A Survey on MapReduce Performance and Hadoop Acceleration
نویسنده
چکیده
MapReduce is implementation for generating large data sets with a parallel, distributed algorithm on a cluster. Hadoop is open source implementation of the MapReduce programming datamodel used for large-scale parallel applications such as web indexing, data mining, and scientific simulation. Hadoop-A framework is able to levitate Hadoop acceleration and give significant performance compared to existing Hadoop framework. A new scheduling algorithm, Longest Approximate Time to End (LATE), that is highly robust to heterogeneity. There are factors which will make Hadoop more reliable scalable and efficient. With extensive survey we have gone through various papers and studied mechanism for improving performance of MapReduce architecture. Keywords—component; formatting; style; styling; insert (key words)
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