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On the Selection of SPARQL Endpoints to Efficiently Execute Federated SPARQL Queries

Maria-Esther Vidal, Simón Castillo, Maribel Acosta, Gabriela Montoya, Guillermo Palma

Veröffentlicht: 2016 Februar

Journal: TLDKS (Large-scale Data and Knowledge-Centered Systems)

Seiten: 109-149
Verlag: Springer
Volume: 9620

Nicht-referierte Veröffentlichung

We consider the problem of source selection and query decomposition in federations of SPARQL endpoints, where query decompositions of a SPARQL query should reduce execution time and maximize answer completeness. This problem is in general intractable, and performance and answer completeness of SPARQL queries can be consider- ably affected when the number of SPARQL endpoints in a federation in- creases. We devise a formalization of this problem as the Vertex Coloring Problem and propose an approximate algorithm named Fed-DSATUR. We rely on existing results from graph theory to characterize the family of SPARQL queries for which Fed-DSATUR can produce optimal decompositions in polynomial time on the size of the query, i.e., on the number of SPARQL triple patterns in the query. Fed-DSATUR scales up much better to SPARQL queries with a large number of triple patterns, and may exhibit significant improvements in performance while answer completeness remains close to 100%. More importantly, we put our results in perspective, and provide evidence of SPARQL queries that are hard to decompose and constitute new challenges for data management.

ISBN: 978-3-662-49533-9
Weitere Informationen unter: Link
DOI Link: 10.1007/978-3-662-49534-6_4


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