Continuous Top-k Dominating Queries in Subspaces

Dominating queries are significant tools for preference-based query processing in databases and decision support applications. An important preference-based query is the top-k dominating query, which reports the k most important objects according to their domination capabilities (score). In this paper, we address the following issues to tackle two limitations of previously proposed approaches: (i) we allow dominating queries to be expressed in a subset of the available dimensions and (ii) we provide the necessary techniques to enable continuous processing of multiple queries. We use a grid-based indexing scheme to facilitate efficient search and update operations, avoiding expensive reorganization costs. In addition, several optimizations are proposed to enhance efficiency. Performance evaluation results, based on real-life and synthetic data sets, show the efficiency and scalability of the proposed scheme.