Research Article | OPEN ACCESS
HADOOP+Big Data: Analytics Using Series Queue with Blocking Model
S. Koteeswaran, P. Visu, K. Silambarasan and R. Vimal Karthick
Department of CSE, Vel Tech RR and SR Technical University, Chennai-600 062, India
Research Journal of Applied Sciences, Engineering and Technology 2014 3:341-345
Received: February 11, 2014 | Accepted: June 08, 2014 | Published: July 15, 2014
Abstract
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.
Keywords:
Big data , blocking queue , data rendering , hadoop , map reduce,
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Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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