Enhancing the Performance of Traditional Hadoop Using AWS with EMR Approach

  • Parul Dubey, Dr. Gurpreet Singh Chhabra, Riju Bhattacharya, Teshu Gaurav Singh
Keywords: Big data Analysis, Real time processing, Hadoop, Map Reduce, Transaction, Data set, Utility, Amazon Elastic MapReduce, EC2.

Abstract

In this on-demand, on command digital universe we have data growing at exponential rate. This data is growing in its volume, variety and velocity as a result it is called “Big Data”. Analysis of this growing data is a challenging job due to the involvement of large distributed file system. Map-Reduce in traditional Hadoop architecture is well known for analyzing big data. Amazon Map-Reduce programming model is introduced by Amazon to work with Amazon computing model and its data storage services. This approach is elastic in its nature hence, called Elastic Map-Reduce(EMR). In Amazon Web Services (AWS) made use of Amazon EC2 model and Amazon S3 is used for storing large complex data. In this paper, the proposed work is to understand the analysis and implementationof Hadoop on top of Amazon  EMR approach. This make use of Amazon Services , nodes, compute services, security and  management tools.

Published
2021-09-30
How to Cite
Teshu Gaurav Singh, P. D. D. G. S. C. R. B. (2021). Enhancing the Performance of Traditional Hadoop Using AWS with EMR Approach. Design Engineering, 571-580. Retrieved from http://thedesignengineering.com/index.php/DE/article/view/4901
Section
Articles