Utility-Driven Share Scheduling Algorithm in Hadoop

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原文链接

NETL

外文摘要：Job scheduling in hadoop is a hot topic， however， current research mainly focuses on the time optimization in scheduling。 With the trend of providing hadoop as a service to the public or specified groups， more factors should be considered， such as time and cost。 To solve this problem， we present a utility-driven share scheduling algorithm。 Considering time and cost， algorithm offers a global optimization scheduling scheme according to the workload of the job。 Furthermore， we present a model that can estimate job execute time by cost。 Finally， we implement the algorithm and experiment it in a hadoop cluster。

外文关键词：

schedulinghadooputilityQoS

作者：

Cong Wan、Cuirong Wang、Ying Yuan、Haiming Wang、Xin Song

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作者单位：

College of Information Science and Engineering, Northeastern University, Shenyang 110044, China

会议名称：

International symposium on neural networks

会议地点：

Dalian(CN)

会议母体文献：

Advances in neural networks - ISNN 2013

页码：

560-568

出版时间：

2013