期刊名称：International Journal of Grid and Distributed Computing
印刷版ISSN：2005-4262
出版年度：2016
卷号：9
期号：2
页码：203-214
DOI：10.14257/ijgdc.2016.9.2.18
出版社：SERSC
摘要：MapReduce , as a popular programming model for processing large data sets , has been widely applied. MapReduce 2.0 (MRV2) is a newly adopted one, which has a better performance. Those machines which have a lower performance in a cluster usually play a role who pull down the pace of job execution time. Speculative execution known as an approach for dealing with the above problems works by backing up those tasks running on a low performance machine to a higher one. Although multiple speculative execution strategies have been proposed, there are still a lot of pitfalls existing in the strategies. In this paper, Some pitfalls in proposed strategy have been modified and computer hardware has been taken into consideration (HWC-Speculation). In Hadoop-2.6, we have implemented it, called Hadoop-HWC. Experiment results show that our method can find a slow task correctly, also, the performance of MRV2 is improved.
