• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>International Conference on Cloud Computing >Distributed Scheduling Extension on Hadoop
【24h】

Distributed Scheduling Extension on Hadoop

机译：hadoop上的分布式调度扩展

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Distributed computing splits a large-scale job into multiple tasks and deals with them on clusters. Cluster resource allocation is the key point to restrict the efficiency of distributed computing platform. Hadoop is the current most popular open-source distributed platform. However, the existing scheduling strategies in Hadoop are kind of simple and cannot meet the needs such as sharing the cluster for multi-user, ensuring a concept of guaranteed capacity for each job, as well as providing good performance for interactive jobs. This paper researches the existing scheduling strategies, analyses the inadequacy and adds three new features in Hadoop which can raise the weight of job temporarily, grab cluster resources by higher-priority jobs and support the computing resources share among multi-user. Experiments show they can help in providing better performance for interactive jobs, as well as more fairly share of computing time among users.
机译：分布式计算将大规模的作业分成多个任务，并在集群上处理它们。群集资源分配是限制分布式计算平台效率的关键点。 Hadoop是目前最受欢迎的开源分布式平台。但是，Hadoop中的现有调度策略有点简单，无法满足共享多用户的群集等需求，确保每项工作的保证能力的概念，并为交互式作业提供良好的性能。本文研究了现有的调度策略，分析了Hadoop中的不足，并在Hadoop中增加了三个新功能，它可以暂时提高作业权重，通过更高优先级作业抓取群集资源并支持多用户之间的计算资源共享。实验表明，他们可以帮助为互动工作提供更好的表现，以及用户在用户之间的计算时间相当相当地份额。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号