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Parallel Skyline Computation on Multicore Architectures

Parallel Skyline Computation on Multicore Architectures. ICDE`09. Outline. Introduction Preliminary Parallel BBS(branch-and-bound algorithm) Parallel Skyline Algorithm ( Pskyline ) Experiments Conclusion. Introduction. (cont.). The advantage of the skyline Skyline algorithm Sequential

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Parallel Skyline Computation on Multicore Architectures

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  1. Parallel Skyline Computation on Multicore Architectures ICDE`09

  2. Outline • Introduction • Preliminary • Parallel BBS(branch-and-bound algorithm) • Parallel Skyline Algorithm (Pskyline) • Experiments • Conclusion

  3. Introduction

  4. (cont.) • The advantage of the skyline • Skyline algorithm • Sequential • No index structure • BNL、SFS 、LESS • Index structure • NN 、BBS 、ZSHARE • Parallel • Many in Distributed environment, but no algorithm for multi-core environment

  5. Prrliminary • A. Skyline computation • For a d-dimensional dataset D. • skyline set : • Incomparable : • Transitivity : • Incomparability : • Distributivity :

  6. (cont.) • B.Skeletal parallel programming • A programming model • Need two component : • Data structure • List : • Parallel skeletons • not • For developing parallel skyline algorithm • Parallel map and Parallel reduce

  7. (cont.) • Pmap (parallel map) A B C D E F G H A’ B’ C’ D’ E’ F’ G’ H’

  8. (cont.) • Preduce (parallel reduce) A B C D E F G H A’ B’ C’ D’ …… R

  9. Parallel BBS • A. branch-and-bound algorithm • Use R-tree as its index structure

  10. (cont.) • B.Parallelizing BBS

  11. Parallel skyline algorithm (Pskyline) • Overall design • Pskyline D = S(D) • PskylineD = sreducepmerge (pmapsskyline L) • L = [D1,…,Db] D = D1++…++Db • Sreduce

  12. (cont.) • Pmerge • Sskyline

  13. Experiments

  14. (cont.)

  15. Conclusion • Muliti-core architecture for database operations.

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