Parallelizing Progressive Computation for Skyline Queries in Multi-disk Environment

  • Yunjun Gao
  • Gencai Chen
  • Ling Chen
  • Chun Chen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4080)


Given a set of d-dimensional points, skyline query returns the points that are not dominated by any other point on all dimensions. In this paper, we study an interesting scenario of skyline retrieval, where multi-dimensional points are distributed among multiple disks. Efficient algorithms for parallelizing progressive skyline computation are developed, using the parallel R-trees. The core of our scheme is to visit more entries from some disks simultaneously and enable effective pruning strategies with dominance checking to prune away the non-qualifying entries. Extensive experiments with synthetic data confirm that our proposed algorithms are both efficient and scalable.


Query Time Skyline Query Pruning Strategy Skyline Point Node Access 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yunjun Gao
    • 1
  • Gencai Chen
    • 1
  • Ling Chen
    • 1
  • Chun Chen
    • 1
  1. 1.College of Computer ScienceZhejiang UniversityHangzhouP.R. China

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