Hadoop Map Reduce Over Multiple Distributed Storage System

Authors

  • Rajalakshmi R Dept. of Computer Science, ARJ College of Engineering & Technology, Mannargudi, Thiruvarur
  • Sharmila V Dept. of Computer Science, ARJ College of Engineering & Technology, Mannargudi, Thiruvarur

DOI:

https://doi.org/10.26438/ijcse/v7i2.923927

Keywords:

Multiple distributed system, hadoop, Data mining

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.

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Published

2019-02-28
CITATION
DOI: 10.26438/ijcse/v7i2.923927
Published: 2019-02-28

How to Cite

[1]
R. Rajalakshmi and V. Sharmila, “Hadoop Map Reduce Over Multiple Distributed Storage System”, Int. J. Comp. Sci. Eng., vol. 7, no. 2, pp. 923–927, Feb. 2019.

Issue

Vol. 7 No. 2 (2019): IJCSE February Edition

Section

Research Article

License

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