Semi-skyline optimization of constrained skyline queries
Markus Endres, Werner Kießling · 2011
Skyline evaluation techniques (also known as Pareto preference queries) follow a common paradigm that eliminates data elements by finding other elements in a data set that dominate them. Nowadays already a variety of sophisticated skyline evaluation techniques are known, hence skylines are considered a well re-searched area. On the other hand, the skyline op-erator does not stand alone in database queries. In particular, the skyline operator may commute with the selection operator which may express hard con-straints on the skyline. In this paper, we address skyline queries that satisfy some hard constraints, so-called constrained skyline queries. We will present novel optimization techniques for such queries, which allow more efficient computation. For this, we pro-pose semi-skylines which can be used effectively for algebraic optimizations of skyline queries having a mixture of hard constraints and soft preference con-ditions. All our efficiency claims are supported by a series of performance benchmarks.