Published Paper Details:

In Hadoop condition fundamentally we are performing has two segments in particular HDFS and MapReduce. Hadoop stores client information in view of room use of datanodes on the group as opposed to the handling capacity of the datanodes. Here Hadoop keeps running in half and half condition as all datanodes may not be same framework. Hence, workload irregular characteristics will happen when occupations keep running in a Hadoop group bringing about poor execution. So that here I propose a dynamic calculation to adjust the workload between various racks on a Hadoop group in view of the log documents of Hadoop. In any case, if the assignments are executing on basic or delicate information in a secured rack, the information exchange to an unsecured bunch will bring about protection being bargained. We propose a way to deal with exchange information between racks without revealing private data. Moving undertakings from the most over-burden rack to another rack enhances the execution of MapReduce employments. Our reenactments show that the proposed calculation diminishes running time of an occupation by over 50% running on the most over-burden rack