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Coursebooks
Database systems
CS-422
Lecturer(s) :
Ailamaki AnastasiaLanguage:
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
- SemesterSpring
- Exam formDuring 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
- Semester
- SemesterSpring
- Exam formDuring 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
- Semester
- SemesterSpring
- Exam formDuring 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
- Semester
- SemesterSpring
- Exam formDuring 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
- Semester
- SemesterSpring
- Exam formDuring 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
- Semester
- SemesterSpring
- Exam formDuring 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
- Semester
- SemesterSpring
- Exam formDuring 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
- Semester
- SemesterSpring
- Exam formDuring 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
- Semester
- SemesterSpring
- Exam formDuring 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
- Semester
- SemesterSpring
- Exam formDuring 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
- Semester
Reference week
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19-20 | |||||
20-21 | |||||
21-22 |
Under construction
Lecture
Exercise, TP
Project, other
legend
- Autumn semester
- Winter sessions
- Spring semester
- Summer sessions
- Lecture in French
- Lecture in English
- Lecture in German