Spark-DIY: A framework for interoperable Spark Operations with high performance Block-Based Data Models

Caino Lores, Silvina; Carretero Pérez, Jesús; Nicolae, Bogdan; Yildiz, Orcun; Peterka, Tom

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Spark-DIY: A framework for interoperable Spark Operations with high performance Block-Based Data Models

Author(s): Caino Lores, Silvina; Carretero Pérez, Jesús; Nicolae, Bogdan; Yildiz, Orcun; Peterka, Tom

Publisher: Ieee Computer Society

Issued date: 2018-12-17

Citation: S. Caíno-Lores, J. Carretero, B. Nicolae, O. Yildiz and T. Peterka, "Spark-DIY: A Framework for Interoperable Spark Operations with High Performance Block-Based Data Models," 2018 IEEE/ACM 5th International Conference on Big Data Computing Applications and Technologies (BDCAT), 2018, pp. 1-10, doi: 10.1109/BDCAT.2018.00010.

ISBN: 978-1-5386-5502-3

DOI: https://doi.org/10.1109/BDCAT.2018.00010

xmlui.dri2xhtml.METS-1.0.item-contributor-funder: Ministerio de Economía, Industria y Competitividad (España)
Ministerio de Educación, Cultura y Deporte (España)

Sponsor: This work was partially funded by the Spanish Ministry of Economy, Industry and Competitiveness under the grant TIN2016-79637-P ”Towards Unification of HPC and Big Data Paradigms”; the Spanish Ministry of Education under the FPU15/00422 Training Program for Academic and Teaching Staff Grant; the Advanced Scientific Computing Research, Office of Science, U.S. Department of Energy, under Contract DE-AC02-06CH11357; and by DOE with agreement No. DE-DC000122495, program manager Laura Biven.

Project: Gobierno de España. TIN2016-79637-P
Gobierno de España. FPU15/00422

Keywords: hpc , big data , spark , MPI , high-performance analytics , programming environments , big data

URI: http://hdl.handle.net/10016/34501

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