Research Article | OPEN ACCESS
An Extended Form of MATLAB To-map Reduce Frameworks in HADOOP Based Cloud Computing Environments
1T. Tamilvizhi, 2B. Parvatha Varthini, 3K. Manoj and 4R. Surendran
1Research Scholar, Faculty of Computing, Sathyabama University,
Chennai, Tamil Nadu, India
2Professor and Dean, St. Joseph’s College of Engineering, Chennai, Tamil Nadu,
3Faculty of Computing, Sathyabama University, India
4Asst. Professor (IST), Sur University College, Sultanate of Oman
Research Journal of Applied Sciences, Engineering and Technology 2016 9:900-906
Received: September ‎21, ‎2015 | Accepted: January ‎18, ‎2016 | Published: May 05, 2016
Abstract
Aim of study to extend the implementation of Matlab to Mapreduce translation based on the M2M translation technique. Cloud computing is a service which provides services by handling massive amount of data. To handle it effectively it needs some technology like Hadoop. Hadoop is an open source project written in java. It is optimised to handle massive amount of data (structured, unstructured, semi-structured) through parallelism. Thus to achieve this parallelism Hadoop Distributed File System (HDFS) uses Mapreduce as a programming index. Here proposing a translator which converts Matlab commands to Mapreduce commands especially concentrated in executing some basic commands in Mapreduce environment to access large datasets. Matlab is a very effective tool for numerical computing since executing this command in a platform independent, distributed environment makes it more efficient.
Keywords:
Cloud computing, hadoop, mapreduce, matlab, parallel computing,
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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
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