In this paper, we formalize the problem of Basic Graph Pattern (BGP) optimization for SPARQL queries and main memory graph implementations of RDF data. We define and analyze the characteristics of heuristics for selectivitybased static BGP optimization. The heuristics range from simple triple pattern variable counting to more sophisticated selectivity estimation techniques. Customized summary statistics for RDF data enable the selectivity estimation of joined triple patterns and the development of efficient heuristics. Using the Lehigh University Benchmark (LUBM), we evaluate the performance of the heuristics for the queries provided by the LUBM and discuss some of them in more details.

semantic web, query, RDF, internet engineering RDF provides a basic way to represent data for the Semantic Web. We have been experimenting with the query paradigm for working with RDF data in semantic web applications. Query of RDF data provides a declarative access mechanism that is suitable for application usage and remote access. We describe work on a conceptual model for querying RDF data that refines ideas first presented in at the W3C workshop on Query Languages and the design of one possible syntax, derived from rdfDB, that is suitable for application programmers. Further, we present experience gained in three independent implementations of the query language. Abstract. RDF provides a basic way to represent data for the Semantic Web.We have been experimenting with the query paradigm for working with RDF data in semantic web applications. Query of RDF data provides a declarative access mechanism that is suitable for application usage and remote access. We describe work on a conceptual model for querying RDF data that refines ideas first presented in at the W3C workshop on Query Languages [14] and the design of one possible syntax, derived from [7], that is suitable for application programmers. Further, we present experience gained in three implementations of the query language.

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