A Study on Hadoop Mapreduce Framework in Bigdata
Abstract
Hadoop Map Reduce is processed for analysis large volume of data through multiple nodes. Today we’re surrounded by data like oxygen. The exponential growth of data first presented challenges to cutting-edge businesses such as Google, Yahoo, Amazon, Microsoft, Facebook, Twitter etc.., data volumes to be processed by cloud application are growth much faster than computing power. This growth is demands new strategy for processing and analysing information Hadoop MapReduce has become a powerful computation model address to these problems
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Benjamins, V.R. “Big data: From hype to reality? “ In: Proceedings of the 4th International Conference on Web Intelligence, Mining and Semantics (WIMS14).ACM, New York, NY, USA, 2014, pp. 2:1-2:2.
Assunção, M. D., Calheiros, R. N., Bianchi, S., Netto, M.A.S. ,Buyya, R., “Big Data computing and clouds: Trends and future directions”, Journal of Parallel and Distributed Computing, Volumes 79–80, May,2015,pp. 3-15.
Boyd, D., Crawford, K, “Critical questions for big data. Information”, Communication & Society 15:5, 2012, pp. 662- 679.
Adams, M.N, “Perspectives on Data Mining. International Journal of Market Research 52(1),2012, pp.11–19
Asur, S., Huberman, B.A, “Predicting the Future with Social Media”, In: ACM International Conference on Web Intelligence and Intelligent Agent Technology, vol. 1,2010, pp.492–499
Bakshi, K.,”Considerations for Big Data: Architecture and Approaches”, In: Proceedings of the IEEE Aerospace Conference, 2012, pp. 1–7
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