WebMapReduce: an accessible and adaptable tool for teaching map-reduce computing

Authors:
Patrick Garrity;Timothy Yates;Richard Brown;Elizabeth Shoop
Affiliations:
St. Olaf College, Northfield, MN, USA;St. Olaf College, Northfield, MN, USA;St. Olaf College, Northfield, MN, USA;Macalester College, St. Paul, MN, USA
Venue:
Proceedings of the 42nd ACM technical symposium on Computer science education
Year:
2011

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Abstract

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.