Skip to main content
SpringerLink
Log in
Book cover

International Conference on Knowledge Engineering and the Semantic Web

KESW 2013: Knowledge Engineering and the Semantic Web pp 69–82Cite as

SRelation: Fast RDF Graph Traversal

  • Conference paper

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 394))

Abstract

Linked Data in the RDF format can be viewed as a set of interlinked data on the web. Particular tasks, which are computed upon this data includes text based searching for entities, relations or performing various queries using querying languages like SPARQL. Such interlinked data can be interpreted as a graph with edges and vertexes. For the current SPARQL 1.1 standard, there is support for graph traversal, proposed and announced by SPARQL working group. Regarding performance, the property path task is the problem in current solutions. This paper describes an innovative and time efficient method of the graph traversal task - SRelation. First we discuss current approaches for SPARQL 1.1 graph traversal. For data access we mention local and distributed solutions, disk-based, mixed and whole-in-memory data storage aspects. We debate pros and cons of various approaches and suggest our new method SRelation to fit in the field of in-memory concept. To support this, we present our experiments on selected Linked Data datasets.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Berners-Lee, T.: Linked Data - Design Issues, http://www.w3.org/DesignIssues/LinkedData.html (retrieved May 28, 2013)

  2. W3C consortium, http://www.w3.org/Consortium/ (retrieved May 28, 2013)

  3. Schmidt, M., Hornung, T., Lausen, G., Pinkel, C.: SP^2Bench: a SPARQL Performance Benchmark. In: The 25th IEEE International Conference on Data Engineering, pp. 222–233. IEEE (2009)

    Google Scholar 

  4. Bizer, C., Schultz, A.: The Berlin Sparql Benchmark. International Journal on Semantic Web and Information Systems 5(2), 1–24 (2009)

    Article  Google Scholar 

  5. Even, S.: Graph algorithms. Cambridge University Press (2011)

    Google Scholar 

  6. Bahmani, B., Goel, A.: Partitioned Multi-Indexing: Bringing Order to Social Search. In: The 21st International Conference on World Wide Web, pp. 399–408. ACM (2012)

    Google Scholar 

  7. Hatcher, E., Gospodnetic, O., Mccandless, M.: Lucene in Action. Manning Publications Co., Greenwich (2004)

    Google Scholar 

  8. Lumsdaine, A., Gregor, D., Hendrickson, B., Berry, J.: Challenges in Parallel Graph Processing. Parallel Processing Letters 17(1), 5–20 (2007)

    Article  MathSciNet  Google Scholar 

  9. Schmidt, M., Hornung, T., Küchlin, N., Lausen, G., Pinkel, C.: An Experimental Comparison of RDF Data Management Approaches in a SPARQL Benchmark Scenario. In: Sheth, A.P., Staab, S., Dean, M., Paolucci, M., Maynard, D., Finin, T., Thirunarayan, K. (eds.) ISWC 2008. LNCS, vol. 5318, pp. 82–97. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  10. Abadi, D.J., Marcus, A., Madden, S.R., Hollenbach, K.: Scalable Semantic Web Data Management Using Vertical Partitioning. In: The 33rd International Conference on Very Large Data Bases, pp. 411–422 (2007)

    Google Scholar 

  11. Arenas, M., Conca, S., Pérez, J.: Counting Beyond a Yottabyte, or How SPARQL 1.1 Property Paths Will Prevent Adoption of the Standard. In: Proceedings of the 21st International Conference on World Wide Web, pp. 629–638 (2012)

    Google Scholar 

  12. Mituzas, D.: Wikipedia: Site Internals, Configuration and Code Examples and Management Issues (2007)

    Google Scholar 

  13. DB-Engines Ranking, http://db-engines.com/en/ranking/rdf+store (retrieved July 9, 2013)

  14. http://www.ontotext.com/owlim/editions (retrieved July 8, 2013)

  15. Heese, R., Leser, U., Quilitz, B., Rothe, C.: Index Support for SPARQL. In: European Semantic Web Conference, Innsbruck, Austria (2007)

    Google Scholar 

  16. Lehman, P.L.: Efficient Locking for Concurrent Operations on B-Trees. ACM Transactions on Database Systems (TODS) 6(4), 650–670 (1981)

    Article  MATH  Google Scholar 

  17. Bayer, R.: Symmetric Binary B-Trees: Data Structure and Maintenance Algorithms. Acta Informatica 1(4), 290–306 (1972)

    Article  MathSciNet  MATH  Google Scholar 

  18. Oracle Documents, http://docs.oracle.com/javase/6/docs/api/java/util/TreeMap.html (retrieved July 1, 2013)

  19. Malewicz, G., Austern, M.H., Bik, A.J., Dehnert, J.C., Horn, I., Leiser, N., Czajkowski, G.: Pregel: A System for Large-Scale Graph Processing. In: The ACM SIGMOD International Conference on Management of Data, pp. 135–146 (2010)

    Google Scholar 

  20. Yang, S., Yan, X., Zong, B., Khan, A.: Towards effective partition management for large graphs. In: The ACM SIGMOD International Conference on Management of Data, pp. 517–528 (2012)

    Google Scholar 

  21. Semantic Web Challenge, http://challenge.semanticweb.org/2013/ (retrieved June 18, 2013)

  22. W3C consortium, SPARQL 1.1 Property Paths, http://www.w3.org/TR/sparql11-property-paths/ (retrieved July 18, 2013)

  23. W3C consortium, SPARQL 1.1 Query Language, http://www.w3.org/TR/sparql11-query/ (retrieved July 18, 2013)

  24. Web Data Commons, http://www.webdatacommons.org/ (retrieved July 25, 2013)

Download references

Author information

Authors and Affiliations

  1. Institute of Informatics, Slovak Academy of Sciences, Bratislava, Slovakia

    Ján Mojžiš & Michal Laclavík

Authors
  1. Ján Mojžiš
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Michal Laclavík
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Institute of Artificial Intelligence, University of Ulm, 89069, Ulm, Germany

    Pavel Klinov

  2. Intelligence Systems Laboratory, Saint Petersburg National Research University of Information Technologies, Mechanics and Optics, Kronverksky prospekt 49, office 380,, 197101, St. Petersburg, Russia

    Dmitry Mouromtsev

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Mojžiš, J., Laclavík, M. (2013). SRelation: Fast RDF Graph Traversal. In: Klinov, P., Mouromtsev, D. (eds) Knowledge Engineering and the Semantic Web. KESW 2013. Communications in Computer and Information Science, vol 394. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41360-5_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-41360-5_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-41359-9

  • Online ISBN: 978-3-642-41360-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation