Lecture 1: Course Introduction Welcome to cs 511, Advanced Database Management!



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Lecture 1: Course Introduction


Welcome to CS 511, Advanced Database Management!

  • Instructor: ChengXiang (“Cheng”) Zhai, czhai@cs

    • 2116 Siebel
    • Office hours: Wed 8:30-10:00, Fri 3:30-4:30 (right after class)
    • Won't have office hour today
  • Home page: http://www.cs.uiuc.edu/class/fa06/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”)


More Administrative Information

  • TA

    • Yoonkyong Lee (also the I2CS TA)
    • Office hours: Tue 8-9pm; Thu 1-2pm
  • Take advantage of the newsgroup class.cs511

    • Discuss course content, homework, project ideas, etc
  • Slides

    • Integrated from those of AnHai Doan and Kevin Chang
    • Will try to have them posted before each lecture


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?
  • 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?


Prerequisites

  • Need cs 411-equivalent background

  • Proficiency in programming

  • Contact the instructor if you aren’t sure



Course Format

  • Lecture-based (twice a week; 75 min each)

  • Each class covers one major paper and possibly a couple of reference papers

  • Only the major paper will be covered in the exam

  • You are required to read the major paper and send a brief review to the newsgroup before the class

  • 3 assignments (problem solving + problem creation)

  • Midterm exam (no final exam!)

  • Course project (to be finished in teams)



Grading

  • Participation: 10%

    • reviews, discussion
    • attendance (not required for I2CS)
  • Homeworks: 30%

  • Midterm exam: 25%

  • Project: 35%

    • Presentation (10%)
    • Report (25%)


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 (Oct 11): In class, close-book



Rough Schedule (cont.)

  • Second half covers the current research topics

    • Overview of “post-relational development”
    • Selectively cover some major current research topics
  • Your job:

    • Read the major paper before each class, but no review is required
    • Mainly work on your project
    • Make a project presentation and write a report


Highlight: Policies

  • All due dates/times are UIUC time

  • No late homework, no extensions, no make-ups:

    • please do not ask unless in exceptional, fully documented cases
  • Use right channels for communications

    • quick clarifications  newsgroup or emails
    • involved questions  office hours
    • administrative requests/comments  email
  • Email: subject as “CS511: …”



How to Get the Most out of CS511?

  • Read and think before class

    • read the paper
    • reference DB textbooks for related concepts
  • Use lectures as road map for studying

    • these papers can seem overwhelming
  • Use your peers in learning

    • discuss in/out classes to enhance understanding
  • Explore interesting projects creatively



Overview of Database Research



Knowledge in Creation: Database Turing Awards?

  • 1966 A.J. Perlis 1967 Maurice V. Wilkes 1968 Richard Hamming 1969 Marvin Minsky 1970 J.H. Wilkinson 1971 John McCarthy 1972 E.W. Dijkstra 1973 Charles W. Bachman 1974 Donald E. Knuth 1975 Allen Newell 1975 Herbert A. Simon 1976 Michael O. Rabin

  • 1977 John Backus



Database Turing Awards

  • 1973 Charles W. Bachman

  • 1981 Edgar F. Codd

  • 1998 James Gray

  • Who’s who?

  • What have they contributed?

  • (stay tuned in this class)

  • And we certainly need more!

  • (work hard and we are counting on YOU!)



Evolution of Data Management

  • Jim Gray: Evolution of Data Management. IEEE Computer 29(10): 38-46 (1996) [also available as this EE]



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

    • many applications still run today!
  • Relational DB: 1980-1995

  • Post-relational and the Internet: 1995-



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) [EE]

  • When data processing was mostly ad-hoc programs– Need generalization, e.g.,

    • sorting
    • file maintenance
    • report generation


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



What Are We “Still” Working On?

  • Although relational database systems are almost commodity software now, researchers are even more fascinated by general data management issues.

  • New challenges naturally arise–

    • databases vs. information retrieval
    • structured vs. unstructured data
    • querying vs. analysis vs. searching
    • closed “base” vs. the open Web


Road map: 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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