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Bonfring International Journal of Software Engineering and Soft Computing

Impact Factor: 0.375 | International Scientific Indexing(ISI) calculate based on International Citation Report(ICR)




Distributed Data Storage Technique for Big Data using Hadoop

M.M. Kodabagi, Savita Rathod and Vilas Naik


Nowadays the data size and domains of data is increasing because of the use by both public and private sectors. The size of the data is increasing every year by double the rate. There are mainly three types of data structured, unstructured and semi-structured data. The existing systems were unable to store the structured, unstructured and semi-structured data in a single database, Big data is used to store such data. As day by need data size in increasing we need storage management in Big data. The objective of the proposed work is to design HDFS based distributed data storage for Big data, contains different types of Multimedia data such as text, audio, images, Log files and web based data. In proposed work there are three nodes one is master and two are slaves. Mainly data is stored in master and in both slaves data is distributed to avoid loss of data. Users can access the data from nearest slave Incase one of the slave fails data can be accessed from other slaves. If both slaves fails data can be retrieved from master.

Keywords: Big data, Hadoop , HDFS, MapReduce.

Volume: 6 | Issue: Special Issue on Advances in Computer Science and Engineering and Workshop on Big Data Analytics Editors: Dr.S.B. Kulkarni, Dr.U.P. Kulkarni, Dr.S.M. Joshi and J.V. Vadavi

Pages: 43-48

Issue Date: October , 2016

DOI: 10.9756/BIJSESC.8240

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