mapreduce framework optimization via performance modeling
文献类型：会议论文
| 作者 | Xu Lijie |
| 出版日期 | 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 |
| 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 |
| 推荐引用方式 GB/T 7714 | 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. |
入库方式： OAI收割
来源：软件研究所
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