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Lecturer(s)
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Prokopová Zdenka, doc. Ing. CSc.
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Šilhavý Petr, doc. Ing. Ph.D.
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Komenda Tomáš, Ing.
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Beltran Prieto Luis Antonio, MSc.
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Course content
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- Introduction to "advanced" databases - from SQL to NoSQL - Principles of NoSQL databases - scalability, sharding, replication etc. - Distributed data processing - MapReduce - Key-value NoSQL database - Document NoSQL databases - Column NoSQL databases - Graph NoSQL databases - Multi-model databases - Other Big Data processing options - Query languages in NoSQL - MongoDB - installation and configuration - MongoDB - basic operations, creation and use of indexes - MongoDB - support for database aggregation and modeling - MongoDB - management and use of roles and users, regular expressions
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Learning activities and teaching methods
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Monologic (Exposition, lecture, briefing), Dialogic (Discussion, conversation, brainstorming), Demonstration, Exercises on PC, Practice exercises
- Participation in classes
- 42 hours per semester
- Term paper
- 30 hours per semester
- Home preparation for classes
- 14 hours per semester
- Preparation for course credit
- 22 hours per semester
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| prerequisite |
|---|
| Knowledge |
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| Knowledge from relational database systems - relational model, normal forms, SQL language, data security. |
| Knowledge from relational database systems - relational model, normal forms, SQL language, data security. |
| learning outcomes |
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| define the concept of Big Data |
| define the concept of Big Data |
| characterize the methods of distributed data processing |
| characterize the methods of distributed data processing |
| explain the principle of the CAP theorem |
| explain the principle of the CAP theorem |
| list the different types of NoSQL databases |
| list the different types of NoSQL databases |
| describe other BigData processing options |
| describe other BigData processing options |
| Skills |
|---|
| design a document database model |
| design a document database model |
| install and configure MongoDB |
| install and configure MongoDB |
| create a database, a collection, a document and save the document to the collection |
| create a database, a collection, a document and save the document to the collection |
| find the required data by querying |
| find the required data by querying |
| apply the use of indexes, MapReduce, Replication |
| apply the use of indexes, MapReduce, Replication |
| teaching methods |
|---|
| Knowledge |
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| Dialogic (Discussion, conversation, brainstorming) |
| Dialogic (Discussion, conversation, brainstorming) |
| Monologic (Exposition, lecture, briefing) |
| Demonstration |
| Demonstration |
| Practice exercises |
| Practice exercises |
| Exercises on PC |
| Exercises on PC |
| Monologic (Exposition, lecture, briefing) |
| assessment methods |
|---|
| Systematic observation of the student |
| Analysis of the student's performance |
| Systematic observation of the student |
| Written examination |
| Written examination |
| Grade (Using a grade system) |
| Oral examination |
| Oral examination |
| Analysis of the student's performance |
| Grade (Using a grade system) |
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Recommended literature
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BANKER, K., et al. MongoDB in action.. New York, 2016.
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EDWARD, S.G. Practical MongoDb : architecting, developing, and administering MongoDB. Expert's voice in open source.. New York, 2015.
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ERL, Thomas; KHATTAK, Wajid; BUHLER, Paul. Big Data Fundamentals. New York, 2016.
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HOLUBOVÁ, Irena, et al. Big Data a NoSQL databáze.. Praha, 2015.
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PLUGGE, E., et al. The Definitive Guide to MongoDB: A complete guide to dealing with Big Data using MongoDB.. New York, 2015.
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SADALAGE, Pramod J.; FOWLER, Martin. NoSQL distilled: a brief guide to the emerging world of polyglot persistence.. Pearson Education, 2013.
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