Teaching HDFS/MapReduce Systems Concepts to Undergraduates

Author

Linh Bao Ngo ; Duffy, E.B. ; Apon, A.W.

Author_Institution

Sch. of Comput., Clemson Univ., Clemson, SC, USA

fYear

2014

fDate

19-23 May 2014

Firstpage

1114

Lastpage

1121

Abstract

This paper presents the development of a Hadoop MapReduce module that has been taught in a course in distributed computing to upper undergraduate computer science students at Clemson University. The paper describes our teaching experiences and the feedback from the students over several semesters that have helped to shape the course. We provide suggested best practices for lecture materials, the computing platform, and the teaching methods. In addition, the computing platform and teaching methods can be extended to accommodate emerging technologies and modules for related courses.

Keywords

computer science education; data analysis; distributed processing; educational courses; educational institutions; further education; teaching; Clemson University; HDFS MapReduce system concept; Hadoop MapReduce module; distributed computing course; teaching methods; undergraduate computer science students; Educational institutions; Java; Linux; Materials; Programming; Supercomputers; HDFS; MapReduce; distributed systems; parallel computing education;

fLanguage

English

Publisher

ieee

Conference_Titel

Parallel & Distributed Processing Symposium Workshops (IPDPSW), 2014 IEEE International

Conference_Location

Phoenix, AZ

Print_ISBN

978-1-4799-4117-9

Type

conf

DOI

10.1109/IPDPSW.2014.124

Filename

6969506