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Abstract
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Article Information:
HADOOP+Big Data: Analytics Using Series Queue with Blocking Model
S. Koteeswaran, P. Visu, K. Silambarasan and R. Vimal Karthick
Corresponding Author: S. Koteeswaran
Submitted: February 11, 2014
Accepted: June 08, 2014
Published: July 15, 2014 |
Abstract:
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Big data deals with large volumes of tons and tons of data. Since managing this much amount of data is not in the mere way for the traditional data mining techniques. Technology is in the world of pervasive environment i.e., technology follows up with its tremendous growth. Hence coordinating these amount of data in a linear way is mere little difficult, hence we proposed a new scheme in order to draw the data and data transformation in large data base. We extended our work in HADOOP (one of the big data managing tool). Our model is fully based on aggregation of data and data modelling. Our proposed model leads to high end data transformation for big data processing. We achieved our analytical result by applying our model with 2 HADOOP clusters, 4 nodes and with 25 jobs in MR functionality.
Key words: Big data, blocking queue, data rendering, hadoop, map reduce, ,
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Cite this Reference:
S. Koteeswaran, P. Visu, K. Silambarasan and R. Vimal Karthick, . HADOOP+Big Data: Analytics Using Series Queue with Blocking Model. Research Journal of Applied Sciences, Engineering and Technology, (3): 341-345.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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