Scaling Database Systems - NDBI052

• Anglický název: Scaling Database Systems
• Zajišťuje: Katedra softwarového inženýrství (32-KSI)
• Fakulta: Matematicko-fyzikální fakulta
• Platnost: od 2024
• Semestr: zimní
• E-Kredity: 6
• Rozsah, examinace: zimní s.:2/2, Zk [HT]
• Počet míst: neomezen
• Minimální obsazenost: neomezen
• 4EU+: ne
• Virtuální mobilita / počet míst pro virtuální mobilitu: ne
• Stav předmětu: nevyučován
• Jazyk výuky: angličtina
• Způsob výuky: prezenční
• Garant: doc. RNDr. Irena Holubová, Ph.D.
• Třída: Informatika Mgr. - Softwarové systémy
• Kategorizace předmětu: Informatika > Databázové systémy

Anotace

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[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.

Poslední úprava: Zavoral Filip, RNDr., Ph.D. (04.11.2024)

Podmínky zakončení předmětu

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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.

Poslední úprava: Zavoral Filip, RNDr., Ph.D. (04.11.2024)

Literatura

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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.

Poslední úprava: Zavoral Filip, RNDr., Ph.D. (04.11.2024)

Sylabus

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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).

Poslední úprava: Zavoral Filip, RNDr., Ph.D. (04.11.2024)