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541: Database Systems

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This course provides an introduction to database systems, covering topics such as data models, relational algebra, SQL, storage, indexing, query optimization, transactions, XML, data warehousing, data mining, and more.

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541: Database Systems

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  1. 541: Database Systems S. Muthu Muthukrishnan

  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 6595yihwu@paul.rutgers.edu Hill 415. Office hrs: Tuesday 4 – 5 PM.

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

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

  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/ • 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. 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. More Background • Curiosity, THINK, DO. • Enjoy, participate.

  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.

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