CPS 216: Data-intensive Computing Systems, Fall 2011
Database systems are going through very interesting and chaotic times. Popular relational database systems like IBM DB2, Microsoft SQLServer, Oracle, and Sybase are struggling to handle the massive scale of data introduced by the Web. Today, companies have to deal with extremely large datasets. Facebook absorbs 15 TeraBytes of data each day into their 2.5 PetaByte Hadoop-powered data warehouse. eBay maintains a 6.5 PetaByte (i.e., 6.5 x 1,000,000,000,000,000 Bytes!) data warehouse.
A new breed of database systems are emerging to handle data at massive scale. These systems take some of the successful features from conventional relational databases---like run-time query optimization, automated crash recovery, and self-tuning---and make them work at the scale of 100s-1000s of processors and disks. As we move into the world of "big data", many traditional assumptions break, new query and programming interfaces are required, and new computing models will emerge. Did you know that each Google search query can touch up to 2,000 servers that must all execute that query and respond in less than a third of a second?
This course covers a spectrum of topics from core techniques in relational data management to highly-scalable data processing using parallel database systems and MapReduce. The course material will be drawn from textbooks as well as recent research literature. The following topics will be covered this year. The figures in brackets indicate the amount of time devoted to the topic relative to the total duration of the course.
Prerequisites: An introductory database course will be helpful, but it is not required. If you have not taken an introductory database course before, please talk to the instructor first. A lot of the material that we cover cannot be found in textbooks. Be prepared to do a fair amount of reading.
2:50pm-4:05 PM on Mondays and Wednesdays; D243 LSRC
(Highly recommended) Hadoop: The Definitive Guide, by Tom White. O'Reilly Media. October 2010. (Second edition of the book at Amazon.com)
Cassandra: The Definitive Guide, by Eben Hewitt. O'Reilly Media. November 2010. (First edition of the book at Amazon.com)
Database Systems: The Complete Book, by Hector Garcia-Molina, Jeffrey D. Ullman, and Jennifer Widom. Prentice Hall. 2002. (The second edition is available now.)
Readings will be posted on the readings page.
Instructor: Shivnath Babu
TA: Rozemary Scarlat
There is a semester-long course project (done in groups of two or three). Details will be presented in class.
Both midterm and final exams are open-book and open-notes. Laptops and other electronic devices are not allowed. Late homeworks will not be accepted, unless there are documented excuses from a physician or dean.
Under the Duke Honor Code, you are expected to submit your own work in this course, including homeworks, projects, and exams. On many occasions when working on homeworks and projects, it is useful to ask others (the instructor or other students) for hints or debugging help, or to talk generally about the written problems or programming strategies. Such activity is both acceptable and encouraged, but you must indicate in your submission any assistance you received. Any assistance received that is not given proper citation will be considered a violation of the Honor Code. In any event, you are responsible for understanding and being able to explain on your own all written and programming solutions that you submit. The course staff will pursue aggressively all suspected cases of Honor Code violations, and they will be handled through official University channels.