Cluster Computing for Web-Scale Data Processing

被引：0
|
作者：
Kimball, Aaron [1 ]
Michels-Slettvet, Sierra [1 ]
Bisciglia, Christophe
机构：
[1] Univ Washington, Dept Comp Sci & Engn, Seattle, WA 98195 USA
来源：
SIGCSE'08: PROCEEDINGS OF THE 39TH ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION | 2008年
关键词：
Education; Hadoop; MapReduce; Clusters; Distributed computing;
D O I：
暂无
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
In this paper we present the design of a modem course in cluster computing and large-scale data processing. The defining differences between this and previously published designs are its focus on processing very large data sets and its use of Hadoop, an open source Java-based implementation of MapReduce and the Google File System as the platform for programming exercises. Hadoop proved to be a key element for successfully implementing structured lab activities and independent design projects. Through this course, offered at the University of Washington in 2007, we imparted new skills on our students, improving their ability to design systems capable of solving web-scale problems.
引用
收藏
页码：116 / 120
页数：5
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