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. © 2013 IEEE.
A big data analytics framework for scientific data management / Fiore, S.; Palazzo, C.; D'Anca, A.; Foster, I.; Williams, D. N.; Aloisio, G.. - (2013), pp. 1-8. (Intervento presentato al convegno 2013 IEEE International Conference on Big Data, Big Data 2013 tenutosi a Santa Clara, CA, usa nel 2013) [10.1109/BigData.2013.6691720].
A big data analytics framework for scientific data management
Fiore S.;
2013-01-01
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. © 2013 IEEE.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione
