A Novel Location Awareing Mapreducing Techniques Using Big Data Applications

Authors

  • Buthukuri B Department of CSE, Shri JagadishPrasad Jabarmal Tibrewala University, Jhun Jhunu, INDIA
  • Purushoththaman ME Department of Computer Science and Engineering, JNTUH, INDIA

DOI:

https://doi.org/10.26438/ijcse/v6i5.10821091

Keywords:

Map Reduce Framework, Hadoop, Data Mining, Query Processing, Data Analysis,

Abstract

There is a growing trend of applications that should handle big data. However, analyzing big data is a very challenging problem today. For such applications, the MapReduce framework has recently attracted a lot of attention. Google's MapReduce or its open-source equivalent Hadoop is a powerful tool for building such applications. In this paper, we will discuss the MapReduce framework based on Hadoop, and how to design efficient MapReduce algorithms and present the state-of-the-art in MapReduce algorithms for data mining, machine learning, query processing, data analysis and similarity joins. The intended audience of this tutorial is professionals who plan to design and develop MapReduce algorithms and researchers who aware of the state-of-the-art in MapReduce algorithms available today for big data analysis

References

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Published

2025-11-13
CITATION
DOI: 10.26438/ijcse/v6i5.10821091
Published: 2025-11-13

How to Cite

[1]
B. Buthukuri and M. E. Purushoththaman, “A Novel Location Awareing Mapreducing Techniques Using Big Data Applications”, Int. J. Comp. Sci. Eng., vol. 6, no. 5, pp. 1082–1091, Nov. 2025.

Issue

Vol. 6 No. 5 (2018): IJCSE May Edition

Section

Research Article

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