Course: Computational Techniques for Large-Scale Data Analysis (CSE 491/891)
Project Information
- Discipline
- Computer Science (401)
- Orientation
- Education
The new millennium has ushered in the era of big data and data-intensive computing. As storage becomes cheaper and computers become more powerful, the need for advanced computing solutions to address large-scale data analysis problems has become increasingly important. This course is intended for senior undergraduate and graduate students who are interested in gaining hands-on experience applying computational techniques to solve large-scale data analysis problems.
Intellectual MeritThis course is intended for senior undergraduate and graduate students who are interested in gaining hands-on experience applying Hadoop to analyze large-scale data.
Broader ImpactsStudents will have practical experience writing, debugging, compiling, and executing programs that can run on a Hadoop cluster.
Project Contact
- Project Lead
- Pang-Ning Tan (ptan)
- Project Manager
- Pang-Ning Tan (ptan)
- Project Members
- Dirk Colbry, Jianpeng Xu, Philip Plachta, Clay Reimann, Ruijuan He, Lei Huang, Yi Zhang, Stephen Paslaski, Di Dan, Maxime Goovaerts, Liyan Wang, Joshua Willard, Christian Fincher, Yevgeny Khessin, Ryan Westra, Mark Schwerzler, Matthew Wenner, Yue Zhuang
Resource Requirements
- Hardware System
-
- Not sure
To complete homework assignments and project for Hadoop class.
Scale of UseThere are currently 44 students enrolled in the class, each will have to run their own Hadoop instance. There will be 2 homework assignments and 1 class project that requires Hadoop.
Project Timeline
- Submitted
- 02/05/2013 - 15:41