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    請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/99028

    題名: Adaptive Combiner for MapReduce on cloud computing
    作者: Huang, Tzu-Chi;Chu, Kuo-Chih;Lee, Wei-Tsong;Ho, Yu-Sheng
    貢獻者: 淡江大學電機工程學系
    關鍵詞: 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
    顯示於類別:[電機工程學系暨研究所] 期刊論文


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