Scalagon: An efficient skyline algorithm for all seasons

Abstract

Skyline queries are well-known in the database community and there are many algorithms for the computation of the Pareto frontier. The most prominent algorithms are based on a block-nested-loop style tuple-to-tuple comparison (BNL). Another approach exploits the lattice structure induced by a Skyline query over low-cardinality domains. In this paper, we present Scalagon, an algorithm which combines the ideas of the lattice approach and a BNL-style algorithm to evaluate Skylines on arbitrary domains. Since multicore processors are going mainstream, we also present a parallel version of Scalagon. We demonstrate through extensive experimentation on synthetic and real datasets that our algorithm can result in a significant performance advantage over existing techniques.