CompSci 516

Database Systems

Fall 2017

News



      Day/Time: Mondays and Wednesdays, 10:05 am - 11:20 am
      PlacePhysics 130

      Instructor: Sudeepa Roy
  • Email: sudeepa AT cs.duke.edu
  • Office Hour: LSRC D325, Mondays 11:30 am - 12:30 pm
      (half-)TA: Yilin Gao
  • Email: yilin.gao AT duke.edu
  • Office Hour: LSRC D301, Wednesdays 3:00 pm - 4:00 pm
      (half-)TA: Keping Wang
  • Email: keping.wang AT duke.edu
  • Office Hour: LSRC D301, Thursdays 3:00 pm - 4:00 pm

    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:
    1. [RG] (Main) Database Management Systems (third edition); Raghu Ramakrishnan and Johannes Gehrke.
    2. [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 as well. Undergraduate students with the necessary background and interests are welcome.

    Grading
    • Three Homework: 30%
    • Project: 15%
    • Two Midterms: 25 + 25 = 50%
    • Class participation: 5%

    Homework
    There will be three homework assignments. They have to solved strictly individually by every student (see the honor code below). There are no late days. We will use Sakai for homework submission and Piazza for discussions.

    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 research project of their own research interests that is related to data management / processing / visualization / applications / theory. Some ideas of the projects will be posted.

    The deliverables of the project will be (1) a project proposal (1-3 pages), (2) a midterm project report (3-5 pages), (3) the final project report (4-8 pages), and (4) a short (~10 minutes) class presentation at the end. The same document will be updated through the semester as the project progresses. A template of the project report will be posted on sakai.

    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.

    What is allowed/not allowed

    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 8/28 (M) Introduction and Data Models Lecture-1 [RG] 1.1, 1.3, 1.4, 1.5
    2 8/30 (W) SQL Lec-2-notes

    Lecture-2
    SQL: [RG] 3, 5 (also see 4.2.4), [GUW] 6

    XML (optional reading): [RG] 27.6, [GUW] 11.1, 11.2
    3 9/4 (M) More SQL Lec-3-notes

    Lecture-3
    4 9/6 (W) Relational Algebra/Calculus Lec-4-notes

    Lecture-4
    [RG] 4, [GUW] 2.4, 5.1, 5.2
    5 9/11 (M) Design Theory and Normalization Lec-5-notes

    Lecture-5
    [RG] 19.1-19.5, 19.6.1, 19.8 (overview only)
    [GUW] 3
    6 9/13 (W) Normalization and Storage Lec-6-notes

    Lecture-6a
    Lecture-6b
    [RG] 9.4-9.7
    [GUW] 13.5-13.8
    7 9/18 (M) Storage and Indexing Lec-7-notes

    Lecture-7
    8 9/20 (W) Index Lec-8-notes

    Lecture-8
    9 9/25 (M) Index Selection and External Sorting Lec-9-notes [RG] 13
    [GUW] 15.4.1
    10 9/27 (W) Query Optimization
    11 10/2 (M) Recursive query evaluation and Datalog
    12 10/4 (W) Map-Reduce and Spark
    10/9 (M) No class- Fall break
    10/11 (W) Midterm-1 (in class)
    13 10/16 (M) Transactions - introduction
    14 10/18 (W) Transactions: Concurrency Control
    15 10/23 (M) Transactions: Recovery (ARIES)
    16 10/25 (W) Parallel Databases
    17 10/30 (M) Distributed Databases
    18 11/1 (W) NOSQL and Column Stores
    19 11/6 (M) Data Warehousing and Decision Support
    20 11/8 (W) Data Mining
    21 11/13 (M) Advanced topic - TBD
    22 11/15 (W) Advanced topic - TBD
    23 11/20 (M) Advanced topic - TBD
    11/22 (W) No class - Thanksgiving Recess
    24 11/27 (M) Project Presentations
    11/29 (W) Midterm-2 (in class)


    Homework

    Homework Topic Posted on Due on
    HW1(see Sakai) SQL and Postgres 08/28 (Mon) 09/21 (Thurs), 11:55 pm
    HW2 Spark and AWS
    HW3 NOSQL

    Project Milestones

    Milestone Due on
    Project Proposal (1-3 pages) 09/25 (Mon), 11:55 pm
    Please send an email with group member and an informal project description by 09/18 (Mon).
    Midterm Report (3-5 pages) 10/25 (Wed), 11:55 pm
    Final Report (4-8 pages) 11/30 (Thurs), 11:55 pm