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Rewriting Common Sub-Expressions for Optimizing Multiple SPARQL Queries


Affiliations
1 Department of Computer Science in Bannari Amman Institute of Technology, Sathyamangalam, Tamilnadu, India
2 Department of Computer Science and Engineering from Bannari Amman Institute of Technology, Sathyamangalam, Tamilnadu, India
3 Department of Electronics and Instrumentation Engineering in Bannari Amman Institute of Technology, Sathyamangalam, Tamilnadu, India
     

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A World Wide Web Consortium standard for processing Resource Description Framework data is a SPARQL query language, a technique that is used to encode data in meaningful manner. Multi Query optimization (MQO) is a technique in which multiple query plans for satisfying a query are examined and a good query plan is identified. Query optimization is performed by grouping into individual clusters using common substructures in the multiple SPARQL queries. The foundations of SPARQL query and Query Optimization technique for Multiple SPARQL queries are investigated. An Efficient algorithm for identifying the common sub expressions is executed. A comprehensive set of query rewriting rules for the clustered group is proposed and finally Query execution provide the final result of optimized query. The proposed method is effective and efficient for optimized SPARQL query.


Keywords

W3C, RDF, SPARQL, MQO.
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  • Rewriting Common Sub-Expressions for Optimizing Multiple SPARQL Queries

Abstract Views: 196  |  PDF Views: 3

Authors

R. Gomathi
Department of Computer Science in Bannari Amman Institute of Technology, Sathyamangalam, Tamilnadu, India
C. Sathya
Department of Computer Science and Engineering from Bannari Amman Institute of Technology, Sathyamangalam, Tamilnadu, India
D. Sharmila
Department of Electronics and Instrumentation Engineering in Bannari Amman Institute of Technology, Sathyamangalam, Tamilnadu, India

Abstract


A World Wide Web Consortium standard for processing Resource Description Framework data is a SPARQL query language, a technique that is used to encode data in meaningful manner. Multi Query optimization (MQO) is a technique in which multiple query plans for satisfying a query are examined and a good query plan is identified. Query optimization is performed by grouping into individual clusters using common substructures in the multiple SPARQL queries. The foundations of SPARQL query and Query Optimization technique for Multiple SPARQL queries are investigated. An Efficient algorithm for identifying the common sub expressions is executed. A comprehensive set of query rewriting rules for the clustered group is proposed and finally Query execution provide the final result of optimized query. The proposed method is effective and efficient for optimized SPARQL query.


Keywords


W3C, RDF, SPARQL, MQO.