Job-Aware Optimization of File Placement in Hadoop
Job-Aware Optimization of File Placement in Hadoop
复制标题
Hadoop 中文件放置的作业感知优化
DOI:
10.1109/compsac.2019.10284
复制
发表时间:
2019
期刊:
影响因子:
--
通讯作者:
Yamaguchi, Saneyasu
中科院分区:
文献类型:
--
作者:
Nakagami, Makoto;Fortes, Jose A.;Yamaguchi, Saneyasu
Hadoop is a popular data-analytics platform based on the MapReduce model. When analyzing extremely big data, hard disk drives are commonly used and Hadoop performance can be optimized by improving I/O performance. Hard disk drives have different performance depending on whether data are placed in the outer or inner disk zones. In this paper, we propose a method that uses knowledge of job characteristics to place data in hard disk drives so that Hadoop performance is improved. Files of a job that intensively and sequentially accesses the storage device are placed in outer disk tracks which have higher sequential access speed than inner tracks. Temporary and permanent files are placed in the outer and inner zones, respectively. This enables repeated usage of the faster zones by avoiding the use of the fastest zones by permanent files. Our evaluation demonstrates that the proposed method improves the performance of the Hadoop jobs by 15.0% over the normal case when file placement is not used. The proposed method also outperforms a previously proposed placement approach by 9.9%.
DOI:
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发表时间:
2005
期刊:
International Symposium on Applications and the Internet
影响因子:
--
作者:
Saneyasu Yamaguchi;M. Oguchi;M. Kitsuregawa
通讯作者:
M. Kitsuregawa
DOI:
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发表时间:
2016
期刊:
影响因子:
--
作者:
Eita Fujishima;Saneyasu Yamaguchi
通讯作者:
Saneyasu Yamaguchi
DOI:
--
发表时间:
2006
期刊:
LECTRONICS and COMMUNICATIONS in JAPAN (Part 3 : Fundamental Electronic Science) VOLUME 89, NUMBER 4
影响因子:
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作者:
Saneyasu Yamaguchi;Masato Oguchi;Masaru Kitsuregawa
通讯作者:
Masaru Kitsuregawa