Course: no SQL systems and Big Data

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Course title no SQL systems and Big Data
Course code KIT/ISQBD
Organizational form of instruction Lecture + Lesson
Level of course Bachelor
Year of study not specified
Semester Summer
Number of ECTS credits 5
Language of instruction Czech
Status of course Compulsory
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Borkovcová Monika, Ing. Ph.D.
Course content
1. Optimization techniques, execution plans and CBO. 2. The design and selection of suitable structures to data access methods. 3. Enteprise manager - advanced database administration. 4. Advanced database application development - JDBC&Hibernate. 5. Advanced PL/SQL - mapping of Java procedures to PL/SQL. 6. Oracle RAC. 7. Introduction to NoSQL databases, the motivation to use NoSQL databases, NoSQL databases categorization, Big Data 8. Key-value databases (Redis, Riak), categorization, caching, sharding 9. Document databases (MongoDB, CouchDB), access from higher programming language 10. Graph databases (Neo4j), recommendation systems, implementation of recommendation algorithms in graph database 11. Big Data and Map-reduce paradigm, history, architecture. Apache Hadoop, installation, configuration and architecture. 12. Apache Hadoop - programming of map-reduce tasks, performance analysis, map-reduce design patterns 13. Apache Hadoop - extensions (Apache Pig, Apache Hive and Apache Mahout).

Learning activities and teaching methods
Monologic (reading, lecture, briefing), Dialogic (discussion, interview, brainstorming), Demonstration, Work-related activities
Learning outcomes
The first aim of the course is to get studets acquainted with advanced work with classical RDBMS and with development of advanced database appliactions (ORM, Hibernate, JPA). The second aim is to acquaint students with NoSQL paradigma and Big Data processing.
Development of database appliactions. Database system optimalization. Basic knowledge of NoSQL and Big Date systems.
Prerequisites
Good knowledge of SQL language. Basic knowledge of Oracla Database system, PL/SQL languge a JDBC interface.

Assessment methods and criteria
Oral examination, Student performance assessment, Creative work analysis, Self project defence

Participation in exercises (min. 70%). Elaboration of all tasks assigned to exercise. Preparation and submission of semestral work. Pass the exam.
Recommended literature
  • HARRISON, Guy. Oracle performance survival guide. Upper Saddle River, NJ, 2010. ISBN 01-370-1195-4.
  • KYTE, Thomas. Expert Oracle. Signature ed. Apress, c2005, xviii,1297 p. ISBN 15-905-9525-4..
  • LAM, Chuck. Hadoop in action. Greenwich: Manning Publications, 2011, xxi, 312 S. ISBN 978-1-935182-19-1..
  • McCREARY, Dan - KELLY, Ann. Making sense of NoSQL: a guide for managers and the rest of us. Shelter Island, 2013. ISBN 978-161-7291-074..
  • ROBINSON, Ian - WEBBER Jim. Graph databases. First edition. Sebastopol, Calif, 2013. ISBN 978-144-9356-262.11.
  • WHITE, Tom. Hadoop: the definitive guide. 3rd ed. Sebastopol: O'Reilly, 2012. ISBN 978-1-449-31152-0..


Study plans that include the course
Faculty Study plan (Version) Branch of study Category Recommended year of study Recommended semester
Faculty of Electrical Engineering and Informatics Information Technology (2015) Informatics courses 3 Summer
Faculty of Electrical Engineering and Informatics Information Technology (2016) Informatics courses 3 Summer