Title :
Ophidia: A full software stack for scientific data analytics
Author :
Fiore, S. ; D´Anca, Alessandro ; Elia, Donatello ; Palazzo, Cosimo ; Foster, Ian ; Williams, Doug ; Aloisio, Giovanni
Author_Institution :
Centro Euro-Mediterraneo sui Cambiamenti Climatici, Lecce, Italy
Abstract :
The Ophidia project aims to provide a big data analytics platform solution that addresses scientific use cases related to large volumes of multidimensional data. In this work, the Ophidia software infrastructure is discussed in detail, presenting the entire software stack from level-0 (the Ophidia data store) to level-3 (the Ophidia web service front end). In particular, this paper presents the big data cube primitives provided by the Ophidia framework, discussing in detail the most relevant and available data cube manipulation operators. These primitives represent the proper foundations to build more complex data cube operators like the apex one presented in this paper. A massive data reduction experiment on a 1TB climate dataset is also presented to demonstrate the apex workflow in the context of the proposed framework.
Keywords :
Big Data; Web services; data analysis; data reduction; Ophidia Web service front end; Ophidia data store; Ophidia software infrastructure; big data analytics platform; big data cube primitives; data reduction; scientific data analytics; software stack; Arrays; Big data; Data models; Meteorology; Servers; Web services; big data; data analytics; multidimensional data; scientific workflow; software infrastructure;
Conference_Titel :
High Performance Computing & Simulation (HPCS), 2014 International Conference on
Conference_Location :
Bologna
Print_ISBN :
978-1-4799-5312-7
DOI :
10.1109/HPCSim.2014.6903706