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A SPARQL distributed query processing engine addressing both vertical and horizontal data partitions

Abstract : An increasing number of linked knowledge bases are openly accessible over the Internet. Distributed Query Processing (DQP) techniques enable querying multiple knowledge bases coherently. However, the precise DQP semantics is often overlooked, and query performance issues arise. In this paper, we propose a DQP engine for distributed RDF graphs, adopting a SPARQL-compliant DQP semantics. We improve performance through heuristics that generate Basic Graph Pattern-based sub-queries designed to maximise the parts of the query processed by the remote endpoints. We evaluate our DQP engine considering a query set representative of most common SPARQL clauses and different data distribution schemes. Results show a significant reduction of the number of remote queries executed and the query execution time while preserving completeness.
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Contributor : Abdoul Macina <>
Submitted on : Monday, November 28, 2016 - 2:22:47 PM
Last modification on : Tuesday, May 26, 2020 - 6:50:59 PM
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Abdoul Macina, Johan Montagnat, Olivier Corby. A SPARQL distributed query processing engine addressing both vertical and horizontal data partitions. BDA 2016 - 32ème Conférence sur la Gestion de Données - Principes, Technologies et Applications, Nov 2016, Poitiers, France. ⟨hal-01404165⟩

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