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We are in the era of” Big Data”. There is a lot more data, all the time, growing at 50 percent a year. Data is not only becoming more available but also more understandable to computers. Big companies perform scalable and time-effective analytical processing of the data to extract useful information. Cost-effective and scalable processing of large datasets is a nontrivial undertaking. Fortunately, MapReduce frameworks and cloud computing have made it easier than ever. To improve the performance of processing the data, developers either transform their sequential code to correspondent MapReduce code or improve the existing MapReduce code by configuring the parameters (eg, number of mapper nodes, etc.). For both activities of the developers, there is a need of an automatic tool.