DocumentCode :
659571
Title :
A big data analytics framework for scientific data management
Author :
Fiore, S. ; Palazzo, Cosimo ; D´Anca, Alessandro ; Foster, Ian ; Williams, Dean N. ; Aloisio, Giovanni
Author_Institution :
Centro Euro-Mediterraneo sui Cambiamenti Climatici, Italy
fYear :
2013
fDate :
6-9 Oct. 2013
Firstpage :
1
Lastpage :
8
Abstract :
The Ophidia project is a research effort addressing big data analytics requirements, issues, and challenges for eScience. We present here the Ophidia analytics framework, which is responsible for atomically processing, transforming and manipulating array-based data. This framework provides a common way to run on large clusters analytics tasks applied to big datasets. The paper highlights the design principles, algorithm, and most relevant implementation aspects of the Ophidia analytics framework. Some experimental results, related to a couple of data analytics operators in a real cluster environment, are also presented.
Keywords :
Big Data; data analysis; natural sciences computing; pattern clustering; Ophidia analytics framework; Ophidia project; array-based data manipulation; array-based data processing; array-based data tranformation; big data analytics framework; cluster analytics task; data analytics operators; eScience; scientific data management; Arrays; Data handling; Information management; Libraries; Meteorology; Servers; big data; data analytics; eScience; parallel I/O;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Big Data, 2013 IEEE International Conference on
Conference_Location :
Silicon Valley, CA
Type :
conf
DOI :
10.1109/BigData.2013.6691720
Filename :
6691720
Link To Document :
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