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Foundations of SPARQL query optimization

Published:23 March 2010Publication History

ABSTRACT

We study fundamental aspects related to the efficient processing of the SPARQL query language for RDF, proposed by the W3C to encode machine-readable information in the Semantic Web. Our key contributions are (i) a complete complexity analysis for all operator fragments of the SPARQL query language, which -- as a central result -- shows that the SPARQL operator Optional alone is responsible for the PSpace-completeness of the evaluation problem, (ii) a study of equivalences over SPARQL algebra, including both rewriting rules like filter and projection pushing that are well-known from relational algebra optimization as well as SPARQL-specific rewriting schemes, and (iii) an approach to the semantic optimization of SPARQL queries, built on top of the classical chase algorithm. While studied in the context of a theoretically motivated set semantics, almost all results carry over to the official, bag-based semantics and therefore are of immediate practical relevance.

References

  1. R. Angles and C. Gutierrez. The Expressive Power of SPARQL. In ISWC, pages 114--129, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. C. Beeri and M. Y. Vardi. A Proof Procedure for Data Dependencies. J. ACM, 31(4):718--741, 1984.Google ScholarGoogle Scholar
  3. C. Weiss et al. Hexastore: Sextuple Indexing for Semantic Web Data Management. In VLDB, pages 1008--1019, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. U. S. Chakravarthy, J. Grant, and J. Minker. Logic-based Approach to Semantic Query Optimization. TODS, 15(2):162--207, 1990.Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. R. Cyganiac. A relational algebra for SPARQL. Technical report, HP Laboratories Bristol, 2005.Google ScholarGoogle Scholar
  6. D. J. Abadi et al. Scalable Semantic Web Data Management Using Vertical Partitioning. In VLDB, pages 411--422, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. A. Deutsch, A. Nash, and J. Remmel. The Chase Revisited. In PODS, pages 149--158, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. A. Deutsch, L. Popa, and V. Tannen. Query Reformulation with Constraints. SIGMOD Record, 35(1):65--73, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. E. I. Chong et al. An Efficient SQL-based RDF Querying Scheme. In VLDB, pages 1216--1227, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. François Bry et al. Foundations of Rule-based Query Answering. In Reasoning Web, pages 1--153, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. G. Serfiotis et al. Containment and Minimization of RDF/S Query Patterns. In ISWC, pages 607--623, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. C. Gutierrez, C. A. Hurtado, and A. O. Mendelzon. Foundations of Semantic Web Databases. In PODS, pages 95--106, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. A. Harth and S. Decker. Optimized Index Structures for Querying RDF from the Web. In LA-WEB, pages 71--80, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. D. S. Johnson and A. Klug. Testing Containment of Conjunctive Queries under Functional and Inclusion Dependencies. In PODS, pages 164--169, 1982.Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. J. J. King. QUIST: a system for semantic query optimization in relational databases. In VLDB, pages 510--517, 1981.Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. L. Sidirourgos et al. Column-store Support for RDF Data Management: not all swans are white. In VLDB, page 1553, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. G. Lausen, M. Meier, and M. Schmidt. SPARQLing Constraints for RDF. In EDBT, pages 499--509, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Linked Data, http://linkeddata.org/.Google ScholarGoogle Scholar
  19. M. Schmidt et al. An Experimental Comparison of RDF Data Management Approaches in a SPARQL Benchmark Scenario. In ISWC, pages 82--97, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. M. Stocker et al. SPARQL Basic Graph Pattern Optimization Using Selectivity Estimation. In WWW, pages 595--604, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. D. Maier, A. Mendelzon, and Y. Sagiv. Testing Implications of Data Dependencies. In SIGMOD, pages 152--152, 1979.Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. M. Meier, M. Schmidt, and G. Lausen. On Chase Termination Beyond Stratification. In VLDB, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. T. Neumann and G. Weikum. RDF-3X: a RISC-style engine for RDF. PVLDB, 1(1):647--659, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. J. Pérez, M. Arenas, and C. Gutierrez. Semantics and Complexity of SPARQL. Technical report, arXiv:0605124 cs.DB, 2006.Google ScholarGoogle Scholar
  25. J. Pérez, M. Arenas, and C. Gutierrez. Semantics of SPARQL, 2006. TR/DCC-2006-16, Universidad de Chile.Google ScholarGoogle Scholar
  26. J. Pérez, M. Arenas, and C. Gutierrez. Semantics and Complexity of SPARQL. ACM Trans. Database Syst., 34(3), 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. A. Polleres. From SPARQL to Rules (and back). In WWW, pages 787--796, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. R. Fagin et al. Data Exchange: Semantics and Query Answering. Theor. Comput. Sci., 336(1):89--124, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. Resource Description Framework (RDF). http://www.w3.org/RDF/.Google ScholarGoogle Scholar
  30. S. Alexaki et al. On Storing Voluminous RDF descriptions: The case of Web Portal Catalogs. In WebDB, pages 43--48, 2001.Google ScholarGoogle Scholar
  31. J. Smith and P. Chang. Optimizing the Performance of a Relational Algebra Database Interface. Commun. ACM, 18(10):568--579, 1975.Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. SPARQL Query Language for RDF. W3C Recommendation, 15 Januray 2008.Google ScholarGoogle Scholar
  33. L. J. Stockmeyer. The polynomial-time hierarchy. Theor. Comput. Sci., 3:1--22, 1976.Google ScholarGoogle ScholarCross RefCross Ref
  34. Y. Theoharis et al. Benchmarking Database Representations of RDF/S Stores. In ISWC, pages 685--701, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library

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      cover image ACM Other conferences
      ICDT '10: Proceedings of the 13th International Conference on Database Theory
      March 2010
      260 pages
      ISBN:9781605589473
      DOI:10.1145/1804669

      Copyright © 2010 ACM

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      Publication History

      • Published: 23 March 2010

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