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Title: UPSP: Unique predicate-based source selection for SPARQL endpoint federation
Authors: Özkan, E. C.
Saleem, M.
Doğdu, Erdoğan
Ngomo, A. C. N.
Keywords: Federated query
Linked data
Source pruning
Issue Date: 2016
Publisher: CEUR-WS
Source: 3rd International Workshop on Dataset PROFIling and fEderated Search for Linked Data, PROFILES 2016, 30 May 2016, , 122216
Abstract: Efficient source selection is one of the most important optimization steps in federated SPARQL query processing as it leads to more efficient query execution plan generation. An over-estimation of the data sources will generate extra network traffic by retrieving irrelevant intermediate results. Such intermediate results will be excluded after performing joins between triple patterns. Consequently an over-estimation of sources may result in increased query execution time. Devising triple patterns join-aware source selection approaches has shown to yield great improvement potential. In this work, we present UPSP, a new source selection approach for SPARQL query federation over multiple SPARQL endpoints. UPSP makes use of the subject-subject, subject-object, object-subject, and object-object joins information stored in an index structure to perform efficient triple patterns join-aware source selection. Our evaluation results on FedBench shows that UPSP outperforms state-of-the-art source selection approaches by selecting smaller number of sources (without losing recall) and reducing the query execution times.
ISSN: 1613-0073
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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