Map Reduce Performance Evaluation: A Step Towards Big Data Optimization

Zanab Safdar, Shafiq Hussain, Shabir Ahmad, Rana Abu Bakar1


There is a marvelous growth in the volume of data processed every day. The revolution has taken us to the level where we are trying to find the technology suitable for the amount of data in pet bytes and zeta bytes. With the change in the market, it has become a compulsion for the business to compete strategically with the competitors. Decision support plays a vigorous part in this regard. The concern is that we need sound technology for processing an enormous amount of data and do it with efficiency and reliability. Performance optimization of MapReduce is critical in the sense that it is leading us to the optimization of big data. Increasing the performance of MapReduce will lead us to an optimized state of big data. In this paper, we explore the performance problems associated to the processing of MapReduce and reviewed different models relating to the performance evaluation of MapReduce processing.

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