Fall 2008

CS 505 : Intermediate Topics in Database Systems

 

Instructor and Course Information

Jinze Liu

liuj@cs.uky.edu

http://www.cs.uky.edu/~liuj

(859) 257 – 3101

Meeting Time:   MWF   11:00AM-11:50AM   

Meeting Place255-FPAT

Office Hours:    MW   12:00PM - 1:00PM

Office:  237 James F. Hardymon Building

 

Announcements

10/14/08

Mid-term exam is on 10/20/08 in class for about 50 minutes.

Project demo are scheduled this Friday 10/17/08 at my office 237 Hardymon . Please arrive 5 minutes earlier before your scheduled time. A hard copy of your project report is due before your demo. 

08/26/08

Course website is up!

 

Course entry exam will be Wednesday in class. It is open book exam, which will cover basic database design issue and SQL .  The exam will be distributed at 11am in class and due at 4pm in Diane’s office (FPAT 7th floor). 

 

Date

Topic

Assigned

Due

Note

Week 1

 

 

08/27

Course entry exam on basic database design and SQL

 

Open book

08/29

Introduction to the course.     [ Slides ]

 

Week 2

09/01

No Class

 

Labor day

09/03

Review of Database Design. [ Slides ]

HM1

09/05

Review of Relational Algebra. [ Slides ]

Week 3

09/08

Review of SQL. [ Slides ]

09/10

Review of Normal Forms [ Slides ]

 

09/12

Review of Normal Forms -- continued

 

Week 4

09/15

Project Description

Project 1

09/17

Database Security  [ Slides ]

 

HM1

09/19

Database Security – Continued.

HM2

Week 5

09/22

Database Security – Continued.

 

Proposal

09/24

Storage [ Slides ]

 

09/26

Storage - Continued

 

Week 6

09/29

Indexing [ Slides ]

10/01

Indexing – ISAM, B+Tree

HM3

HM2

10/03

Indexing – ISAM, B+Tree - Continued

 

Week 7

10/06

Indexing - R-Tree  [ Slides ]

 

10/08

Indexing - Hashing  [ Slides ]

 

10/10

Indexing – Hashing - Continued

 

Week 8

10/13

Indexing – Hashing - Continued

 

10/15

Index & Storage [ Slides ]

 

HM3

10/17

Mid-term Review [ Slides ]

 

Project1

HM3 Solutions

Week 9

10/20

Mid-term Exam

 

10/22

Mid-term Exam Review

10/24

Concurrency control – Introduction [ Slides ]

 

10/27

Concurrency control – Introduction

HW4

10/29

Concurrency control -  Locking [ Slides ]

 

10/31

Concurrency control -  Locking

 

Week  11

11/03

 

Out of town

11/05

Out of town

11/07

Concurrency control -  Tree-based Locking [ Slides ]

 

HW4

Week 12

11/10

Logging and Recovery [ Slides ]

HW5

11/12

Logging and Recovery

 

11/14

Query Optimization [ Slides ]

 

Week 13

11/17

Query Optimization

 

11/19

Query Optimization

11/21

Query Processing [ Slides ]

HW5

Week 14

11/24

Query Processing

 

11/26

 

Thanksgiving!

11/28

HW6

Thanksgiving!

Week 15

12/01

Introduction to Information Retrieval [ Slides ]

 

Project Early Submission  (10% Extra Credit)

12/03

Tolerant Query [ Slides ]

 

12/05

Google MapReduce Framework [ Slides ]

 

Week 16

12/08

Guest Lecture: Data Integration Issues in Large Pathological Databases

 

Final Project

Dr. Michael Blechner

Director of Pathological Informatics,  UKY

12/10

Guest Lecture : Biomedical Data Warehouse Architecture

[ Slides ]

 

HW6

Keith Henry, Main Architect,

RDMC, UKY

12/12

Final Exam Review [ Slides ]

 

12/18

Final Exam

 

3pm - 5pm @ CB 242

 

Syllabus

We assume that the student is familiar with the introductory issues in Databases such as SQL and database design. The course will start with a brief review of these topics and an entry SQL exam will be instituted. Individuals who will not be able to get a satisfactory mark on that exam will be encouraged to drop this class. While the exam will be easy, the student should expect not only SQL proper, but also the issue of modeling, so Entity-Relationship questions and even (slightly) more difficult questions pertaining to foreign keys, normal forms, etc.

Following the current University practice, and the fact that the course is open to undergraduate students, the lecture will be divided into two parts. Each of these parts will have a separate grade, and the final score will be the arithmetic mean of both scores. According to the University rules the midterm grade will be recorded in student's record along with the final grade (for undergraduate students only). The two parts of the lecture is tentatively  subdivided further as the following.

1.    Part I

1.    Brief review of E-R model, SQL and database design.

2.    Security in databases.

3.    Storage and indexing.

2.    Part II

1.    Transaction management

2.    XML

3.    Brief Introduction to data mining

 

Prerequisite:


CS405G:  Introduction to database systems. 

 

Credit For the Course


Due to the recent university requirement, there will be a mid-term grade and a final grade for this course. 

The credit for the first part of the course will be determined as follows:

·         Homeworks : 30%

·         Project: 30%

·         Midterm Exam: 30%

The credit for the second part of the course will be determined as follows:

·         Homeworks: 30%

·         Project: 30%

·         Final Exam: 40%

The final grade will be the average of the results of part I and part II.

Grading Scale:


·         91%+: A

·         81%-90%: B

·         71%-80%: C

·         61%-70%: d

·         <70%: F

Academic Conduct Expectations


Students are expected to complete all assignments independently. Honest and ethical behaviors are always

expected. There will be no tolerance for plagiarism or other academic misconduct. The minimum punish-

ment is an E grade that cannot be removed by the repeat option. You may read U.K. Student Rights and

Responsibilities at http://www.uky.edu/StudentAffairs/Code for a detailed description.

 

Required Textbook


 

Database Systems: The Complete Book (DS:CB), by Hector Garcia-Molina, Jeff Ullman, and Jennifer Widom

 

 

 

Resources


 

1.    Christopher D. Manning, Prabhakar Raghavan and Hinrich Schütze, Introduction to Information Retrieval, Cambridge University Press. 2008

 

                         Related courses: http://www.stanford.edu/class/cs276/cs276-2008-syllabus.html

 

 

 

 

Spring 2008

CS 685 : Special Topics in Data Mining