Implementation of Hadoop Distributed File System Services in an Application

Authors

  • Anto S Department of Information Technology Jyothi Engineering College, Cheruthuruthy, Thrissur, Kerala, India
  • Anila Ramesh K Department of Information Technology Jyothi Engineering College, Cheruthuruthy, Thrissur, Kerala, India
  • Dias L Department of Information Technology Jyothi Engineering College, Cheruthuruthy, Thrissur, Kerala, India
  • Sabna AB Department of Information Technology Jyothi Engineering College, Cheruthuruthy, Thrissur, Kerala, India

Keywords:

Big Data, Fault tolerant, Hadoop Distributed File System

Abstract

Cloud is the collection of computers on the internet that is being offered as a revolutionary storage method for files and Big Data is an evolving term that describes any voluminous amount of structured, semi-structured and unstructured data that has the potential to be mined for information. In our proposed system, we implement a safe method to save Big Data files using Apache Hadoop technology. And here we provide two web services: uploading and downloading of files. Once we upload the files, they are stored in different nodes across the cluster after partitioning. We make the data highly available, by keeping the different copies of data in several nodes. The uploaded files can be retrieved at any time according to our needs. Even if there is a failure at any node, the copy of data on some other nodes makes our system fault tolerant and reliable. Along with that, we can also make our files public or private and thus providing file sharing facility. We offer a security system for storing and managing Big Data files

References

Sivaraman, E.; Manickachezian, R., "High Performance and Fault Tolerant Distributed File System for Big Data Storage and Processing Using Hadoop," International Conference on Intelligent Computing Applications (ICICA), 2014, vol., no., pp.32,36, 6-7 March 2014.

Krishna, T.L.S.R.; Ragunathan, T.; Battula, S.K., "Performance Evaluation of Read and Write Operations in Hadoop Distributed File System," Parallel Architectures, Algorithms and Programming (PAAP), 2014 Sixth International Symposium on , vol., no., pp.110,113, 13-15 July 2014

Shvachko, K.; Hairong Kuang; Radia, S.; Chansler, R., "The Hadoop Distributed File System," in Mass Storage Systems and Technologies (MSST), 2010 IEEE 26th Symposium on , vol., no., pp.1-10, 3-7 May 2010

K.V. Shvachko, “HDFS Scalability: The limits to growth,” login:. April 2010, pp. 6-16.

Manikandan, S.G.; Ravi, S., "Big Data Analysis Using Apache Hadoop," in IT Convergence and Security (ICITCS), 2014 International Conference on , vol., no., pp.1-4, 28-30 Oct. 2014

Devakunchari, R., "Handling big data with Hadoop toolkit," in Information Communication and Embedded Systems (ICICES), 2014 International Conference on , vol., no., pp.1-5, 27-28 Feb. 2014

Downloads

Published

2025-11-10

How to Cite

[1]
S. Anto, K. Anila Ramesh, L. Dias, and A. Sabna, “Implementation of Hadoop Distributed File System Services in an Application”, Int. J. Comp. Sci. Eng., vol. 3, no. 9, pp. 11–14, Nov. 2025.

Issue

Vol. 3 No. 9 (2015): IJCSE September Edition

Section

Research Article

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Authors contributing to this journal agree to publish their articles under the Creative Commons Attribution 4.0 International License, allowing third parties to share their work (copy, distribute, transmit) and to adapt it, under the condition that the authors are given credit and that in the event of reuse or distribution, the terms of this license are made clear.