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Parallel CBAR Technique in Hadoop-MapReduce Framework

Parallel CBAR Technique in Hadoop-MapReduce Framework

Paperback

Technology & Engineering

ISBN10: 3659912751
ISBN13: 9783659912757
Publisher: LAP Lambert Academic Publishing
Published: Nov 14 2024
Pages: 76
Weight: 0.27
Height: 0.18 Width: 6.00 Depth: 9.00
Language: English
Data clustering is a prevalent challenge in big data processing, and parallelizing clustering operations significantly enhances efficiency in applications involving frequent searches. Various clustering techniques are available for data grouping, with CBAR being widely used across different applications. Parallelizing CBAR is essential for big data, and the Hadoop MapReduce platform offers a suitable framework to improve efficiency by leveraging effective segmentation techniques. This book involves designing and implementing algorithms for CBAR using the MapReduce approach, with testing conducted on clusters of up to 4 nodes. The results demonstrate substantial performance gains, which are analyzed and discussed with illustrative examples.

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Singha Roy, Sayantan

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Technology & Engineering