Adaptive Combiner for MapReduce on cloud computing
學年 102
學期 2
出版(發表)日期 2014-03-11
作品名稱 Adaptive Combiner for MapReduce on cloud computing
著者 Huang, Tzu-Chi; Chu, Kuo-Chih; Lee, Wei-Tsong; Ho, Yu-Sheng
單位 淡江大學電機工程學系
出版者 New York: Springer New York LLC
著錄名稱、卷期、頁數 Cluster Computing 17(4), pp.1231-1252
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.
關鍵字 MapReduce;Combiner;Cloud computing;ACMR
語言 en
ISSN 1573-7543
期刊性質 國外
收錄於 SCI
國別 NLD
出版型式 ,電子版,紙本

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