The Study of Hadoop Application across Multiple Data Centers

DOI

10.2991/iiicec-15.2015.144How to use a DOI?

Keywords

data-intensive computing; data center; Hadoop; hierarchical distributed computing; across multiple clusters

Abstract

Hadoop is a reasonable tool for cloud computing in big data and MapReduce paradigm may be a highly successful programming model for large-scale data-intensive computing application. However, traditional Hadoop and MapReduce have been deployed over local or tightly-coupled cloud resources with one data center. This paper focuses on the issue of Hadoop application across multiple data centers. A hierarchical distributed computing architecture of Hadoop is designed and proposed. The job submitted by user can be decomposed automatically into several subtasks which are then allocated and executed on corresponding cluster by location-aware manner. The presentation of the workflow shows the operating principle of this architecture.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Aizhi Wu
PY  - 2015/03
DA  - 2015/03
TI  - The Study of Hadoop Application across Multiple Data Centers
BT  - Proceedings of the 2015 International Industrial Informatics and Computer Engineering Conference
PB  - Atlantis Press
SP  - 633
EP  - 636
SN  - 2352-538X
UR  - https://doi.org/10.2991/iiicec-15.2015.144
DO  - 10.2991/iiicec-15.2015.144
ID  - Wu2015/03
ER  -