Abstract
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.
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Vasani, S., Pandey, M., Bhise, M., Padiya, T. (2013). Faster Query Execution for Partitioned RDF Data. In: Hota, C., Srimani, P.K. (eds) Distributed Computing and Internet Technology. ICDCIT 2013. Lecture Notes in Computer Science, vol 7753. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36071-8_44
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DOI: https://doi.org/10.1007/978-3-642-36071-8_44
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