A complete translation from SPARQL into efficient SQL

  • Authors:

  • Brendan Elliott;En Cheng;Chimezie Thomas-Ogbuji;Z. Meral Ozsoyoglu

  • Affiliations:

  • Case Western Reserve University, Cleveland, OH and Microsoft Corporation, Redmond, WA;Case Western Reserve University, Cleveland, OH;Cleveland Clinic, Cleveland, OH and Case Western Reserve University, Cleveland, OH;Case Western Reserve University, Cleveland, OH

  • Venue:
  • IDEAS '09 Proceedings of the 2009 International Database Engineering & Applications Symposium
  • Year:
  • 2009

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Abstract

This paper presents a feature-complete translation from SPARQL, the proposed standard for RDF querying, into efficient SQL. We propose "SQL model"-based algorithms that implement each SPARQL algebra operator via SQL query augmentation, and generate a flat SQL statement for efficient processing by relational database query engines. SPARQL-to-SQL translation presented is feature-complete, since it applies to all SPARQL language features. Finally, we demonstrate the performance and scalability of our method by an extensive evaluation using recent SPARQL benchmark queries, and a benchmark dataset, as well as a real-world photo dataset.