Castor: a Constraint-based SPARQL Engine with Active Filter Processing

Vianney Le Clément de Saint-Marcq 1 Yves Deville Christine Solnon 1 Pierre-Antoine Champin 2
1 M2DisCo - Geometry Processing and Constrained Optimization
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
2 SILEX - Supporting Interaction and Learning by Experience
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : Efficient evaluation of complex SPARQL queries is still an open research problem. State-of-the-art engines are based on relational database technologies. We approach the problem from the perspective of Constraint Programming (CP), a technology designed for solving NP-hard problems. Such technology allows us to exploit SPARQL filters early-on during the search instead of as a post-processing step. We propose Castor, a new SPARQL engine based on CP. Castor performs very competitively compared to state-of-the-art engines.
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Conference papers
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Submitted on : Wednesday, August 10, 2016 - 4:17:09 PM
Last modification on : Friday, January 11, 2019 - 4:49:52 PM

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Vianney Le Clément de Saint-Marcq, Yves Deville, Christine Solnon, Pierre-Antoine Champin. Castor: a Constraint-based SPARQL Engine with Active Filter Processing. 9th Extended Semantic Web Conference (ESWC), May 2012, Heraklion, Crète, Greece. Springer, pp.391-405, 2012, 〈10.1007/978-3-642-30284-8_33〉. 〈hal-01352967〉

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