WebMapReduce: an accessible and adaptable tool for teaching map-reduce computing
WebMapReduce: an accessible and adaptable tool for teaching map-reduce computing
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WebMapReduce：一种可访问且适应性强的地图缩减计算教学工具
DOI：
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
E. Shoop
中科院分区：
文献类型：
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作者：
Patrick Garrity;Timothy Yates;Richard A. Brown;E. Shoop
WebMapReduce(WMR)是一种战略性简化的用户界面，用于在集群上实现分布式计算的Map-Reduce模型的Hadoop实施，旨在使CS入门课程中的新手程序员可以使用他们在课程中学习的编程语言执行真正的数据密集型可扩展计算。开放源码的WMR软件目前支持Java、C++、Python和方案计算，并且可以很容易地扩展以支持其他编程语言，并配置为适应特定机构的实践，以教授入门编程。指出了WMR在所有本科层次课程中的潜在应用，并描述了WMR软件的实现。
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. The open-source WMR software 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. Potential applications in courses at all undergraduate levels are indicated, and implementation of the WMR software is described.