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Hadoop Map Reduce Over Multiple Distributed Storage System

R. Rajalakshmi1 , V. Sharmila2

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-2 , Page no. 923-927, Feb-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i2.923927

Online published on Feb 28, 2019

Copyright © R. Rajalakshmi, V. Sharmila . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: R. Rajalakshmi, V. Sharmila, “Hadoop Map Reduce Over Multiple Distributed Storage System,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.2, pp.923-927, 2019.

MLA Style Citation: R. Rajalakshmi, V. Sharmila "Hadoop Map Reduce Over Multiple Distributed Storage System." International Journal of Computer Sciences and Engineering 7.2 (2019): 923-927.

APA Style Citation: R. Rajalakshmi, V. Sharmila, (2019). Hadoop Map Reduce Over Multiple Distributed Storage System. International Journal of Computer Sciences and Engineering, 7(2), 923-927.

BibTex Style Citation:
@article{Rajalakshmi_2019,
author = {R. Rajalakshmi, V. Sharmila},
title = {Hadoop Map Reduce Over Multiple Distributed Storage System},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {2 2019},
volume = {7},
Issue = {2},
month = {2},
year = {2019},
issn = {2347-2693},
pages = {923-927},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3772},
doi = {https://doi.org/10.26438/ijcse/v7i2.923927}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i2.923927}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3772
TI - Hadoop Map Reduce Over Multiple Distributed Storage System
T2 - International Journal of Computer Sciences and Engineering
AU - R. Rajalakshmi, V. Sharmila
PY - 2019
DA - 2019/02/28
PB - IJCSE, Indore, INDIA
SP - 923-927
IS - 2
VL - 7
SN - 2347-2693
ER -

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Abstract

Distributed computing gives individuals an approach to share substantial mount of distributed assets having a place with various associations. Distributed computing can be characterized as the executives and arrangement of various assets, for example, programming, applications and data as administrations over the cloud (web) on interest. That is a decent method to share numerous sorts of distributed assets, however it likewise makes security issues more entangle and more imperative for clients than previously. In this venture, secure distributed algorithm execute Hadoop Map Reduce structure over multiple distributed storage (MDS) and assess its execution on a general heterogeneous group of gadgets. An actualize the nonexclusive record framework interface of Hadoop for MDS which makes our framework interoperable with other Hadoop systems like HBase. There are no progressions required for existing HDFS applications to be sent over MDS. To the best of our insight, this is the main work to bring Hadoop Map Reduce system for versatile cloud that really addresses the difficulties of the dynamic system condition. Our framework gives a distributed figuring model to handling of huge datasets in versatile condition while guaranteeing solid assurances for vitality productivity, information unwavering quality, Data region and security.

Key-Words / Index Term

Multiple distributed system, hadoop, Data mining

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