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Subject: Computer Science (provided by Thomson Reuters)
Title:
FlowS:一种MapReduce数据流公平调度方法
Alternative Title: flows:a fair scheduling method for mapreduce dataflow
Author: 李奇原 ; 刘杰 ; 叶丹 ; 许舒人
Keyword: MapReduce数据流 ; 资源管理 ; 公平调度方法
Source: 计算机科学
Issued Date: 2012
Volume: 39, Issue:9, Pages:157-161,174
Indexed Type: CNKI ; WANFANG ; CSCD
Department: 中国科学院软件研究所软件工程技术中心;中国科学院研究生院;
Sponsorship: 国家自然科学基金项目(61170074)|国家科技重大核高基项目(2010ZX01042-001-001-05)|国家科技支撑计划(2011BAH15B05,2012BAH05F02)资助
Abstract: MapReduce Job的调度机制一直是学术研究的热点。在分析MapReduce数据流调度模型的基础上,提出一种面向MapReduce数据流的公平调度方法FlowS。该方法采用数据流池来分配资源以保证MapReduce数据流的隔离性,并且采用数据流池动态构建算法来确保资源的公平分配。实验表明,该调度方法可以有效提高Hadoop集群对MapReduce数据流的处理效率。
English Abstract: MapReduce Job scheduling has been paid great attention in academic research.Based on the analysis of MapReduce dataflow scheduling model,this paper presented a fair scheduling method for MapReduce dataflow-FlowS.This method can not only provide the isolation of MapReduce dataflow through dataflow pools,but also assure the fairness of resource allocation through dynamic construction algorithm.The results of experiences show that the proposed method can improve the processing efficiency of Hadoop Clusters.
Language: 中文
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Content Type: 期刊论文
URI: http://ir.iscas.ac.cn/handle/311060/14960
Appears in Collections:软件所图书馆_期刊论文

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Recommended Citation:
李奇原,刘杰,叶丹,等. FlowS:一种MapReduce数据流公平调度方法[J]. 计算机科学,2012-01-01,39(9):157-161,174.
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