Output-sensitive Skyline Algorithms in External Memory

Xiaocheng Hu, Cheng Sheng, Yufei Tao, Yi Yang, Shuigeng Zhou

Abstract: This paper presents new results in external memory for finding the skyline (a.k.a. maxima) of N points in d-dimensional space. The state of the art uses for fixed d ≥ 3, and O((N/B)logM/B(N/B)) I/Os for d = 2, where M and B are the sizes (in words) of memory and a disk block, respectively. We give algorithms whose running time depends on the number K of points in the skyline. Specifically, we achieve expected cost for fixed d ≥ 3, and O((N/B)logM/B(K/B)) worst-case cost for d = 2. As a side product, we solve two problems both of independent interest. The first one, the M-skyline problem, aims at reporting M arbitrary skyline points, or the entire skyline if its size is at most M. We settle this problem in O(N/B) expected time in any fixed dimensionality d. The second one, the M-pivot problem, is more fundamental: given a set S of N elements drawn from an ordered domain, it outputs M evenly scattered elements (called pivots) from S, namely, S has asymptotically the same number of elements between each pair of consecutive pivots. We give a deterministic algorithm for solving the problem in O(N/B) I/Os.