MapReduce Scheduler Using Classifiers for Heterogeneous Workloads

被引：0
|
作者：
Visalakshi, P. [1 ]
Karthik, T. U. [2 ]
机构：
[1] PSG Coll Technol, Dept Comp Sci, Coimbatore, Tamil Nadu, India
[2] PSG Coll Technol, ME CSE, Coimbatore, Tamil Nadu, India
来源：
INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY | 2011年 / 11卷 / 04期
关键词：
Hadoop; MapReduce; Scheduler; Heterogeneous;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Hadoop is a large-scale distributed processing infrastructure, designed to efficiently distribute large amounts of work across a set of machines. Scheduling of jobs or work is very important in order to achieve efficiency. The proposed work incorporates the design of a new scheduler that will not overload any TaskTracker at any time and thus preventing the unnecessary re-launch of tasks. The scheduler also classifies the job into CPU bound and IO bound. So, a balance is maintained between either of them.
引用
收藏
页码：68 / 73
页数：6
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