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Reseach Article

A Review of Hadoop Ecosystem for BigData

by Ashlesha S. Nagdive, R. M. Tugnayat
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 180 - Number 14
Year of Publication: 2018
Authors: Ashlesha S. Nagdive, R. M. Tugnayat
10.5120/ijca2018916273

Ashlesha S. Nagdive, R. M. Tugnayat . A Review of Hadoop Ecosystem for BigData. International Journal of Computer Applications. 180, 14 ( Jan 2018), 35-40. DOI=10.5120/ijca2018916273

@article{ 10.5120/ijca2018916273,
author = { Ashlesha S. Nagdive, R. M. Tugnayat },
title = { A Review of Hadoop Ecosystem for BigData },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2018 },
volume = { 180 },
number = { 14 },
month = { Jan },
year = { 2018 },
issn = { 0975-8887 },
pages = { 35-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume180/number14/28932-2018916273/ },
doi = { 10.5120/ijca2018916273 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:04:25.283292+05:30
%A Ashlesha S. Nagdive
%A R. M. Tugnayat
%T A Review of Hadoop Ecosystem for BigData
%J International Journal of Computer Applications
%@ 0975-8887
%V 180
%N 14
%P 35-40
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper, describes Concept of Big Data which is collection of large data set that cannot be proceed by traditional computational techniques. Therefore Hadoop technology designed to process Big Data. Hadoop is the platform in businesses for Big Data processing. Hadoop is an open source, Java-based programming framework which supports the processing and storage of extremely large data sets in a distributed computing environment. It helps Big Data analytics by overcoming the difficulties that are usually faced in handling Big Data. Hadoop can break down large computational problems into smaller tasks as smaller elements can be analyzed economically and quickly[1]. Hadoop is an open-source software framework for storing data and running applications on clusters of commodity hardware. It provides massive storage for various kind of data, enormous processing power and the ability to handle virtually limitless concurrent tasks. All these parts are analyzed in parallel and the results of the analysis are regrouped to produce the final output.

References
  1. BaoRong Chang, Yo-Ai Wang, Yun-Da Lee, and Chien-FengHuang, "Development of Multiple Big Data Analysis Platforms for Business Intelligence", Proceedings of the 2017 IEEE International Conference on Applied System Innovation
  2. Chu-Hsing Lin, Jung-Chun Liu, Tsung-Chi Peng, "Performance Evaluation of Cluster Algorithms for Big Data Analysis on Cloud", Proceedings of the 2017 IEEE International Conference on Applied System Innovation
  3. https://intellipaat.com/tutorial/hadooptutorial/introduction- hadoop/
  4. Apache Hadoop. http://hadoop.apache.org/
  5. Ms.Preeti Narooka, Dr.Sunita Choudhary, "Optimization of the Search Graph Using Hadoop andLinux Operating System", 2017 International Conference on Nascent Technologies in the Engineering Field (ICNTE-2017) IEEE-ICASI 2017.
  6. Yu-Sheng Su1, Ting-Jou Ding2, Jiann-Hwa Lue3, Chin-Feng Lai4, Chiu-Nan Su5,"Applying Big Data Analysis Technique to Students’ Learning Behavior and Learning", Proceedings of the 2017 IEEE International Conference on Applied System Innovation IEEE-ICASI 2017.
Index Terms

Computer Science
Information Sciences

Keywords

Big Data Hadoop Architecture Apache Hadoop Mapreduce Hadoop Ecosystem Hadoop Distributed File System (HDFS).