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ERIC Number: EJ1003711
Record Type: Journal
Publication Date: 2013-Jan
Pages: 18
Abstractor: As Provided
Reference Count: 18
ISBN: N/A
ISSN: ISSN-1946-6226
Using Clouds for MapReduce Measurement Assignments
Rabkin, Ariel; Reiss, Charles; Katz, Randy; Patterson, David
ACM Transactions on Computing Education, v13 n1 Article 2 Jan 2013
We describe our experiences teaching MapReduce in a large undergraduate lecture course using public cloud services and the standard Hadoop API. Using the standard API, students directly experienced the quality of industrial big-data tools. Using the cloud, every student could carry out scalability benchmarking assignments on realistic hardware, which would have been impossible otherwise. Over two semesters, over 500 students took our course. We believe this is the first large-scale demonstration that it is feasible to use pay-as-you-go billing in the cloud for a large undergraduate course. Modest instructor effort was sufficient to prevent students from overspending. Average per-pupil expenses in the Cloud were under $45. Students were excited by the assignment: 90% said they thought it should be retained in future course offerings. (Contains 1 table, 4 figures and 3 footnotes.)
Association for Computing Machinery. 2 Penn Plaza Suite 701, New York, NY 10121. Tel: 800-342-6626; Tel: 212-626-0500; Fax: 212-944-1318; e-mail: acmhelp@acm.org; Web site: http://toce.acm.org/
Publication Type: Journal Articles; Reports - Descriptive
Education Level: Higher Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: California