Exploiting MapReduce-based Similarity Joins
Cloud enabled systems have become a crucial component to efficiently process and analyze massive amounts of data. One of the key data processing and analysis operations is the Similarity Join, which retrieves all data pairs whose distances are smaller than a pre-defined threshold ?. Even though multiple algorithms and implementation techniques have been proposed for Similarity Joins, very little work has addressed the study of Similarity Joins for cloud systems. This paper presents MRSimJoin, a multi-round MapReduce based algorithm to efficiently solve the Similarity Join problem. MRSimJoin efficiently partitions and distributes the data until the subsets are small enough to be processed in a single node.