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Published in:
2011 | OriginalPaper | Chapter
Massive-Scale RDF Processing Using Compressed Bitmap Indexes
Authors : Kamesh Madduri, Kesheng Wu
Published in: Scientific and Statistical Database Management
Publisher: Springer Berlin Heidelberg
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The Resource Description Framework (RDF) is a popular data model for representing linked data sets arising from the web, as well as large scientific data repositories such as UniProt. RDF data intrinsically represents a labeled and directed multi-graph. SPARQL is a query language for RDF that expresses subgraph pattern-finding queries on this implicit multigraph in a SQL-like syntax. SPARQL queries generate complex intermediate join queries; to compute these joins efficiently, this paper presents a new strategy based on bitmap indexes. We store the RDF data in column-oriented compressed bitmap structures, along with two dictionaries. We find that our bitmap index-based query evaluation approach is up to an order of magnitude faster the state-of-the-art system RDF-3X, for a variety of SPARQL queries on gigascale RDF data sets.