Probability Computation for Rank Joins Using Weibull Distribution
Zaheer Ahmad, Adnan Abid · 2014
Ranking queries produce results that are ranked on some pre-computed score. Typically, these queries involve joins, where users are usually interested only in the top-K join results. Current relational query processors handle ranking queries efficiently, however, in case of top-k join queries involving distributed or web based data sources which have a non negligible response time for data extraction, the existing algorithms do not perform well in terms of time taken. Focus of this paper is to compute the join results efficiently, while minimizing the time to compute top-k join results, as well as reducing the number of data extractions from these data sources. As a principal contribution, we present a probabilistic method to compute the top-k join results efficiently, and we have found the initial results of this research promising.