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mapreduce framework optimization via performance modeling
Xu Lijie
2012
会议名称2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2012
会议日期May 21, 2012 - May 25, 2012
会议地点Shanghai, China
关键词Data processing Distributed parameter networks Scheduling
页码2506-2509
中文摘要MapReduce framework has become the state-of-the-art paradigm for large-scale data processing. In our ongoing work, we attempt to solve the three interrelated problems: how to build an accurate MapReduce performance model, how to use it to automatically detect and optimize slow-running MapReduce jobs, and how to use it to help scheduler arrange job execution sequence. Currently, we mainly study the job execution time model and its training method. We also present several policies to optimize the job configuration and scheduler. © 2012 IEEE.
英文摘要MapReduce framework has become the state-of-the-art paradigm for large-scale data processing. In our ongoing work, we attempt to solve the three interrelated problems: how to build an accurate MapReduce performance model, how to use it to automatically detect and optimize slow-running MapReduce jobs, and how to use it to help scheduler arrange job execution sequence. Currently, we mainly study the job execution time model and its training method. We also present several policies to optimize the job configuration and scheduler. © 2012 IEEE.
收录类别EI ; ISTP
会议主办者IEEE Computer Society Technical Committee on Parallel Processing
会议录Proceedings of the 2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2012
学科主题Computer Science
语种英语
ISSN号2164-7062
ISBN号9780769546766
内容类型会议论文
源URL[http://ir.iscas.ac.cn/handle/311060/15782]  
专题软件研究所_软件所图书馆_会议论文
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Xu Lijie. mapreduce framework optimization via performance modeling[C]. 见:2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2012. Shanghai, China. May 21, 2012 - May 25, 2012.
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