SciHadoop array-based query processing in Hadoop

Hadoop has become the de facto platform for large-scale data analysis in commercial applications, and increasingly so in scientific applications. However, Hadoop's byte stream data model causes inefficiencies when used to process scientific data that is commonly stored in highly-structured, arr...

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Vydané v:	2011 International Conference for High Performance Computing, Networking, Storage and Analysis (SC) s. 1 - 11
Hlavní autori:	Buck, Joe B., Watkins, Noah, LeFevre, Jeff, Ioannidou, Kleoni, Maltzahn, Carlos, Polyzotis, Neoklis, Brandt, Scott
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	New York, NY, USA ACM 12.11.2011 IEEE
Edícia:	ACM Conferences
Predmet:	Arrays Data analysis Data intensive Data models Human-centered computing > Visualization > Visualization application domains > Scientific visualization Information systems > Data management systems > Database management system engines > Database query processing Information systems > Information retrieval > Search engine architectures and scalability > Distributed retrieval Information systems > Information retrieval > Search engine architectures and scalability > Peer-to-peer retrieval Information systems > Information storage systems > Storage architectures > Distributed storage Information systems > Information systems applications Layout Libraries map reduce Optimization query optimization scientific file-formats Semantics Theory of computation > Theory and algorithms for application domains > Database theory > Database query processing and optimization (theory) query optimization scientific file-formats data intensive map reduce
ISBN:	145030771X, 9781450307710
ISSN:	2167-4329
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