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Skyline Processing on Distributed Vertical Decompositions
April 2013 (vol. 25 no. 4)
pp. 850-862
George Trimponias, Hong Kong University of Science and Technology, Hong Kong
Ilaria Bartolini, University of Bologna , Bologna
Dimitris Papadias, Hong Kong University of Science and Technology, Hong Kong
Yin Yang, Advanced Digital Sciences Center, Singapore
We assume a data set that is vertically decomposed among several servers, and a client that wishes to compute the skyline by obtaining the minimum number of points. Existing solutions for this problem are restricted to the case where each server maintains exactly one dimension. This paper proposes a general solution for vertical decompositions of arbitrary dimensionality. We first investigate some interesting problem characteristics regarding the pruning power of points. Then, we introduce vertical partition skyline (VPS), an algorithmic framework that includes two steps. Phase 1 searches for an anchor point $(P_{anc})$ that dominates, and hence eliminates, a large number of records. Starting with $(P_{anc})$, Phase 2 constructs incrementally a pruning area using an interesting union-intersection property of dominance regions. Servers do not transmit points that fall within the pruning area in their local subspace. Our experiments confirm the effectiveness of the proposed methods under various settings.
Index Terms:
Servers,Lattices,Partitioning algorithms,Query processing,query processing,Distributed skyline,vertical partitioning
Citation:
George Trimponias, Ilaria Bartolini, Dimitris Papadias, Yin Yang, "Skyline Processing on Distributed Vertical Decompositions," IEEE Transactions on Knowledge and Data Engineering, vol. 25, no. 4, pp. 850-862, April 2013, doi:10.1109/TKDE.2011.266
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