and study their performance experimentally in a local cluster. © 2010 Springer-Verlag.
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CITATION STYLE
Kaoudi, Z., Kyzirakos, K., & Koubarakis, M. (2010). SPARQL query optimization on top of DHTs. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6496 LNCS, pp. 418–435). Springer Verlag. https://doi.org/10.1007/978-3-642-17746-0_27
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