Specific queries optimization using Jaya approach

Specific queries optimization using Jaya approach

Автор: Sahil Saharan, J.S. Lather, R. Radhakrishnan

Журнал: International Journal of Modern Education and Computer Science @ijmecs

Статья в выпуске: 3 vol.10, 2018 года.

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The Fast query engine is a requirement as a supporting tool for the semantic web technology application such as Electronic Commerce environ. As the large data is represented using the effective data representation called RDF. The focus of this paper is to optimize the specific type of the query called Cyclic query and star query on main-memory RDF data model using ARQ query engine of Jena. For the considered problem, we ruminate a Jaya algorithm for rearrangement of the order of triple pattern and also compare the results with an already proposed approach in the literature. The evaluation result shows that Jaya performs better in terms of execution time in comparison to Ant Colony Optimization.

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Resource Description Framework (RDF), Query Optimization, Jaya, SPARQL, Reordering triple patterns, Semantic Web

Короткий адрес: https://sciup.org/15016745

IDR: 15016745   |   DOI: 10.5815/ijmecs.2018.03.05

Список литературы Specific queries optimization using Jaya approach

  • T. Berners-Lee, J. Hendler, O. Lassila, “The semantic web”, Sci. Am. vol 284, no.5, pp: 34–43, 2001.
  • Frank Manola and Eric Miller, “RDF primer”, 2004.
  • S. Harris, A. Seaborne, “SPARQL1.1querylanguage” – W3C working draft 05 January 2012.
  • G.H.L. Fletcher, “An algebra for basic graph patterns”, in: Proceedings of the Workshop on Logic in Databases, 2008.
  • H. Stuckenschmidt, R. Vdovjak, J. Broekstra, G. Houben, “Towards distributed processing of RDF path queries”, Int. J. Web Eng. Technol. vol.2, no.2/3, pp.207–230, 2005.
  • A. Hogenboom, V. Milea, F. Frasincar, U. Kaymak, “RCQ-GA: RDF Chain query optimization using genetic algorithms”, in: Proceedings of the 10th International Conference on EC-Web, 2, pp:181–192, 2009.
  • A. Hogenboom, F. Frasincar, U. Kaymak, “Ant colony optimization for RDF Chain queries for decision support”, Expert Syst. Appl. Vol.40, no.5, 2013.
  • R. Rao, “Jaya: A simple and new optimization algorithm for solving constrained and unconstrained optimization problems”. International Journal of Industrial Engineering Computations, vol. 7,no.1,pp:19-34, 2016.
  • R.V. Rao, G.G. Waghmare. “A new optimization algorithm for solving complex constrained design optimization problems”. Engineering Optimization.vol.49, no.1,pp:60-83, 2017.
  • Abhishek K, Kumar VR, Datta S, Mahapatra SS. “Application of JAYA algorithm for the optimization of machining performance characteristics during the turning of CFRP (epoxy) composites: comparison with TLBO, GA, and ICA”. Engineering with Computers. pp.1-9, 2016.
  • Warid W, Hizam H, Mariun N, Abdul-Wahab NI. “Optimal Power Flow Using the Jaya Algorithm”. Energies.vol.9, no.9,pp:678, 2016.
  • Rao RV, Rai DP, Balic J. “Surface Grinding Process Optimization Using Jaya Algorithm”. InComputational Intelligence in Data Mining—vol.2 pp:487-495, 2016.
  • Rao RV, More KC, Taler J, Oclon P. Dimensional optimization of a micro-channel heat sink using Jaya algorithm”. Applied Thermal Engineering.vol.103, pp:572-82, 2016.
  • Phulambrikar S. “Solving Combined Economic Emission Dispatch Solution Using Jaya Optimization Algorithm Approach”.2016
  • H. Stuckenschmidt, R. Vdovjak, J. Broekstra, G. Houben, “Towards distributed processing of RDF path queries”, Int. J. Web Eng. Technol.vol.2 no.2/3 pp.207–230, 2005.
  • J. Broekstra, A. Kampman, F. Van Harmelen, “Sesame: A generic architecture for storing and querying rdf and rdf schema”, in: International semantic web conference, Springer Berlin Heidelberg, pp. 54-68,2002.
  • E.P. Shironoshita, M.T. Ryan, M.R. Kabuka, “Cardinality estimation for the optimization of queries on ontologies, SIGMOD Rec.vol.36,no.2, pp:13–18, 2007.
  • A. Maduko, K. Anyanwu, A. Sheth, P. Schliekelman, “Estimating the cardinality of RDF graph patterns”, in: Proceedings of the 16th International Conference on World Wide Web, ACM, Banff, AB, Canada, pp.1233–1234, 2007.
  • M. Stocker, A. Seaborne, A. Bernstein, C. Kiefer, D. Reynolds, “SPARQL basic graph pattern optimization using selectivity estimation”, in: Proceedings of the 17th International Conference on WWW, ACM, Beijing, China, pp:595–604, 2008.
  • E. Ruckhaus, E. Ruiz, M. Vidal, “Query evaluation and optimization in the semantic web”, Theory Pract. Log. Program. vol.8, no.3, pp:393–409, 2008.
  • T. Neumann, G. Weikum, “RDF-3X: a RISC- style engine for RDF”, Proc. VLDB Endow, Vol.1,No.1, pp.647–659, 2008.
  • T. Neumann, G. Weikum, “Scalable join processing on very large RDF graphs”, in: Proceedings of the ACM SIGMOD International Conference on Management of Data, SIGMOD'09, ACM, New York, NY, USA, pp:627–640, 2009.
  • Z. Kaoudi, K. Kyzirakos, M. Koubarakis, “SPARQL query optimization on top of DHTs”, in: Proceedings of the 9th International Conference on the Semantic Web – vol. partI, ISWC'10, Springer-Verlag, Berlin, Heidelberg, pp:418–435, 2010.
  • T. Neumann and G. Moerkotte, “Characteristic sets: Accurate cardinality estimation for RDF queries with multiple joins”, in: ICDE, Hannover, Germany, pp:984-994, 2011.
  • D. Ouyang, X. Wang, Y. Ye, and X. Cui, “A GA-based SPARQL BGP reordering optimization method”, Advances in Information Sciences and Service Sciences, vol.4, no.9, pp:139–147, 2012.
  • R. Gomathi, D. Sharmila, “A novel adaptive cuckoo search for optimal query plan generation”, The Scientific World Journal, 2014.
  • E. Guzel Kalayci, T.E. Kalaycı, D. Birant, “An ant colony optimization approach for optimising SPARQL queries by reordering triple patterns”, Information Systems, vol.50 pp:51–68, 2015.
  • J.J. Carroll, G. Klyne, “Resource description framework (RDF): Concepts and abstract syntax”– W3C recommendation, 2004.
  • http://jena.apache.org.
  • http://jena.apache.org/documentation/query.
  • http://swat.cse.lehigh.edu/projects/lubm/
  • com.hp.hpl.jena.graph.GraphStatisticsHandler
  • S. N. Sivanandam, S.N. Deepa , “Introduction to Genetic Algorithm”, ISBN 978-3-540-73189-4 Springer Berlin Heidelberg New York, Springer ñ Verlag Berlin Heidelberg 2008.
  • O. Hartig, R. Heese, “The SPARQL query graph model for query optimization”, in: Proceedings of the forthth European Conference on the Semantic Web: Research and Applications, ESWC'07, pp:564–578, 2007.
  • Meimaris M, Papastefanatos G. Distance-Based Triple Reordering for SPARQL Query Optimization. in: Proceedings of the 33rd International Conference on Data Engineering (ICDE), IEEE, 2017, pp. 1559-1562.
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