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Paralleles CBAR-Verfahren im Hadoop-MapReduce-Rahmen

Paralleles CBAR-Verfahren im Hadoop-MapReduce-Rahmen

Sayantan Singha Roy

52,01 €
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Editorial:
KS OmniScriptum Publishing
Año de edición:
2024
Materia
Tecnología: cuestiones generales
ISBN:
9786208363222
52,01 €
IVA incluido
Disponible

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Sobre IBD

Das Clustering von Daten ist eine weit verbreitete Herausforderung in der Big-Data-Verarbeitung, und die Parallelisierung von Clustering-Vorgängen steigert die Effizienz von Anwendungen mit häufigen Suchvorgängen erheblich. Für die Datengruppierung stehen verschiedene Clustering-Techniken zur Verfügung, wobei CBAR in verschiedenen Anwendungen weit verbreitet ist. Die Parallelisierung von CBAR ist für Big Data unerlässlich, und die Hadoop MapReduce-Plattform bietet einen geeigneten Rahmen, um die Effizienz durch den Einsatz effektiver Segmentierungstechniken zu verbessern. In diesem Buch werden Algorithmen für CBAR unter Verwendung des MapReduce-Ansatzes entworfen und implementiert, wobei Tests auf Clustern mit bis zu 4 Knoten durchgeführt werden. Die Ergebnisse zeigen erhebliche Leistungssteigerungen, die anhand von anschaulichen Beispielen analysiert und diskutiert werden.

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