Interactive Visualization Platform Based on MapReduce

Jialiang Wang; Bo Qin; Jianjian Liu; Ni Liu

doi:10.11959/j.issn.1000-0801.2012.09.004

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Interactive Visualization Platform Based on MapReduce

Cloud computing column;Cloud computing column | 更新时间：2024-06-05

- Interactive Visualization Platform Based on MapReduce
- Telecommunications Science Vol. 28, Issue 9, Pages: 22-27(2012)
- 作者机构：
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- DOI：10.11959/j.issn.1000-0801.2012.09.004
  CLC：
- Published Online：2012-09，
  
  Published：15 September 2012
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Jialiang Wang, Bo Qin, Jianjian Liu, et al. Interactive Visualization Platform Based on MapReduce[J]. Telecommunications science, 2012, 28(9): 22-27.
DOI：

Jialiang Wang, Bo Qin, Jianjian Liu, et al. Interactive Visualization Platform Based on MapReduce[J]. Telecommunications science, 2012, 28(9): 22-27. DOI： 10.11959/j.issn.1000-0801.2012.09.004.

摘要

针对长时间序列的海洋环境信息交互可视化处理问题，本文提出一种基于云环境的交互可视化平台架构。可视化平台以Hadoop为基础，将GPU、MPI并行计算引入MapReduce处理机制，实现海洋环境空间数据场大规模数据集的检索、抽取、插值计算、特征可视化分析的并行处理，达到海量数据的远程交互可视化处理目的。实验结果表明，本文提出的可视化平台架构可以有效地将MPI、GPU并行计算与MapReduce处理机制相结合，以满足海洋环境信息交互可视化的需求。

Abstract

For dealing with the problem of ocean data's interactive visualization

this paper proposes an interactive visualization platform architecture based on cloud computing. It inserts GPU

MPI parallel computing into MapReduce mechanism of Hadoop to realize the parallel processing of large-scale ocean environment data sets

such as data retrieval

data extraction

data interpolation

analysis of characteristics' visualization

so that the massive data's visualization can be processed in the remote interactive way. The experiment results show that the visualization platform architecture can combine MPI

GPU with MapReduce effectively to meet the needs of ocean data's interactive visualization.

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Keywords

references

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曾诚，李兵，何克清． . 云计算的栈模型研究 . 微电子学与计算机， 2009 , 26 ( 8 ): 22 ～ 27

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卢风顺，宋君强，银福康等 . CPU/GPU协同并行计算研究综述 . 计算机科学， 2009 , 38 ( 3 ): 5 ～ 9

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Condie T , Conway N , Alvaro P , et al . MapReduce OnLine, UCB/EECS-2009-136 , Berkeley: Electrical Engineering and Computer Sciences University of California , 2009

Lu T , Wang Bing , Zha Li , et al . Can MPI benefit Hadoop and MapReduce applications , Proceedings of 2011 International Conference on Parallel Processing Workshops , Taipei, China , 2011 : 371 ～ 379

Crochow K , Howe B , Stoermer M , et al . Client+Cloud:evaluating seamless architectures for visual data analytics in the ocean sciences , Proceedings of 22nd International Conference on Scientific and Statistical Database Management , Berlin , 201０ : 114 ～ 131

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