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The treatment and processing of Big Data problems imply an essential advantage for researchers and corporations. This is due to the huge quantity of knowledge that is hidden within the vast amount of information that is available nowadays. In order to be able to address with such volume of information in an efficient way, the scalability for Big Data applications is achieved by means of the MapReduce programming model. It is designed to divide the data into several chunks or groups that are processed in parallel, and whose result is “assembled” to provide a single solution.