Column-store support for RDF data management: not all swans are white

ABSTRACT

This paper reports on the results of an independent evaluation of the techniques presented in the VLDB 2007 paper "Scalable Semantic Web Data Management Using Vertical Partitioning", authored by D. Abadi, A. Marcus, S. R. Madden, and K. Hollenbach [1]. We revisit the proposed benchmark and examine both the data and query space coverage. The benchmark is extended to cover a larger portion of the query space in a canonical way. Repeatability of the experiments is assessed using the code base obtained from the authors. Inspired by the proposed vertically-partitioned storage solution for RDF data and the performance figures using a column-store, we conduct a complementary analysis of state-of-the-art RDF storage solutions. To this end, we employ MonetDB/SQL, a fully-functional open source column-store, and a well-known -- for its performance -- commercial row-store DBMS. We implement two relational RDF storage solutions -- triple-store and vertically-partitioned -- in both systems. This allows us to expand the scope of [1] with the performance characterization along both dimensions -- triple-store vs. vertically-partitioned and row-store vs. column-store -- individually, before analyzing their combined effects. A detailed report of the experimental test-bed, as well as an in-depth analysis of the parameters involved, clarify the scope of the solution originally presented and position the results in a broader context by covering more systems.

REFERENCES

• 1: Daniel J. Abadi , Adam Marcus , Samuel R. Madden , Kate Hollenbach, Scalable semantic web data management using vertical partitioning, Proceedings of the 33rd international conference on Very large data bases, September 23-27, 2007, Vienna, Austria
• 2: Barton Library Catalog Data. http://simile.mit.edu/rdf-test-data/barton/.
• 3: Jeen Broekstra , Arjohn Kampman , Frank van Harmelen, Sesame: A Generic Architecture for Storing and Querying RDF and RDF Schema, Proceedings of the First International Semantic Web Conference on The Semantic Web, p.54-68, June 09-12, 2002
• 4: Eugene Inseok Chong , Souripriya Das , George Eadon , Jagannathan Srinivasan, An efficient SQL-based RDF querying scheme, Proceedings of the 31st international conference on Very large data bases, August 30-September 02, 2005, Trondheim, Norway
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• 6: MonetDB/SQL. http://monetdb.cwi.nl/SQL.
• 7: SPARQL Query Language for RDF. http://www.w3.org/TR/rdf-sparql-query/.
• 8: Mike Stonebraker , Daniel J. Abadi , Adam Batkin , Xuedong Chen , Mitch Cherniack , Miguel Ferreira , Edmond Lau , Amerson Lin , Sam Madden , Elizabeth O'Neil , Pat O'Neil , Alex Rasin , Nga Tran , Stan Zdonik, C-store: a column-oriented DBMS, Proceedings of the 31st international conference on Very large data bases, August 30-September 02, 2005, Trondheim, Norway
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INDEX TERMS

Primary Classification:
  H. Information Systems
  H.2 DATABASE MANAGEMENT
      H.2.4 Systems

Additional Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.2 Information Storage
      H.3.3 Information Search and Retrieval
      H.3.4 Systems and Software
          Subjects: Performance evaluation (efficiency and effectiveness)

General Terms:
Algorithms, Design, Management, Performance