[WS21/22] Scalable Data Management
Lecturer: Prof. Dr.-Ing. habil. Dirk Habich
Description
"Data is the new Oil" - with this sentence, the relevance of structured data and thus, implicitly of course the relevance of scalable database systems as a fundamental technique of analytical and transactional processing of usually large data sets becomes visible. In the context of this course, we will discuss concepts and methods that enable distributed data processing with respect to two essential properties: on the one hand, the aspect of "performance" will be addressed and thus, questions of scalability in the case of scale-out architectures will be discussed using systems such as Apache Spark. On the other hand, the aspect of "consistency" will be discussed, where different methods for synchronizing concurrent read and write activities on the same dataset will be presented.
In general, the goal of this course is to give an insight into scalable techniques and methods of database technology. The course requires a basic knowledge of databases. Attendance of another advanced courses is not necessary, but helpful in some topics. The course exercises consist of tasks that are integrated into the lecture and practical exercises in dealing with "real" systems.
Information
- The course is only open to students of the master's program "Distributed Systems Engineering".
- Please register in OPAL, because all materials and all communication are restricted for registered course members.
- Registration opens on September, 22.
Course Start
- The course starts on October 11th. More information on the Overview page.
Exercise Schedule
Date | Topic |
19.10 | free |
26.10 | Docker |
2.11 | SQL |
9.11 | Redis I |
16.11 | Redis II |
23.11 | Mapreduce |
30.11 | MongoDB |
7.12 | MongoDB |
14.12 | free |
21.12 | free |
28.12 | free |
4.1 | free |
11.1 | Spark |
18.1 | Spark |