摘要
为提高Hadoop作业调度的效率,增加云平台的吞吐率,提出了一种基于Hadoop云计算平台的作业调度算法。该算法在加权轮转调度算法的基础上,针对MapReduce的运行特点,增加了改进map任务本地性调度的因素,使得作业调度仍然保持了相对的公平性,并通过提高轮转周期内的map任务数据本地性,减少了任务的执行时间。实验结果证明,该调度算法与加权轮转调度算法相比,较好地提高了任务本地执行的比例,缩短了云计算系统内作业的总执行时间。
To increase job scheduling eflficiency and system throughput in Hadoop platforn% a job scheduling algorithm is proposed. The algorithm is based on weighted round robin （WRR） algorithm, and adds factors to improve the data locality of map tasks according to the characteristic of MapReduce. The methods reduce task execution time by improving the data locality of map tasks while maintaining fairness to some extent in every cycle. The experimental results show that compared with WRR algorithm , the proposed algorithm increases the scheduling ratio of local tasks , thus reduces the execution time of total jobs in the cloud computing system.
出处
《电脑与信息技术》
2013年第4期18-21,共4页
Computer and Information Technology
关键词
云计算
作业调度
本地性
加权轮转
网络延时
cloud computing
job scheduling
locality
round-robin
network delay
