Effective Resource Utilization in Hadoop Using Ganglia

The exponential growth of big data has led to the widespread adoption of Hadoop clusters for storing and processing large volumes of data. Efficient management of resources within these clusters is crucial for achieving optimal performance and cost efficiency. This research paper explores the use of Hadoop and Ganglia for monitoring and optimizing resource utilization in Hadoop clusters. The study demonstrates that leveraging Hadoop and Ganglia is an effective strategy for improving cluster performance and resource efficiency. Results show significant enhancements in cluster performance and resource utilization, highlighting the importance of proactive resource management in Hadoop environments.

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Publication Details

Published
2024-12-06
DOI
https://doi.org/10.1109/ccis63231.2024.10932012
Primary Topic
Cloud Computing and Resource Management
Type
article
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article

Effective Resource Utilization in Hadoop Using Ganglia

Biswajit Bhowmik, Anusha Hegde, Beaula Srungarapati, Mounika Pamarthi et al.
Cloud Computing and Resource Management
article

Effective Resource Utilization in Hadoop Using Ganglia

Biswajit Bhowmik, Anusha Hegde, Beaula Srungarapati, Mounika Pamarthi, Vaishnavi Vakada
article en

Abstract

The exponential growth of big data has led to the widespread adoption of Hadoop clusters for storing and processing large volumes of data. Efficient management of resources within these clusters is crucial for achieving optimal performance and cost efficiency. This research paper explores the use of Hadoop and Ganglia for monitoring and optimizing resource utilization in Hadoop clusters. The study demonstrates that leveraging Hadoop and Ganglia is an effective strategy for improving cluster performance and resource efficiency. Results show significant enhancements in cluster performance and resource utilization, highlighting the importance of proactive resource management in Hadoop environments.

National Institute of Technology Karnataka (IN)
Openalex Percentile: Top 54%
Cloud Computing and Resource Management
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