Description
Storing, indexing, accessing and processing techniques for big data. Map/Reduce algorithm and related technologies. Data analysis and application in big data ecosystem. This course covers the basics of big data processing and analysis; answers the following questions: what the big data is and its differences from the traditional data and traditional processing methods, where it is used, how it is used.
General Information
Lectures
Tue 18:00 – 21:00 (Balgat Campus, A-307)
Textbook
1) Data-Intensive Text Processing with MapReduce
Jimmy Lin and Chris Dyer. Morgan & Claypool Publishers, 2010.
http://lintool.github.io/MapReduceAlgorithms/
2) Mining Massive Data Sets, 2nd Ed.
Jure Leskovec, Anand Rajaraman, Jeff Ullman
http://mmds.org
3) Mastering Apache Spark
Jacek Laskowski
https://www.gitbook.com/book/jaceklaskowski/mastering-apache-spark/details
4) Hadoop: The Definitive Guide, 3rd Edition
Tom White, O'Reilly
http://shop.oreilly.com/product/0636920021773.do
Jimmy Lin and Chris Dyer. Morgan & Claypool Publishers, 2010.
http://lintool.github.io/MapReduceAlgorithms/
2) Mining Massive Data Sets, 2nd Ed.
Jure Leskovec, Anand Rajaraman, Jeff Ullman
http://mmds.org
3) Mastering Apache Spark
Jacek Laskowski
https://www.gitbook.com/book/jaceklaskowski/mastering-apache-spark/details
4) Hadoop: The Definitive Guide, 3rd Edition
Tom White, O'Reilly
http://shop.oreilly.com/product/0636920021773.do
| Name | Office Hours | |
|---|---|---|
Erdoğan Doğdu | When? Where? |
Homework
Homework
Due Date
Apr 5, 2018
Apr 4, 2017
Mar 7, 2017
Lecture Notes
Lecture Notes
Lecture Date
May 2, 2017
Apr 4, 2017
Mar 28, 2017
Mar 21, 2017
Mar 7, 2017
Feb 28, 2017
Feb 21, 2017
Feb 14, 2017
General Resources
General Resources