1. 1 541: Database Systems S. Muthu Muthukrishnan

2. 2 Preliminaries  CS541. Thursdays 5 – 8 PM, CORE A. Course webpage: http://www.cs.rutgers.edu/~muthu/cs541- 04.html  Instructor: S. Muthu Muthukrishnan, muthu@cs.rutgers.edu, Core 319. X 2379. Office hrs: Mondays 11 -- 12 PM.  TA: Yihua Wu X 6595 yihwu@paul.rutgers.edu Hill 415. Office hrs: Tuesday 4 – 5 PM.

3. 3 Course Details I  Book: Database Management Systems, 3 rd Edition, Raghu Ramakrishnan and Johannes Gehrke. McGraw Hill, 2002. http://www.cs.wisc.edu/~dbbook/ http://www.cs.wisc.edu/~dbbook/  Slides on the web.  Solutions to some exercises.

4. 4 Course Details II  We meet:  [1] 01/29  [4] 02/05, 02/12, 02/19, 02/26.  [3] 03/04, 03/11, 03/18, 03/25.  [5] 04/01, 04/08, 04/15, 04/22, 04/29.  [1] 05/06. 03/18: Spring Break 04/29: Project demo 05/06: Final Exam. Grading: Homework 20% Project 40% Finals 40%

5. 5 Course Project  Pick a dataset.  Stock market data, US patent data, web data, internet traffic data.  UC Irvine data repository. http://odwin.ucsd.edu/idata/  Set of conf papers: http://www.acm.org/sigs/sigmod/record/xml/http://www.acm.org/sigs/sigmod/record/xml/  Medical, ecological, biological, text, movie database.  Rutgers labs..  How to collect it? How to make it up?  HW 0: Decide by 02/26. Submit a writeup of what data, how you will collect it, how much, what application you will build—what queries are important, what challenges you foresee, schedule+timeline and how you are going to divide work, etc.  Midterm project review 03/25. Experiment with different indices, join methods, different ways of posing queries, schemas, etc.  Project demo and project writeup due: 04/22. Check out http://paul.rutgers.edu/~eiman/cs541_fall03.html for details.

6. 6 Background Needed  Discrete Math: sets (compare), functions (domain/range), proofs(induction/counterexamples)  Boolean Algebra: logical operators (and or not parity), CNF/DNF, Exists, Forall.  Data Structures: pointers, linked lists, trees (binary, height/level), hashing,  Programming: C, Java, Program constructs.  Algorithms: sorting, simple graph algorithms.

7. 7 More Background  Curiosity, THINK, DO.  Enjoy, participate.

8. 8 Syllabus  Basics, Intro.  Data Models. Chapter 2 and 3.  RelationalAlgebra and Calculus.  SQL.  Storage, files and Tree Indexes.  Hash indexing, sorting, evaluation of relational ops.  Scheme refinement  Physical D/B design.  Query optimization.  ? Transactions.  Special Topics:  XML, internet databases  Decision Support and data warehousing  Data mining. Data quality.  Spatial, text databases and data streams.