The k-Nearest Neighbor Algorithm Using MapReduce Paradigm

Data in any form is a valuable resource but more often than not data collected in the real world is completely random and unstructured. Hence, to utilize the true potential of data as a resource we must transform it in such a manner so as to retrieve meaningful information from it. Data mining fulfills this need. Today there is not only a need for efficient data mining techniques to process large volume of data but also a need for a means to meet the computational requirements to process such huge volume of data. In this paper we implement an effective data mining technique known as the k-Nearest Neighbor method on a distributed computing environment running Apache Hadoop that uses the MapReduce paradigm to process high volume data.