Partial Selection Query in Peer-to-Peer Databases

  • Authors:
  • Farnoush Banaei-Kashani;Cyrus Shahabi

  • Affiliations:
  • University of Southern California;University of Southern California

  • Venue:
  • ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
  • Year:
  • 2006

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Abstract

In this paper, we propose DBSampler, a query execution mechanism to answer "partial selection" queries in peerto- peer databases. A partial selection query is an arbitrary selection query that is satisfied with a fraction\inof the results; a universal operation with applications in database tuning, query optimization and approximate query processing in peer-to-peer databases. DBSampler is based on an epidemic dissemination algorithm. We model the epidemic dissemination as a percolation problem and by rigorous percolation analysis tune DBSampler per-query and on-thefly to answer partial queries correctly and efficiently. We verify the efficiency of DBSampler in terms of query cost and query time via extensive simulation.