A survey of data partitioning and sampling methods to support big data analysis

Computer clusters with the shared-nothing architecture are the major computing platforms for big data processing and analysis. In cluster computing, data partitioning and sampling are two fundamental strategies to speed up the computation of big data and increase scalability. In this paper, we prese...

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Veröffentlicht in:	Big Data Mining and Analytics Jg. 3; H. 2; S. 85 - 101
Hauptverfasser:	Mahmud, Mohammad Sultan, Huang, Joshua Zhexue, Salloum, Salman, Emara, Tamer Z., Sadatdiynov, Kuanishbay
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Beijing Tsinghua University Press 01.06.2020
Schlagworte:	approximate computing Big Data big data analysis Cluster analysis Computation Data analysis data partitioning Data processing Data sampling distributed and parallel computing Partitioning Random sampling Sampling methods
ISSN:	2096-0654, 2097-406X
Online-Zugang:	Volltext
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