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Paralleles CBAR-Verfahren im Hadoop-MapReduce-Rahmen
Paperback
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ISBN10: 6208363225
ISBN13: 9786208363222
Publisher: Verlag Unser Wissen
Published: Dec 9 2024
Pages: 68
Weight: 0.25
Height: 0.16 Width: 6.00 Depth: 9.00
Language: German
ISBN13: 9786208363222
Publisher: Verlag Unser Wissen
Published: Dec 9 2024
Pages: 68
Weight: 0.25
Height: 0.16 Width: 6.00 Depth: 9.00
Language: German
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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