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Detailed Course Information


Spring 2014 Semester
Apr 20, 2014
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CS 6240 - Parallel Data Processing in MapReduce
Introduces the MapReduce programming model and the core technologies it relies on in practice, such as a distributed file system and the distributed consensus protocol. Also discusses related approaches and technologies from distributed databases and cloud computing. Emphasizes practical examples and hands-on programming experiences. Examines both plain MapReduce and database-inspired advanced programming models running on top of a MapReduce infrastructure. Prereq. CS 5800 or permission of instructor; restricted to students in the College of Computer and Information Science.
4.000 Credit hours
4.000 Lecture hours

Levels: Graduate
Schedule Types: Lecture

Computer Science Department

Course Attributes:
GSCS Computer & Info Science

Must be enrolled in one of the following Levels:     
Must be enrolled in one of the following Colleges:     
      Coll of Computer & Info Sci

Graduate level CS 5800 Minimum Grade of C-

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