No lecture on Jan 30, 2017.
The course provides an in-depth understanding of the techniques, algorithms, and data structures that are used in database systems. The focus of the course is on the relational data model and the following topics will be covered:
Course schedule and exam dates are available in PlusOnline. You may register or cancel the registration up to 48 hours before the exam. If you do not show up for a registered exam, you will be blocked for this exam according to the university regulations.
The lecture is mainly based on Chapter 14 (Transactions), Chapter 15 (Concurrency Control), and Chapter 16 (Recovery Systems) of the folloing book:
Silberschatz, Korth, Sudarshan.
Database System Concepts.
McGraw-Hill, 2011 (6th edition)
Please prepare for the lecture by reading the relevant sections in the textbook. The course is designed to be attended by students that have read the relevant contents in the textbook. During the lecture we will focus on examples, deepening discussions, and student questions.
|2016-10-24||Ch 15.1.4–15.1.5, Ch 15.2|
|2016-11-14||Ch 15.4 (including View Serializability)|
The exam will we written. In the case of very few registrations for an exam date, the exam will be held as an oral exam. The students will be notified before the exam.
The exam dates will be announced on PlusOnline. Presumably there will be an exam (1) at the end of the semester, (2) before the summer break, and (3) in autumn.
How to prepare for the exam?
- study the relevant chapters in the textbook (Database System Concepts)
- attend the lecture and study the slides
- actively participate and solve the exercises in the proseminar
At the exam you are allowed to use one A4 sheet with your personal notes (both sides, hand written or printed).
You may register or cancel the registration up to 48 hours before the exam. If you do not show up for a registered exam, you will be blocked for this exam according to the university regulations.
We will practice the concepts discussed in the lecture regarding transactions, concurrency, and recovery. We will exercise numerous techniques to deal with the problems related to these topics by solving theoretical and practical exercises.
Each lab consists of three sections:
- PRE-LAB Self-studying before the lab meeting that includes getting familiar with the concepts related to specific lab (by attending the lecture, reading) and performing simple introductory exercises.
- IN-LAB Solving theoretical and practical exercises together during the lab meeting.
- POST-LAB Self-studying after the lab meeting that includes solving homeworks and studying the lab's contents.
The grading is based on homeworks that must be solved and submitted individually before the deadline.
During our meetings we solve exercises which will help us better understand the details of the concepts introduced during the lecture. The exercises will be solved together, which will hopefully trigger a constructive discussion.
You are encouraged to solve the exercises before the lab meeting.
The purpose of the homeworks is to apply the theoretical knowledge in a practical setting and to deepen the understanding of the implementation details of Database Management Systems.
|17.10.2016||Labs 1||23.10.2016, 23:59|
|24.10.2016||Labs 2||30.10.2016, 23:59|
|31.10.2016||Labs 3||11.11.2016, 21:59|
|14.11.2016||Labs 4 | simulator.py||23.11.2016, 21:59|
|28.11.2016||Labs 5||04.12.2016, 23:59|
|05.12.2016||Labs 6||11.12.2016, 23:59|
|12.12.2016||Labs 7 | simulator_group.py||18.12.2016, 23:59|
|19.12.2016||Labs 8||NO HOMEWORK|
|09.01.2017||Labs 9||15.01.2017, 23:59|
|16.01.2017||Labs 10 | sample-input.txt | generate_tests.py||29.01.2017, 23:59|
|23.01.2017||Labs 11||10.01.2017, 13:59|
Each homework must be submitted through our dbabgabe system.
Access details will be sent by email.
The homeworks can be submitted as TXT or PDF files (including readable and neat handwriting). However, only the PDF submissions can be viewed in the students frontend. Some programming homeworks may require to submit a Python script.
The evaluation is based only on the submitted homeworks with the following grading scale (1 point for each homework; 10 homeworks in total).