Faster Query Execution for Partitioned RDF Data

  • Sandeep Vasani
  • Mohit Pandey
  • Minal Bhise
  • Trupti Padiya
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7753)


This work demonstrates use of Materialized Views to enhance query performance for partitioned RDF data. Given a query, our system determines which views or combinations thereof can be used to answer it. Break- even analysis for the proposed system has been done based on view materialization and refreshment costs. The system performance was evaluated for 7 query types, 3 having Sub-Obj joins. It shows that our approach reduces query response time by an average of 26% for all query types w.r.t response time using just vertical partitioning. Specifically, for queries with Sub-Obj joins, the average reduction is by 37%. On scaling data up 8 times, the reduction changed from 37% to 79% for queries with Sub-Obj joins, and from 26% to 51% on an average for all query types. With the proposed technique, Semantic Web Applications shall be more interactive since queries having Sub-Obj. joins are expected for them.


Materialized Views Query Execution RDF Data Semantic Web Data Vertical Partitioning 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Sandeep Vasani
    • 1
  • Mohit Pandey
    • 2
  • Minal Bhise
    • 2
  • Trupti Padiya
    • 2
  1. 1.University College LondonLondonUK
  2. 2.Dhirubhai Ambani Institute of Information and Communication TechnologyGandhinagarIndia

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