Fast Distributed Top-q and Top-k Query ...

Top-k queries retrieve the k results of a query which score best for an objective function representing the preferences of users. To require that the returned results also have to satisfy the preferences to a certain degree we introduce top-q queries which return all results which approximate the user preferences to at least some minim degree q. We show how top-q queries and top-k queries can be combined enabling the user to post a large number of interesting queries. Furthermore, we show that the calculation of top-q queries can be integrated in algorithms efficiently processing top-k queries. We implemented our approach and evaluated it against the fastest threshold based top-k query answering approaches (BPA-2). Our experiments showed an improvement by one to two orders of magnitude regarding time and memory requirements. Furthermore, we show how such queries can be processed in highly distributed peer-to-peer databases in an efficient way and propose an adaptive algorithm which takes several parameters of the network of databases into account to optimize the processing of distributed top-k queries.