CAJ | 학술논문

执行时间是作业调度的重要参考因素之一。通过分析Hadoop MapReduce环境作业的执行特征，提出了以map任务和reduce任务执行时间为输入，估算作业执行时间的方法。该方法在一定假设条件下，借助作业预执行来获取map任务和reduce任务的执行时间。实验结果表明，该方法估算作业执行时间的误差率小于7%。
집행시간시작업조도적중요삼고인소지일。통과분석Hadoop MapReduce배경작업적집행특정，제출료이map임무화reduce임무집행시간위수입，고산작업집행시간적방법。해방법재일정가설조건하，차조작업예집행래획취map임무화reduce임무적집행시간。실험결과표명，해방법고산작업집행시간적오차솔소우7%。
Execution time is very important for job scheduling. In this paper, the execution characters of Hadoop MapReduce jobs are analyzed, and then a new method is proposed to compute the execution times of these jobs. The method takes the execution times of map task and reduce task as input data. It captures these execution times by pre-executing under an assumption. The method has been evaluated in a Linux cluster, the experiment results show that the method computed the execution times of jobs with the error rate no more than 7%.