文章基本信息

标题：Earlier stage for straggler detection and handling using combined CPU test and LATE methodology
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作者：Anwar H. Katrawi ; Rosni Abdullah ; Mohammed Anbar 等
期刊名称：International Journal of Electrical and Computer Engineering
电子版ISSN：2088-8708
出版年度：2020
卷号：10
期号：5
页码：4910-4917
DOI：10.11591/ijece.v10i5.pp4910-4917
出版社：Institute of Advanced Engineering and Science (IAES)
摘要：Using MapReduce in Hadoop helps in lowering the execution time and power consumption for large scale data. However, there can be a delay in job processing in circumstances where tasks are assigned to bad or congested machines called "straggler tasks"; which increases the time, power consumptions and therefore increasing the costs and leading to a poor performance of computing systems. This research proposes a hybrid MapReduce framework referred to as the combinatory late-machine (CLM) framework. Implementation of this framework will facilitate early and timely detection and identification of stragglers thereby facilitating prompt appropriate and effective actions.
关键词：Big data;Combinatory late-machine;Hadoop;Mapreduce;Straggler