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R. Lovas^1,2, E. Nagy^1,2 and J. Kovács¹

¹Institute for Computer Science and Control, Hungarian Academy of Sciences (MTA SZTAKI), Budapest, Hungary
²John von Neumann Faculty of Informatics, O´ buda University, Budapest, Hungary

doi:10.4203/ccp.111.15

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R. Lovas, E. Nagy, J. Kovacs , "Cloud Agnostic Orchestration for Big Data Research Platforms", in , (Editors), "Proceedings of the Fifth International Conference on Parallel, Distributed, Grid and Cloud Computing for Engineering", Civil-Comp Press, Stirlingshire, UK, Paper 15, 2017. doi:10.4203/ccp.111.15

Keywords: cloud computing, orchestration, Hadoop, Occopus, contextualization.

Summary

Nowadays a significant part of the cloud applications process large amount of data to provide the desired analytics, simulation and other results. Cloud infrastructures are becoming an appropriate and widely used solution to address the computation need of many scientific and commercial Big Data applications. In this paper, we present a solution of an automatic Hadoop infrastructure deployment on cloud with the Occopus cloud orchestrator. This solution provides an easy-to-use, portable, scalable, automatic deployment of Hadoop particularly for non-commercial clouds in order to avoid vendor locking issues, i.e. there is no dependency on any provider prepared virtual machine image, etc.

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Front Page Browse CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Proceedings ISSN 1759-3433 CCP: 111 PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON PARALLEL, DISTRIBUTED, GRID AND CLOUD COMPUTING FOR ENGINEERING Edited by: Paper 15 Cloud Agnostic Orchestration for Big Data Research Platforms R. Lovas^1,2, E. Nagy^1,2 and J. Kovács¹ ¹Institute for Computer Science and Control, Hungarian Academy of Sciences (MTA SZTAKI), Budapest, Hungary ²John von Neumann Faculty of Informatics, O´ buda University, Budapest, Hungary doi:10.4203/ccp.111.15 purchase the full-text of this paper Full Bibliographic Reference for this paper R. Lovas, E. Nagy, J. Kovacs , "Cloud Agnostic Orchestration for Big Data Research Platforms", in , (Editors), "Proceedings of the Fifth International Conference on Parallel, Distributed, Grid and Cloud Computing for Engineering", Civil-Comp Press, Stirlingshire, UK, Paper 15, 2017. doi:10.4203/ccp.111.15 Keywords: cloud computing, orchestration, Hadoop, Occopus, contextualization. Summary Nowadays a significant part of the cloud applications process large amount of data to provide the desired analytics, simulation and other results. Cloud infrastructures are becoming an appropriate and widely used solution to address the computation need of many scientific and commercial Big Data applications. In this paper, we present a solution of an automatic Hadoop infrastructure deployment on cloud with the Occopus cloud orchestrator. This solution provides an easy-to-use, portable, scalable, automatic deployment of Hadoop particularly for non-commercial clouds in order to avoid vendor locking issues, i.e. there is no dependency on any provider prepared virtual machine image, etc. purchase the full-text of this paper (price £22) go to the previous paper go to the next paper return to the table of contents return to the book description purchase this book (price £45 +P&P)
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