CompSci 516 - Database Systems (original) (raw)
Overview
This is the graduate database course. This course will cover principles and design of database management systems at an advanced level.
Topics will include:
SQL/Relational Algebra/Relational Calculus, Database Normalization, DBMS Architecture/Storage, Indexing/Hashing, Query Algorithms and Optimizations, Transactions and Recovery, Parallel DB/Map Reduce/Distributed query processing, NOSQL/Column store, Datalog, Advanced and Research Topics in Databases (TBD).
Textbooks:
- [RG] (Main) Database Management Systems (third edition); Raghu Ramakrishnan and Johannes Gehrke.
- [GUW] (Additional) Database Systems: The Complete Book (second edition); Hector Garcia-Molina, Jeffrey Ullman, and Jennifer Widom
Prerequisites:
An introductory database course (CompSci 316 or equivalent) or consent of the instructor. Some background in Algorithms, Data Structure, and Discrete Maths will be assumed. Undergraduate students with the necessary background and interests are welcome.
Grading
- Three Homework: 30%
- Project: 10%
- Midterm: 20%
- Final: 30%
- In-class labs: 5%
- In-class quizzes: 5%
Homework
There will be three homework assignments. They have to solved strictly individually by every student (see the honor code below). There will be two "late days" with penalty : first late day will have a 25% penalty for the entire assignment (even if you are late on one problem), and the second late day will have a 50% penalty. You do not get any credit if you are more than 2 days (i.e. 48 hours) late. Note that if you submit 1 min after the deadline, it counts as the first late day (similarly 24 hours 1 min counts as the second late day). After the solution is posted (even if within the 2 late days after the deadline), you do not get any credit. So do not rely on late days and submit your solutions on time!
Project
There will be a semester-long project on topics chosen by the students in groups of 3-4. Students are encouraged to choose a project of their own research interests that is related to data management / processing / visualization / applications / theory. Some ideas of the projects will be posted later.
Exams
Exams are closed book and closed notes, and in class. No electronic devices are allowed.
Honor Code:
Under the Duke Honor Code, the students are expected to submit their own work in this course in the homework and exams (note that the students will work on the project in groups). The students are allowed (and are encouraged) to discuss the course material with other students, but need to solve problems in the homeworks and exams on their own. Any assistance received must be clearly indicated in the solutions -- failure to do so will be considered a violation of the Honor Code. In any event, the students are responsible for understanding and being able to explain on their own all solutions that they submit. The course staff will pursue aggressively all suspected cases of Honor Code violations, and they will be handled through official University channels.
Schedule
(subject to change) "Notes" will be uploaded before the class and are intentionally left incomplete for interactive lectures. Completed "slides" will be uploaded after the lectures.
| | Day | Topic | Slides | Reading | | | | ----------- | --------------------------------------------- | --------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | | | 1 | 8/27 (T) | Introduction and SQL | Lec1-notes Lecture-1 | SQL: [RG] 3, 5 (also see 4.2.4), [GUW] 6 | | | 2 | 8/29 (Th) | In-class lab (SQL) | Lab-instructions | | | | 3 | 9/3 (T) | Data model, more SQL | Lec-3-notes Lecture-3 | [RG] 1.1, 1.3, 1.4, 1.5XML (optional reading): [RG] 27.6, [GUW] 11.1, 11.2 | | | 4 | 9/5 (Th) | SQL, Relational Calculus/Algebra | Lec-4-notes Lecture-4 | [RG] 4, [GUW] 2.4, 5.1, 5.2 | | | 5 | 9/10 (T) | Relational Algebra, Design Theory and Normalization(Guest Lecture by Junyang Gao) | Lec-5-notes Lecture-5 | [RG] 19.1-19.5, 19.6.1, 19.8 (overview only)[GUW] 3 | | | 6 | 9/12 (Th) | In-class lab (RA) | Lab2-instructions | | | | 7 | 9/17 (T) | RC (revisit) and Functional Dependencies | Lec-7-notes Lecture-7 | | | | 8 | 9/19 (Th) | BCNF and Storage | Lec-8-notes Lecture-8 | [RG] 8.1-8.5, 9.4-9.7, 10.1-10.7, 11[GUW] 8.3, 14.1-14.4 | | | 9 | 9/24 (T) | Storage and Index | Lec-9-10-notes Lecture-9 | | | | 10 | 9/26 (Th) | Tree and Hash Index | Lecture-10 | | | | 11 | 10/1 (T) | External Sorting and Index Selection | Lec-11-notes Lecture-11 | [RG] 13[GUW] 15.4.1 | | | 12 | 10/3 (Th) | Contd. | | | | | 10/8 (T) | No class- Fall break | | | | | | 13 | 10/10 (Th) | Map-Reduce and Spark | Lecture-13 | Spark_RDD Google_File_System Google_MapReduce | | | 14 | 10/15 (T) | Query Evaluation and Join Algorithms | Lecture-14 | [RG] 14 Optional reading: (1) "Architecture of a Database System" by Joseph M. Hellerstein, Michael Stonebraker, and James Hamilton [pdf], Chapters 1.1 and 4.1-4.5(2) "Query Evaluation Techniques for Large Databases" by Goetz Graefe [pdf] | | | 15 | 10/17 (Th) | Query optimization | Lecture-15 | [RG] 15 [GUW] 14.2-14.7 Optional reading: (1) "Access Path Selection in a Relational Database Management System" by Selinger et al. [pdf](2) "An Overview of Query Optimization in Relational Systems" by Chaudhuri et al. [pdf] | | | 16 | 10/22 (T) | Contd.HW2-Part1 due | | | | | 10/24 (Th) | Midterm (in class) | | | | | | 17 | 10/29 (T) | Transactions | Lecture-17 | [RG] 16.1-16.3, 16.4.1, 17.1-17.4 | | | 18 | 10/31 (Th) | contd. | | | | | 11/4 (M) | HW2-Part2 due | | | | | | 19 | 11/5 (T) | Transactions: Concurrency controlMidterm project report due | Lecture-19 | [RG] Chapter 17.5.1, 17.5.3, 17.6[GUW] Chapter 18.8, 18.9 | | | 20 | 11/7 (Th) | Transactions: Recovery | Lecture-20 | [GUW] 17.2-17.4 | | | 21 | 11/12 (T) | HW3 as In-class lab (MongoDB-Part1) | part1 instructions | | | | 22 | 11/14 (Th) | HW3 as In-class lab (MongoDB-Part2) | part2 instructions | | | | 23 | 11/19 (T) | Recovery Contd. | | | | | 24 | 11/21 (Th) | Distributed, parallel databases, NOSQL | Lecture-24 | | | | 25 | 11/26 (T) | Recursive query and Data mining | Lecture-25 | | | | 12/11 (Wed) | Final report and slides due | | | | | | 12/14 (Sat) | Final Exam (2:00 PM - 5:00 PM), LSRC B101 | | | | |
Homework
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| Homework | Topic |
|---|---|
| HW1 | SQL and Postgres |
| HW2 | Spark and AWS |
| HW3 | NOSQL |
Midterm Report (3-5 pages) Final Report (4-8 pages)-->