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一种Hadoop YARN的资源调度机制
引用本文:李 程,柴小丽,谢 彬,唐 鹏. 一种Hadoop YARN的资源调度机制[J]. 计算机与现代化, 2017, 0(11): 29. DOI: 10.3969/j.issn.1006-2475.2017.11.006
作者姓名:李 程  柴小丽  谢 彬  唐 鹏
摘    要:

关 键 词:Hadoop YARN  大数据  资源调度  预约回填  
收稿时间:2017-11-21

A Resource Scheduling Mechanism of Hadoop YARN
LI Cheng,CHAI Xiao-li,XIE Bin,TANG Peng. A Resource Scheduling Mechanism of Hadoop YARN[J]. Computer and Modernization, 2017, 0(11): 29. DOI: 10.3969/j.issn.1006-2475.2017.11.006
Authors:LI Cheng  CHAI Xiao-li  XIE Bin  TANG Peng
Abstract:YARN is a resource management system widely used in Hadoop. It supports MapReduce, Spark, Storm and other computing frameworks, and has become the core component of big data ecology. However, in Hadoop YARN’s existing resource scheduler, a resource guarantee mechanism based on resource reservation, will produce resource fragmentations, leading to a waste of resources. In order to improve the resource utilization and throughput of the cluster, this paper proposes a resource allocation mechanism based on reservation and backfill. In this mechanism, based on the priority of the job, it decides whether to make a reservation to the resource and introduce a backfill strategy to backfill the resource without affecting the execution of the reservation job. Experiments show that the resource scheduling mechanism based on reserved backfill can effectively improve the resource utilization and throughput of Hadoop YARN cluster.
Keywords:Hadoop YARN  big data  resource scheduler  reserved backfill  
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