Course: Big data technologies

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Course title Big data technologies
Course code ITE/TPB
Organizational form of instruction Lecture + Lesson
Level of course Bachelor
Year of study not specified
Semester Winter
Number of ECTS credits 5
Language of instruction Czech
Status of course Compulsory, Compulsory-optional
Form of instruction Face-to-face
Work placements Course does not contain work placement
Recommended optional programme components None
Lecturer(s)
  • Matějů Lukáš, Ing. Ph.D.
  • Červa Petr, doc. Ing. Ph.D.
Course content
Lecture topics: 1. Introduction, examples 2. Offline vs online data processing 3. Distributed computing systems, their properties and components 4. Offline data processing and MapReduce 5. Platform Hadoop 6. Platform Hadoop II 7. Apache Spark 8. Apache Spark II 9. Apache Spark SQL 10. Online data processing 11. Apache Spark streaming 12. Apache Flink 13. Apache Kafka 14. Apache Kafka

Learning activities and teaching methods
Monological explanation (lecture, presentation,briefing), Self-study (text study, reading, problematic tasks, practical tasks, experiments, research, written assignments)
Learning outcomes
Prerequisites
unspecified

Assessment methods and criteria
Combined examination

Recommended literature
  • White T. Hadoop: The Definitive Guide. 2018. ISBN 978-1449311520.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester