Conceptualizing big data analytics through Hadoop

Authors

  • Singh MK MCA (MDU) and B.Sc. (APS) Computer Science (University of Delhi)
  • Baluja GS Dept. of Computer Application, DTTE, Govt. of NCT Delhi
  • Sahu DP Ph.D, M.Tech. and MCA (Jawaharlal Nehru University)

Keywords:

Big Data, Big Data Analytics (BDA), 3V Model of Big Data, MapReduce Framework, Hadoop framework, Hadoop Distributed File System (HDFS)

Abstract

Big Data Analytics (BDA) is the matter of great concern in the research and analysis field of data science today. Each and every day, data in petabytes are processed and analyzed from different sources on the Internet. Big organizations and Internet giants leave no stone to use the hidden information of Big Data. Hence, they make use of one algorithm or another algorithm of data science to do the analytics of Big Data. The most successful algorithm that has been developed so far to do effective Big Data Analytics is MapReduce – an algorithm developed and successfully implemented by Google. The data scientists of data science field have been trying hard to build such an architecture that can implement the philosophy of MapReduce to achieve efficient, effective, and the most economical way of doing BDA. In this effort, Apache Hadoop appears to be the most promising technology build so far. This article is an effort to bring the underlying details of Big Data Analytics done through Hadoop.

References

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Agneeswaran, Vijay. P. 2014. Big Data Analytics Beyond Hadoop. Pearson Education Inc.

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Published

2024-02-26

How to Cite

Singh, M. K., Baluja, G. S., & Sahu, D. P. (2024). Conceptualizing big data analytics through Hadoop. COMPUSOFT: An International Journal of Advanced Computer Technology, 6(05), 2335–2339. Retrieved from https://ijact.in/index.php/j/article/view/403

Issue

Section

Original Research Article

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