Closest Interval Join Using MapReduce

Qiang Zhang, Andy He, Chris Liu, Eric Lo

Abstract: The closest interval join problem is to find all the closest intervals between two interval sets R and S. Applications of closest interval join include bioinformatics and other data science. Interval data can be very large and continue to increase in size due to the advancement of data acquisition technology. In this paper, we present efficient MapReduce algorithms to compute closest interval join. Experiments based on both real and synthetic interval data demonstrated that our algorithms are efficient.