Parallel CBAR Technique in Hadoop-MapReduce Framework

Parallel CBAR Technique in Hadoop-MapReduce Framework

EnglishPaperback / softbackPrint on demand
Singha Roy, Sayantan
OmniScriptum
EAN: 9783659912757
Print on demand
Delivery on Friday, 7. of March 2025
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Detailed information

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.
EAN 9783659912757
ISBN 3659912751
Binding Paperback / softback
Publisher OmniScriptum
Publication date November 14, 2024
Pages 76
Language English
Dimensions 229 x 152 x 5
Authors Singha Roy, Sayantan