Efficient Processing of k Nearest Neighbor Joins using MapReduce

Understand

k nearest neighbor join (kNN join), designed to find k nearest neighbors from a dataset S for every object in another dataset R, is a primitive operation widely adopted by many data mining applications.

• As a combination of the k nearest neighbor query and the join operation, kNN join is an expensive operation.
• Given the increasing volume of data, it is difficult to perform a kNN join on a centralized machine efficiently.
• In this paper, we investigate how to perform kNN join using MapReduce which is a well-accepted framework for data-intensive applications over clusters of computers.