Bunch investigation is utilized to order comparative protests under same gathering. It is a standout amongst the most critical data mining techniques. In any case, it neglects to perform well for big data because of enormous time many-sided quality. For such situations parallelization is a superior approach. MapReduce is a prevalent programming model which empowers parallel handling in an appropriated domain. Be that as it may, a large portion of the clustering calculations are not "normally parallelizable" for example Genetic Algorithms. This is thus, because of the successive idea of Genetic Algorithms. This paper acquaints a system with parallelize GA based clustering by expanding hadoop MapReduce. An examination of proposed way to deal with assess execution picks up regarding a consecutive calculation is displayed. The investigation depends on a genuine huge data set.

Big Data, Clustering, Davies-Bouldin Index, Distributed processing, Hadoop MapReduce , Heuristics, Parallel Genetic Algorithm

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