MapReduce: an infrastructure review and research insights

In the current decade, doing the search on massive data to find “hidden” and valuable information within it is growing. This search can result in heavy processing on considerable data, leading to the development of solutions to process such huge information based on distributed and parallel processi...

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Veröffentlicht in:	The Journal of supercomputing Jg. 75; H. 10; S. 6934 - 7002
Hauptverfasser:	Maleki, Neda, Rahmani, Amir Masoud, Conti, Mauro
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.10.2019 Springer Nature B.V
Schlagworte:	Compilers Computer Science Data search Fault tolerance Infrastructure Interpreters Parallel processing Parallel programming Processor Architectures Programming Languages Provisioning Resource allocation Task scheduling Parallel and distributed programming model Systematic review MapReduce paradigm Hadoop
ISSN:	0920-8542, 1573-0484
Online-Zugang:	Volltext
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