An Optimal and Progressive Algorithm for Skyline Queries

The skyline of a set of d-dimensional points contains the points that are not dominated by any other point on all dimensions. Skyline computation has recently received considerable attention in the database community, especially for progressive (or online) algorithms that can quickly return the first skyline points without having to read the entire data file. Currently, the most efficient algorithm is NN (nearest neighbors), which applies the divideand-conquer framework on datasets indexed by R-trees. Although NN has some desirable features (such as high speed for returning the initial skyline points, applicability to arbitrary data distributions and dimensions), it also presents several inherent disadvantages (need for duplicate elimination if d>2, multiple accesses of the same node, large space overhead). In this paper we develop BBS (branch-and-bound skyline), a progressive algorithm also based on nearest neighbor search, which is IO optimal, i.e., it performs a single access on...

• Type: Conference
• Year: 2003
• Where: SIGMOD
• Authors: Dimitris Papadias, Yufei Tao, Greg Fu, Bernhard Seeger
• Keywords: Alternative Skyline Queries, Branch-and-bound Skyline, Database, Initial Skyline Points, SIGMOD 2003