ComputingComputer ScienceInformation TechnologyCluster ComputingDatabasesDistributed SystemsDatabase ManagementDistributed Data ProcessingDistributed DatabasesQuery OptimizationQuery ProcessingStructured Query LanguageAd Hoc QueryingOptimizer DesignQuery ExecutionQuery Log AnalysisQuery Performance OptimizationSemantic Data ManagementSemantic Query OptimizationSemantic Web
The increasing interest in Semantic Web technologies has led not only to a rapid growth of semantic data on the Web but also to an increasing number of backend applications relying on efficient query processing. Confronted with such a trend, existing centralized state-of-the-art systems for storing RDF and processing SPARQL queries are no longer sufficient. In this paper, we introduce Partout, a distributed engine for fast RDF processing in a cluster of machines. We propose an effective approach for fragmenting RDF data sets based on a query log and allocating the fragments to hosts in a cluster of machines. Furthermore, Partout's query optimizer produces efficient query execution plans for ad-hoc SPARQL queries.
4
The RDF-3X engine for scalable management of RDF data
Thomas Neumann, Gerhard Weikum · The VLDB Journal · 2009 · 639 citations · Full text
Scalable SPARQL querying of large RDF graphs
Jiewen Huang, Daniel J. Abadi, Kun Ren · Proceedings of the VLDB Endowment · 2011 · 455 citations
Data summaries for on-demand queries over linked data
Andreas Harth, Katja Hose, Marcel Karnstedt et al. · 2010 · 209 citations