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.
- D. J. Abadi, A. Marcus, S. R. Madden, and K. Hollenbach. Scalable Semantic Web Data Management Using Vertical Partitioning. In Proceedings of the 33rd International Conference on Very Large Data Bases, pages 411--422. VLDB Endowment, September 2007. Google ScholarDigital Library
- Barton Library Catalog Data. http://simile.mit.edu/rdf-test-data/barton/.Google Scholar
- J. Broekstra, A. Kampman, and F. van Harmelen. Sesame: A Generic Architecture for Storing and Querying RDF and RDF Schema. In Proceedings of the First International Semantic Web Conference on The Semantic Web, pages 54--68, 2002. Google ScholarDigital Library
- E. I. Chong, S. Das, G. Eadon, and J. Srinivasan. An efficient SQL-based RDF querying scheme. In Proceedings of the 31st international conference on Very large data bases, pages 1216--1227, 2005. Google ScholarDigital Library
- S. Harris and N. Gibbins. 3store: Efficient Bulk RDF Storage. In Proceedings of the 1st International Workshop on Practical and Scalable Semantic Systems, pages 1--15, 2003.Google Scholar
- MonetDB/SQL. http://monetdb.cwi.nl/SQL.Google Scholar
- SPARQL Query Language for RDF. http://www.w3.org/TR/rdf-sparql-query/.Google Scholar
- M. Stonebraker, D. Abadi, A. Batkin, X. Chen, M. Cherniack, M. Ferreira, E. Lau, A. Lin, S. Madden, E. O'Neil, P. O'Neil, A. Rasin, N. Tran, and S. Zdonik. C-Store: A Column Oriented DBMS. In Proceedings of the 31st international conference on Very large data bases, pages 553--564, 2005. Google ScholarDigital Library
- K. Wilkinson. Jena Property Table Implementation. In Proceedings of the Second International Workshop on Scalable Semantic Web Knowledge Base Systems, pages 54--68, 2006.Google Scholar
- K. Wilkinson, C. Sayers, H. Kuno, and D. Reynolds. Efficient RDF Storage and Retrieval in Jena2. In Proceedings of the First International Workshop on Semantic Web and Databases, pages 131--150, 2003.Google Scholar
Index Terms
- Column-store support for RDF data management: not all swans are white
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