English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 55218/89515 (62%)
造访人次 : 10720033      在线人数 : 20
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜寻范围 查询小技巧:
  • 您可在西文检索词汇前后加上"双引号",以获取较精准的检索结果
  • 若欲以作者姓名搜寻,建议至进阶搜寻限定作者字段,可获得较完整数据
  • 进阶搜寻


    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/99028


    题名: Adaptive Combiner for MapReduce on cloud computing
    作者: Huang, Tzu-Chi;Chu, Kuo-Chih;Lee, Wei-Tsong;Ho, Yu-Sheng
    贡献者: 淡江大學電機工程學系
    关键词: MapReduce;Combiner;Cloud computing;ACMR
    日期: 2014-03-11
    出版者: New York: Springer New York LLC
    摘要: MapReduce is a programming model to process a massive amount of data on cloud computing. MapReduce processes data in two phases and needs to transfer intermediate data among computers between phases. MapReduce allows programmers to aggregate intermediate data with a function named combiner before transferring it. By leaving programmers the choice of using a combiner, MapReduce has a risk of performance degradation because aggregating intermediate data benefits some applications but harms others. Now, MapReduce can work with our proposal named the Adaptive Combiner for MapReduce (ACMR) to automatically, smartly, and trainer for getting a better performance without any interference of programmers. In experiments on seven applications, MapReduce can utilize ACMR to get the performance comparable to the system that is optimal for an application.
    關聯: Cluster Computing 17(4), pp.1231-1252
    DOI: 10.1007/s10586-014-0362-3
    显示于类别:[電機工程學系暨研究所] 期刊論文

    文件中的档案:

    没有与此文件相关的档案.

    在機構典藏中所有的数据项都受到原著作权保护.

    TAIR相关文章

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回馈