RT Conference Proceedings
T1 A Workflow-oriented Language for Scalable Data Analytics
A1 Marozzo, Fabrizio
A1 Talia, Domenico
A1 Trunfio, Paolo
A2 Carretero Pérez, Jesús
A2 García Blas, Javier
A2 Barbosa, Jorge
A2 Morla, Ricardo
A2 Universidad Carlos III de Madrid. Computer Architecture, Communications and Systems Group (ARCOS)
AB Data in digital repositories are everyday more and more massive and distributed. Therefore analyzing them requires efficient data analysis techniques and scalable storage and computing platforms. Cloud computing infrastructures offer an effective support for addressing both the computational and data storage needs of big data mining and parallel knowledge discovery applications. In fact, complex data mining tasks involve data- and compute-intensive algorithms that require large and efficient storage facilities together with high performance processors to get results in acceptable times. In this paper we describe a Data Mining Cloud Framework (DMCF) designed for developing and executing distributed data analytics applications as workflows of services. We describe also a workflow-oriented language, called JS4Cloud, to support the design and execution of script-based data analysis workflows on DMCF. We finally present a data analysis application developed with JS4Cloud, and the scalability achieved executing it on DMCF.
SN 978-84-617-2251-8
YR 2014
FD 2014-11
LK https://hdl.handle.net/10016/21982
UL https://hdl.handle.net/10016/21982
LA eng
NO Proceedings of: First International Workshop on Sustainable Ultrascale Computing Systems (NESUS 2014). Porto (Portugal), August 27-28, 2014.
NO The work presented in this paper has been partially supported by EU under the COST programme Action IC1305, ’Network for Sustainable Ultrascale Computing (NESUS)’.
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RD 17 jul. 2024