SubjectsSubjects(version: 964)
Course, academic year 2024/2025
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Scaling Database Systems - NDBI052
Title: Scaling Database Systems
Guaranteed by: Department of Software Engineering (32-KSI)
Faculty: Faculty of Mathematics and Physics
Actual: from 2024
Semester: winter
E-Credits: 6
Hours per week, examination: winter s.:2/2, Ex [HT]
Capacity: unlimited
Min. number of students: unlimited
4EU+: no
Virtual mobility / capacity: no
State of the course: not taught
Language: English
Teaching methods: full-time
Guarantor: doc. RNDr. Irena Holubová, Ph.D.
Class: Informatika Mgr. - Softwarové systémy
Classification: Informatics > Database Systems
Annotation -
[Note: Course at the University of Passau; only for joint-degree students.] The learning outcome of the course is as follows: The students understand the importance of scalability when managing large amounts of data. They understand the strengths and limitations of NoSQL data stores and how database systems architecture enables performance. The students are able to map a specific data management problem to a suitable NoSQL database management system. The students have the competence to design their own optimizations for data management systems and implement them.
Last update: Zavoral Filip, RNDr., Ph.D. (04.11.2024)
Course completion requirements -

Part 1: Individual Programming project “miniHive” in Python

Part 2: 60-minute written examination

The points for the final grade are computed as follows: 30% from part 1, 70% from part 2.

Last update: Zavoral Filip, RNDr., Ph.D. (04.11.2024)
Literature -

Peter Bailis, Joseph M. Hellerstein, Michael Stonebraker, (editors), Readings in Database Systems, 5 th edition.

Anand Rajaraman, Jeffrey Ullman: Mining of Massive Datasets, Cambridge University Press, 2020.

Martin Kleppmann: Designing Data-Intensive Applications, O'Reilly, 2017.

Stefanie Scherzinger, Build your own SQL-on-Hadoop Query Engine: A Report on a Term Project in a Master-level Database Course, SIGMOD Record, June 2019.

Last update: Zavoral Filip, RNDr., Ph.D. (04.11.2024)
Syllabus -

Flipped classroom (videos for self-study, in-class exercises), programming project (Python).

  • Managing large amounts of data in BigTable-based systems such as Hadoop File System (HDFS).
  • Processing large amounts of data in MapReduce-based systems such as Hadoop.
  • Optimized evaluation of SQL queries on large volumes of data (as done in Hive and Spark).

Last update: Zavoral Filip, RNDr., Ph.D. (04.11.2024)
 
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