Faster query execution for partitioned RDF data

Vasani, Sandeep; Pandey, Mohit; Bhise, Minal; Padiya, Trupti

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.

Citation

Vasani, S., Pandey, M., Bhise, M., & Padiya, T. (2013). Faster query execution for partitioned RDF data. In C. Hota, & P. K. Srimani (Eds.), Distributed Computing and Internet Technology: 9th International Conference, ICDCIT 2013, Bhubaneswar, India, February 5-8, 2013. Proceedings 9 (547-560)

• Conference Name: Distributed Computing and Internet Technology: 9th International Conference, ICDCIT 2013
• Conference Location: Bhubaneswar, India
• Start Date: Feb 5, 2015
• End Date: Feb 8, 2015
• Publication Date: 2013
• Deposit Date: Sep 13, 2023
• Publisher: Springer
• Volume: 7753
• Pages: 547-560
• Series Title: Lecture Notes in Computer Science
• Book Title: Distributed Computing and Internet Technology: 9th International Conference, ICDCIT 2013, Bhubaneswar, India, February 5-8, 2013. Proceedings 9
• ISBN: 9783642360701
• Public URL: https://uwe-repository.worktribe.com/output/10937844