Performance Improvement of Heterogeneous Hadoop Clusters Using MapReduce For Big Data
DOI:
https://doi.org/10.26438/ijcse/v5i8.211214Keywords:
Big data, hadoop, heterogeneous clusters, map reduce, throughput, latencyAbstract
The problem that has occurred as a result of the increased connection between the device and the system is creating information at an exponential rate that it is becoming increasingly difficult for a possible solution for processing. Therefore, creating a platform for such advanced level data processing, which increase the level of hardware and software with bright data. In order to improve the efficiency of the Hadoop Cluster in large data collection and analysis, we have proposed an algorithm system that meets the needs of protected discrimination data in Hadoop Clusters and improves performance and efficiency. The proposed paper aims to find out the effectiveness of the new algorithm, compare, consultation, and find out the best solution for improving the big data scenario is a competitive approach. The map reduction techniques from Hadoop will help maintain a close watch on the underlying or discriminatory Hadoop clusters with insights of results as expected from the luminosity.
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