Efficient Parallel Set-Similarity Joins Using MapReduceDepartment of Computer Science University of California, Irvine Abstract In this paper we study how to efficiently perform set-similarity joins in parallel using the popular MapReduce framework. We propose a 3-stage approach for end-to-end set-similarity joins. We take as input a set of records and output a set of joined records based on a set-similarity condition. We efficiently partition the dat
