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Hexastore: Sextuple Indexing for Semantic Web Data Management (2008)
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| Citations: | 188 - 11 self |
BibTeX
@MISC{Weiss08hexastore:sextuple,
author = {Cathrin Weiss and Panagiotis Karras and Abraham Bernstein},
title = {Hexastore: Sextuple Indexing for Semantic Web Data Management },
year = {2008}
}
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Abstract
Despite the intense interest towards realizing the Semantic Web vision, most existing RDF data management schemes are constrained in terms of efficiency and scalability. Still, the growing popularity of the RDF format arguably calls for an effort to offset these drawbacks. Viewed from a relationaldatabase perspective, these constraints are derived from the very nature of the RDF data model, which is based on a triple format. Recent research has attempted to address these constraints using a vertical-partitioning approach, in which separate two-column tables are constructed for each property. However, as we show, this approach suffers from similar scalability drawbacks on queries that are not bound by RDF property value. In this paper, we propose an RDF storage scheme that uses the triple nature of RDF as an asset. This scheme enhances the vertical partitioning idea and takes it to its logical conclusion. RDF data is indexed in six possible ways, one for each possible ordering of the three RDF elements. Each instance of an RDF element is associated with two vectors; each such vector gathers elements of one of the other types, along with lists of the third-type resources attached to each vector element. Hence, a sextupleindexing scheme emerges. This format allows for quick and scalable general-purpose query processing; it confers significant advantages (up to five orders of magnitude) compared to previous approaches for RDF data management, at the price of a worst-case five-fold increase in index space. We experimentally document the advantages of our approach on real-world and synthetic data sets with practical queries.
Keyphrases
semantic web data management sextuple indexing rdf element vertical partitioning idea vertical-partitioning approach vector gather element rdf data management relationaldatabase perspective existing rdf data management scheme triple format logical conclusion separate two-column table rdf data model rdf property value triple nature scheme emerges rdf storage scheme vector element semantic web vision possible ordering possible way similar scalability drawback rdf data rdf format scalable general-purpose query processing index space recent research intense interest towards practical query worst-case five-fold increase third-type resource previous approach synthetic data set significant advantage
