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Fragmenting Big Data to Boost the Performance of MapReduce ..:
, In:
2017 International Conference on Big Data Innovations and Applications (Innovate-Data)
,
Cavallo, Marco
;
Di Modica, Giuseppe
;
Polito, Carmelo
. - p. 17-24 , 2017
Link:
https://doi.org/10.1109/Innovate-Data.2017.12
RT T1 <cTitle>2017 International Conference on Big Data Innovations and Applications (Innovate-Data)</cTitle>: T1 <Title>Fragmenting Big Data to Boost the Performance of MapReduce in Geographical Computing Contexts</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-8316295&Exemplar=1&LAN=DE A1 Cavallo, Marco A1 Di Modica, Giuseppe A1 Polito, Carmelo A1 Tomarchio, Orazio YR 2017 K1 Big Data K1 Task analysis K1 Computational modeling K1 Data models K1 Distributed databases K1 Processor scheduling K1 MapReduce K1 Data fragmentation K1 Geographical computing environment K1 Hierarchical Hadoop SP 17 OP 24 LK http://dx.doi.org/https://doi.org/10.1109/Innovate-Data.2017.12 DO https://doi.org/10.1109/Innovate-Data.2017.12 SF ELIB - SuUB Bremen
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