Database Systems II

It is not possible to register for the course B4M36DS2 if the student is concurrently registered for or has already completed the course BE4M36DS2 (mutually exclusive courses).

It is not possible to register for the course B4M36DS2 if the student is concurrently registered for or has previously completed the course BE4M36DS2 (mutually exclusive courses).

The requirement for course B4M36DS2 can be fulfilled by substitution with the course BE4M36DS2.

Garant předmětu:

Yuliia Prokop

Lecturer:

Yuliia Prokop

Tutor:

Yuliia Prokop

Supervisor:

Department of Computer Science

Synopsis:

The aim is to introduce new trends in database systems to students. We will focus primarily on the current issues of Big Data and the associated problems of distributed storage and processing of data. We will introduce a

so-called basic types of NoSQL databases and also the related issue of cloud computing, data storage and distributed computations over large data files.

Requirements:

Syllabus of lectures:

1. Introduction to Big Data and NoSQL databases

2. MapReduce

3. Basic principles of Big Data Management (CAP theorem, distribution,

scaling, replication)

4. Comparison and classification of NoSQL databases

5. The database type of key - value

6. Column database

7. Document Database

8. Graph database - basic principles

9. Graph databases - advanced aspects of indexing, querying

10. Advanced Principles of Big Data management (transaction performance,

polyglot persistence)

11. NewSQL database

11. Cloud computing

13. Data warehouses and Big Data

14. Other problems associated with Big Data - data analysis, data

generators, benchmarking.

Syllabus of tutorials:

Study Objective:

Study materials:

1.http://nosql-database.org/

2.Pramod J. Sadalage - Martin Fowler: NoSQL Distilled: A Brief Guide to the Emerging World of Polyglot Persistence

3.Eric Redmond - Jim R. Wilson: Seven Databases in Seven Weeks: A Guide to Modern Databases and the NoSQL Movement

4.Sherif Sakr - Eric Pardede: Graph Data Management: Techniques and Applications

5.Shashank Tiwari: Professional NoSQL

6.Jeffrey Dean and Sanjay Ghemawat: MapReduce: Simplified Data Processing on Large Clusters, Google, Inc.

7.Google Code: Introduction to Parallel Programming and MapReduce

8.Hadoop: The Definitive Guide, by Tom White, 2nd edition, Oreilly?s, 2010

Note:

Further information:

https://cw.fel.cvut.cz/wiki/courses/b4m36ds2/

Time-table for winter semester 2023/2024:

	06:00–08:0008:00–10:0010:00–12:0012:00–14:0014:00–16:0016:00–18:0018:00–20:0020:00–22:0022:00–24:00
Mon	roomKN:E-301 Prokop Y. 09:15–10:45 (lecture parallel1) Karlovo nám. Šrámkova posluchárna K9roomKN:E-328 Prokop Y. 12:45–14:15 (lecture parallel1 parallel nr.101) Karlovo nám. Bourací učebnaroomKN:E-328 Prokop Y. 14:30–16:00 (lecture parallel1 parallel nr.102) Karlovo nám. Bourací učebnaroomKN:E-328 Prokop Y. 16:15–17:45 (lecture parallel1 parallel nr.103) Karlovo nám. Bourací učebnaroomKN:E-328 18:00–19:30 (lecture parallel1 parallel nr.104) Karlovo nám. Bourací učebna
Tue
Wed
Thu
Fri

Time-table for summer semester 2023/2024:

Time-table is not available yet

The course is a part of the following study plans:

• Open Informatics - Software Engineering (compulsory course of the specialization)
• Open Informatics - Data Science (compulsory course of the specialization)