WebMapReduce: An Accessible and Adaptable Tool for teaching Map-Reduce Computing

被引：0
|
作者：
Garrity, Patrick [1 ]
Yates, Tim [1 ]
Brown, Richard [1 ]
Shoop, Elizabeth
机构：
[1] St Olaf Coll, Northfield, MN 55057 USA
来源：
SIGCSE 11: PROCEEDINGS OF THE 42ND ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION | 2011年
关键词：
Map-reduce; CS1; introductory course; parallel computing; distributed computing; data-intensive scalable computing; CS curriculum; education;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
WebMapReduce (WMR) is a strategically simplified user interface for the Hadoop implementation of the map-reduce model for distributed computing on clusters, designed so that novice programmers in an introductory CS courses can perform authentic data-intensive scalable computations using the programming language they are learning in their course. WMR currently supports Java, C++, Python, and Scheme computations, and can readily be extended to support additional programming languages, and configured to adapt to the practices at a particular institution for teaching introductory programming. The open-source system is designed to give beginning CS students experience with parallel computing and exposure to concepts of parallelism, at a wide variety of institutions with diverse curricular choices and cluster resources. Potential applications in courses at all undergraduate levels are indicated, and implementation of the WMR software is described.
引用
收藏
页码：183 / 188
页数：6
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