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Database systems

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Database systems

CS-422

Lecturer(s) :

Ailamaki Anastasia

Language:

English

Summary

This course is intended for students who want to understand modern large-scale data analysis systems and database systems. It covers a wide range of topics and technologies, and will prepare students to be able to build such systems as well as read and understand recent research publications.

Content

Database systems
Online analytics; data stream processing
Column stores
Decision support systems and data warehouses
Large-scale data analytics infrastructure and systems
Transaction processing. OLTP systems and concurrency control algorithms
Distributed data management systems
Query optimization; database tuning
Logging and recovery
Modern storage hierarchies

Learning Prerequisites

Required courses

CS-322: Introduction to database systems
CS-105: Introduction to object-oriented programming

Recommended courses

CS-323: Introduction to operating systems
CS-452: Foundations of software

Learning Outcomes

By the end of the course, the student must be able to:

Design big data analytics systems using state-of-the-art infrastructures for horizontal scaling, e.g., Spark
Implement algorithms and data structures for streaming data analytics
Decide between different storage models based on the offered optimizations enabled by each model and on the expected query workload
Compare concurrency control algorithms, and algorithms for distributed data management
Identify performance culprits, e.g., due to concurrency control

Teaching methods

Lectures, project, homework, exercises

Expected student activities

During the semester, the students are expected to:

attend the lectures in order to ask questions and interact with the professor,
attend the exercise sessions to solve and discuss exercises about the recently taught material,
work on projects, which cover the practical side of the taught material,
take a midterm,
take a final exam,
read scientific papers related to the course material

Assessment methods

70% exams
30% project

Supervision

Office hours	Yes
Others	Office hours on request. Q&A sessions in lectures and exercises.

Resources

Bibliography

J. Hellerstein & M. Stonebraker, Readings in Database Systems, 4th Edition, 2005

R. Ramakrishnan & J. Gehrke: "Database Management Systems", McGraw-Hill, 3rd Edition, 2002.

A. Rajaraman & J. Ullman: "Mining of Massive Datasets", Cambridge Univ. Press, 2011.

Ressources en bibliothèque

In the programs

Computer Science, 2019-2020, Master semester 2
- Semester
  Spring
- Exam form
  During the semester
- Credits
  7
- Subject examined
  Database systems
- Lecture
  3 Hour(s) per week x 14 weeks
- Exercises
  2 Hour(s) per week x 14 weeks
- Project
  2 Hour(s) per week x 14 weeks
Computer Science, 2019-2020, Master semester 4
- Semester
  Spring
- Exam form
  During the semester
- Credits
  7
- Subject examined
  Database systems
- Lecture
  3 Hour(s) per week x 14 weeks
- Exercises
  2 Hour(s) per week x 14 weeks
- Project
  2 Hour(s) per week x 14 weeks
Communication Systems - master program, 2019-2020, Master semester 2
- Semester
  Spring
- Exam form
  During the semester
- Credits
  7
- Subject examined
  Database systems
- Lecture
  3 Hour(s) per week x 14 weeks
- Exercises
  2 Hour(s) per week x 14 weeks
- Project
  2 Hour(s) per week x 14 weeks
Communication Systems - master program, 2019-2020, Master semester 4
- Semester
  Spring
- Exam form
  During the semester
- Credits
  7
- Subject examined
  Database systems
- Lecture
  3 Hour(s) per week x 14 weeks
- Exercises
  2 Hour(s) per week x 14 weeks
- Project
  2 Hour(s) per week x 14 weeks
Computer Science - Cybersecurity, 2019-2020, Master semester 2
- Semester
  Spring
- Exam form
  During the semester
- Credits
  7
- Subject examined
  Database systems
- Lecture
  3 Hour(s) per week x 14 weeks
- Exercises
  2 Hour(s) per week x 14 weeks
- Project
  2 Hour(s) per week x 14 weeks
Computer Science - Cybersecurity, 2019-2020, Master semester 4
- Semester
  Spring
- Exam form
  During the semester
- Credits
  7
- Subject examined
  Database systems
- Lecture
  3 Hour(s) per week x 14 weeks
- Exercises
  2 Hour(s) per week x 14 weeks
- Project
  2 Hour(s) per week x 14 weeks
Digital Humanities, 2019-2020, Master semester 2
- Semester
  Spring
- Exam form
  During the semester
- Credits
  7
- Subject examined
  Database systems
- Lecture
  3 Hour(s) per week x 14 weeks
- Exercises
  2 Hour(s) per week x 14 weeks
- Project
  2 Hour(s) per week x 14 weeks
Digital Humanities, 2019-2020, Master semester 4
- Semester
  Spring
- Exam form
  During the semester
- Credits
  7
- Subject examined
  Database systems
- Lecture
  3 Hour(s) per week x 14 weeks
- Exercises
  2 Hour(s) per week x 14 weeks
- Project
  2 Hour(s) per week x 14 weeks
Computer and Communication Sciences (edoc), 2019-2020
- Semester
  Spring
- Exam form
  During the semester
- Credits
  7
- Subject examined
  Database systems
- Lecture
  3 Hour(s) per week x 14 weeks
- Exercises
  2 Hour(s) per week x 14 weeks
- Project
  2 Hour(s) per week x 14 weeks
Computer science minor, 2019-2020, Spring semester
- Semester
  Spring
- Exam form
  During the semester
- Credits
  7
- Subject examined
  Database systems
- Lecture
  3 Hour(s) per week x 14 weeks
- Exercises
  2 Hour(s) per week x 14 weeks
- Project
  2 Hour(s) per week x 14 weeks

Reference week

	We	Th
8-9
9-10	MXF1
10-11		BC01
11-12		BC01
12-13		BC01
13-14	SG0213
14-15
15-16
16-17
17-18
18-19
19-20
20-21
21-22

Lecture

Exercise, TP

Project, other

legend

Autumn semester
Winter sessions
Spring semester
Summer sessions

Lecture in French
Lecture in English
Lecture in German