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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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Parallel CBAR Technique in Hadoop-MapReduce Framework (Paperback)
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Paperback. Condizione: new. Paperback. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9783659912757
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Parallel CBAR Technique in Hadoop-MapReduce Framework
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Parallel CBAR Technique in Hadoop-MapReduce Framework (Paperback)
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ISBN 13: 9783659912757
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Paperback. Condizione: new. Paperback. 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. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9783659912757
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