Advanced SearchSearch Tips
Improving Join Performance for SPARQL Query Processing in the Clouds
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
  • Journal title : Journal of KIISE
  • Volume 43, Issue 6,  2016, pp.700-709
  • Publisher : Korean Institute of Information Scientists and Engineers
  • DOI : 10.5626/JOK.2016.43.6.700
 Title & Authors
Improving Join Performance for SPARQL Query Processing in the Clouds
Choi, Gyu-Jin; Son, Yun-Hee; Lee, Kyu-Chul;
Recently, with the rapid growth of LOD (Linked Open Data) existing methods based on a single machine have limitation in performance. Existing solutions use distributed framework such as Mapreduce in order to improve the performance. However, the MapReduce framework for processing SPARQL queries involves multiple MapReduce jobs and additional costs incurred. In addition, the problem of unnecessary data processing arises. In this study, we proposed a method to reduce the number of MapReduce jobs during SPARQL query processing and join indexes based on Bitmap for minimizing the costs of processing unnecessary data.
semantic web;MapReduce;SPARQL;RDF;join index;bitmap index;
 Cited by
W. S. Oh, Trends and Prospectives of Linked Data, TopQuadrant Korea, 2009. (in Korean)

Klyne, Graham, and Jeremy J. Carroll (2004, February 10). Resource description framework (RDF): Concepts and abstract syntax [Online]. Available:

Eric Prud'hommeaux, and Andy Seaborne. (2008, January 15). SPARQL Query Language for RDF [Online]. Available:

Anja Jentzsch, Richard Cyganiak and Chris Bizer. (2011, September 19). State of the lod cloud [Online]. Available:

Dean, Jeffrey, and Sanjay Ghemawat, "MapReduce: simplified data processing on large clusters," Communications of the ACM 51.1, pp. 107-113, 2008.

Apache HBase Team, Apache HBase Reference Guide [Online]. Available:

Weiss, Cathrin, Panagiotis Karras, and Abraham Bernstein, "Hexastore: sextuple indexing for semantic web data management," Proceedings of the VLDB Endowment 1.1, pp. 1008-1019, 2008.

Neumann, Thomas, and Gerhard Weikum, "RDF-3X: a RISC-style engine for RDF" Proceedings of the VLDB Endowment 1.1, pp. 647-659, 2008.

Atre, Medha, Jagannathan Srinivasan, and James A. Hendler, "BitMat: A Main-memory Bit Matrix of RDF Triples for Conjunctive Triple Pattern Queries," International Semantic Web Conference (Posters & Demos), 2008.

Erling, Orri, and Ivan Mikhailov, "Virtuoso: RDF support in a native RDBMS," Semantic Web Information Management, pp. 501-519, Springer, 2010.

Carroll, Jeremy J., et al., "Jena: implementing the semantic web recommendations," Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters, ACM, 2004.

Kiryakov, Atanas, Damyan Ognyanov, and Dimitar Manov, "OWLIM-a pragmatic semantic repository for OWL," Web Information Systems Engineering-WISE 2005 Workshops, Springer, 2005.

Haque, Albert, and Lynette Perkins, "Distributed RDF Triple Store Using HBase and Hive," University of Texas at Austin, 2012.

Sun, Jianling, and Qiang Jin, "Scalable rdf store based on hbase and mapreduce," 2010 3rd International Conference on Advanced Computer Theory and Engineering(ICACTE), Vol. 1, pp. 633-636 IEEE, 2010.

Husain, Mohammad, et al., "Heuristics-based query processing for large rdf graphs using cloud computing" IEEE Transactions Knowledge and Data Engineering, Vol. 23, No. 9, pp. 1312-1327, 2011. crossref(new window)

Schatzle, Alexander, et al., "Cascading Map-Side Joins over HBase for Scalable Join Processing," SSWS+ HPCSW, 2012.

Guo, Yuanbo, Zhengxiang Pan, and Jeff Heflin, "LUBM: A benchmark for OWL knowledge base systems," Web Semantics: Science, Services and Agents on the World Wide Web, Vol. 3, No. 2, pp. 158-182, 2005. crossref(new window)