Skyline queries: An introduction

During the two past decades, skyline queries were used in several multi-criteria decision support applications. Given a dominance relationship in a dataset, a skyline query returns the objects that cannot be dominated by any other objects. Skyline queries were studied extensively in multidimensional spaces, in subspaces, in metric spaces, in dynamic spaces, in streaming environments, and in time-series data. Several algorithms were proposed for skyline query processing, such as window-based, progressive, distributed, geometric-based, index-based, divide- and-conquer, and dynamic programming algorithms. Moreover, several variations were proposed to solve application-specific problems like k-dominant skylines, top-k dominating queries, spatial skyline queries, and others. As the number of objects that are returned in a skyline query may become large, there is also an extensive study for the cardinality of skyline queries. This extensive research depicts the importance of skyline queries and their variations in modern applications.