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Lecture 1: Course Introduction

Lecture 1: Course Introduction. Aug. 24, 2007 ChengXiang Zhai. Welcome to CS 511, Advanced Database Management!. Instructor: ChengXiang (“Cheng”) Zhai, czhai@cs 2116 Siebel Office hours: Tue 8:30-10:00am, Fri 3:30-4:30pm, CDT Home page: http://www.cs.uiuc.edu/class/fa07/cs511/

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Lecture 1: Course Introduction

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  1. Lecture 1: Course Introduction Aug. 24, 2007 ChengXiang Zhai

  2. Welcome to CS 511, Advanced Database Management! Instructor: ChengXiang (“Cheng”) Zhai, czhai@cs • 2116 Siebel • Office hours: Tue 8:30-10:00am, Fri 3:30-4:30pm, CDT Home page: http://www.cs.uiuc.edu/class/fa07/cs511/ Texts and readings: • All papers will be available online (linked to the schedule page) • Recommended textbook: Hellerstein and Stonebraker: Readings in Database Systems, 4th ed. (often called the “Red Book”)

  3. More Administrative Information • TA (also the I2CS TA) • Arash Termehchy <termehch@uiuc.edu> • Office hours: Tue 7-8pm; Wed 11am-12noon, CDT • Take advantage of the newsgroup class.cs511 • Discuss course content, homework, project ideas, etc • Slides • Will try to have them posted before each lecture

  4. Course Objectives • Introduce the classic milestones in database research • How many Turing Awards were given to DB researchers? For what contributions? • What are the key technologies that have enabled a modern commercial database system to have such widespread applications? How were they invented? • Survey the current trends in database research • Databases seem to be quite mature now, so why is database still an active research field? • What is the limitation of the relational data model? • What are some new challenges to solve?

  5. Prerequisites • Need cs 411-equivalent background • Proficiency in programming • Contact the instructor if you aren’t sure

  6. Course Format • Lecture-based (twice a week; 75 min each) • Each class covers one major paper and possibly a couple of reference papers • 3 assignments, 1 midterm exam, 1 “proof-of-attendance” quiz, project • First half: • You are required to read the major paper and send a brief review to the newsgroup before the class • Only the major paper will be covered in the midterm exam • Second half: • Each lecture usually surveys a topic • You are expected to at least briefly read the major paper before class • You are required to attend all lectures • There will be a “proof-of-attendance” quiz at the end of the semester • Course project (team work is encouraged) • Proposal, presentation, and report

  7. Grading • Participation: 10% • Reviews • Attendance quiz • Assignments: 15% • No late homework, no extensions; please do not ask unless in exceptional, fully documented cases • Midterm exam: 30% • Project: 45% • Proposal (10%) • Presentation (10%) • Report (25%)

  8. Rough Schedule • First half covers the foundation – relational databases • Relational model • Early implementation of relational model • Key database implementation techniques (indexing, query optimization, transaction management) • Your job: • Read the major paper and write a brief review before each class • Attend the class and participate in discussion • Finish 3 assignments • Form a project team and choose a project topic • Midterm: In class, close-book

  9. Rough Schedule (cont.) • Second half covers a selected subset of current research topics • Attempt to be as broad as possible • Topics may be selected to match your project topics • Your job: • Briefly read the major paper (and reference papers if interesting to you) • Mainly work on your project (proposal, presentation, and report)

  10. How to Get the Most out of CS511? • Read and think before class • Read the paper • Reference DB textbooks for related concepts • Attend every lecture and study the slides • Course syllabus + slides  road map • Use your peers in learning • Discuss in/out classes to enhance understanding • Do a project together

  11. Questions? • Use right channels for communications • Quick clarifications  newsgroup or email • Complex technical questions  office hours • Administrative requests/comments  email • If you aren’t sure at any time, always send an email to the instructor and TA

  12. Overview of Database Research

  13. Database Turing Awards? 1966A.J. Perlis1967Maurice V. Wilkes1968Richard Hamming1969Marvin Minsky1970J.H. Wilkinson1971John McCarthy1972E.W. Dijkstra1973Charles W. Bachman1974Donald E. Knuth1975Allen Newell1975Herbert A. Simon1976Michael O. Rabin 1977John Backus 1978Robert W. Floyd1979Kenneth E. Iverson1980C. Antony R. Hoare1981Edgar F. Codd1982Stephen A. Cook1983Ken Thompson 1983Dennis M. Ritchie1984Niklaus Wirth1985Richard M. Karp1986John Hopcroft1986Robert Tarjan1987John Cocke 1988Ivan Sutherland1989William (Velvel) Kahan1990Fernando J. Corbato'1991Robin Milner1992Butler W. Lampson1993Juris Hartmanis1993Richard E. Stearns1994Edward Feigenbaum1994Raj Reddy1995Manuel Blum1996Amir Pnueli1997Douglas Engelbart1998James Gray1999Frederick P. Brooks, Jr. 2000Andrew Chi-Chih Yao

  14. Database Turing Awards • 1973Charles W. Bachman • 1981Edgar F. Codd • 1998James Gray Who’s who? What are their contributions? (stay tuned in this class) Who will be the next? (You?)

  15. Evolution of Data Management Jim Gray: Evolution of Data Management. IEEE Computer 29(10): 38-46 (1996)

  16. Data Management Evolution • Manual processing: -- 1900 • Mechanical punched-cards: 1900-1955 • Stored-program computer: sequential record processing: 1955-1970 • Online navigational network DBs: 1965-1980 • Relational DB: 1980-1995 • Post-relational and the Internet: 1995-

  17. Prehistory Thoughts:Emergence of the Notion of DBMS • (Ref) William C. McGee: Generalization: Key to Successful Electronic Data Processing. J. ACM 6(1): 1-23 (1959) • When data processing was mostly ad-hoc programs– Need generalization, e.g., • sorting • file maintenance • report generation

  18. How Did We Get Here? The dominating relational database system, which we take for granted now, was deemed impossible to implement and difficult to use in its early days. But-- Quoting Jim Gray: These innovations give one of the best examples of research prototypes turning into products. The relational model, parallel database systems, active databases, and object-relational databases all came from the academic and industrial research labs. The development of database technology has been a textbook case of successful collaboration between academe and industry. -- Evolution of Data Management

  19. What Are We “Still” Working On? • Although relational database systems are commercial products now, researchers are even more fascinated by general data management issues. • New challenges naturally arise– • New data types (unstructured vs. structured) • New data sources (e.g., Web) • New users (e.g., ordinary users) • New functions (e.g., analysis, data mining) • Even larger scale (e.g., stream processing) • …

  20. What You Should Know • The goal of the course is to • expose you to the key milestones in DB research • allow you to learn how to do high quality DB research from these classic papers • expose you to some recent trends • give you experience with working on a DB research project • The course is more focused on basic/important concepts and ideas, rather than teach you • How to do SQL programming • How to implement a large-scale DB system

  21. What’s Next? • M: E. F. Codd: A Relational Model of Data for Large Shared Data Banks. CACM 13(6): 377-387 (1970) [RDS: 5-15] • Witness how the relational model was first created! • Why relational model? • How have things evolved over the years?

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