1


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.
2

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

 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 .
Grading:
03/18: Spring Break
04/29: Project demo
05/06: Final Exam
.
Homework 20%
Project 40%
Finals 40%
4


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/
 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.
5


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.
6



7


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.
8