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Castor : a constraint-based SPARQL engine with active filter processing

Vianney Le Clement de Saint-Marcq 1
1 M2DisCo - Geometry Processing and Constrained Optimization
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : SPARQL is the standard query language for graphs of data in the SemanticWeb. Evaluating queries is closely related to graph matching problems, and has been shown to be NP-hard. State-of-the-art SPARQL engines solve queries with traditional relational database technology. Such an approach works well for simple queries that provide a clearly defined starting point in the graph. However, queries encompassing the whole graph and involving complex filtering conditions do not scale well. In this thesis we propose to solve SPARQL queries with Constraint Programming (CP). CP solves a combinatorial problem by exploiting the constraints of the problem to prune the search tree when looking for solutions. Such technique has been shown to work well for graph matching problems. We reformulate the SPARQL semantics by means of constraint satisfaction problems (CSPs). Based on this denotational semantics, we propose an operational semantics that can be used by off-theshelf CP solvers. Off-the-shelf CP solvers are not designed to handle the huge domains that come with SemanticWeb databases though. To handle large databases, we introduce Castor, a new SPARQL engine embedding a specialized lightweight CP solver. Special care has been taken to avoid as much as possible data structures and algorithms whosetime or space complexity are proportional to the database size. Experimental evaluations on well-known benchmarks show the feasibility and efficiency of the approach. Castor is competitive with state-of-the-art SPARQL engines on simple queries, and outperforms them on complex queries where filters can be actively exploited during the search.
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Vianney Le Clement de Saint-Marcq. Castor : a constraint-based SPARQL engine with active filter processing. Databases [cs.DB]. Université Claude Bernard - Lyon I, 2013. English. ⟨NNT : 2013LYO10275⟩. ⟨tel-01127937⟩

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