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Triple pattern join cardinality estimations over HDT with enhanced metadata

Wössner, Elena; Qin, Chang; Fernández, J. D.; Acosta, Maribel

Abstract:
In this work, we present HDT-stats, an extension to the HDT operations, to compute further metadata when evaluating triple patterns over RDF graphs represented with HDT. Then, we propose a novel model that relies on the HDT-stats metadata, as well as the distinct position of SPARQL variables, to estimate the cardinality of joins between triple patterns. Our preliminary results suggest that our approach produce smore accurate cardinality estimations than existing solutions.

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Verlagsausgabe §
DOI: 10.5445/IR/1000100184
Veröffentlicht am 06.12.2019
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Angewandte Informatik und Formale Beschreibungsverfahren (AIFB)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2019
Sprache Englisch
Identifikator ISSN: 1613-0073
KITopen-ID: 1000100184
Erschienen in Posters and Demos at SEMANTiCS 2019: Proceedings of the Posters and Demo Track of the 15th International Conference on Semantic Systems, co-located with 15th International Conference on Semantic Systems (SEMANTiCS 2019), Karlsruhe, Germany, September 9th to 12th, 2019. Ed.: M. Alam
Veranstaltung 15th International Conference on Semantic Systems (SEMANTiCS 2019), Karlsruhe, Deutschland, 09.09.2019 – 12.09.2019
Serie CEUR Workshop Proceedings ; 2451
Nachgewiesen in Scopus
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