| Course Unit Code | 460-4137/01 |
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| Number of ECTS Credits Allocated | 4 ECTS credits |
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| Type of Course Unit * | Compulsory |
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| Level of Course Unit * | Second Cycle |
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| Year of Study * | First Year |
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| Semester when the Course Unit is delivered | Summer Semester |
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| Mode of Delivery | Face-to-face |
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| Language of Instruction | Czech |
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| Prerequisites and Co-Requisites | Course succeeds to compulsory courses of previous semester |
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| Name of Lecturer(s) | Personal ID | Name |
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| KRA28 | prof. Ing. Michal Krátký, Ph.D. |
| Summary |
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The main topics of this course includes the following:
- Query processing in database management systems (DBS).
- Physical implementation of DBS.
- Performace of the data layer.
- Extensions of DBMS for storage and handling: text documents, graf data, spatial data, images, videos, and streams.
- NoSQL and In-memory DBMS.
- Algorithms for query processing: algorithms of the join operation.
- Data structures for single and multidimensional pont and range queries. |
| Learning Outcomes of the Course Unit |
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| The goal of this course is to provide advances topics of database systems to students. A student knows current methodologies, methods, and tools for the database design and information system development, especially the physical database design and testing of the data layer, and student is able to apply these knowledges during a real design and implementation of information systems. Moreover, student can describe some extended database technologies such as spatial DBMS, full-text options of DBMS, XML, distributed, and NoSQL DBMS. |
| Course Contents |
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1. Query evaluation in database systems (DBMS): query evaluation plan, IO cost, CPU cost, physical and logical plans: physical design patterns, query tuning, performance measurement.
2. Random and sequential operations in memory/disk, classification of disks, RAID.
3. Physical implementation of DBMS: heap table/clustered table, indices: B-tree, hash table, bitmap index.
4. Performance of the data layer in an information systems.
5. Data paging in the data layer, row/column store, compression in DBMS. Special data types in DBMS.
6. Extension of DBMS for storage and querying of text documents and graphs.
7. Extension of DBMS for storage and querying of spatial data.
8. Extension of DBMS for storage and querying of images, videos, and streams.
9. Criticism of ACID, distributed DBMS, NoSQL: CAP theorem, eventually consistency.
10. Main representatives of NoSQL DBMS: key-value, document, and graph DBMS.
11. In-memory DBMS: features, representatives.
12. Join algorithms: nested loop join, hash join, merge join.
13. Data structures for single-dimensional point and range queries.
14. Data structures for multi-dimensional point and range queries.
Practices:
Practices follow topics of lectures, students will work on tasks defined for individual topics. |
| Recommended or Required Reading |
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| Required Reading: |
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| H. Garcia-Molina, J. D. Ullman, J. Widom: Database Systems: The Complete Book (2nd Edition). Prentice Hall; 2 edition (June 15, 2008). |
1. M. Krátký, R. Bača: Databázové systémy, Učební text pro databázové předměty na Katedře informatiky, VŠB-TU Ostrava. Dostupné na dbedu.cs.vsb.cz, 2021.
2. H. Garcia-Molina, J. D. Ullman, J. Widom: Database Systems: The Complete Book (2nd Edition). Prentice Hall; 2 edition (June 15, 2008).
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| Recommended Reading: |
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1. S. Lightstone, T. Teorey, T. Nadeau. Physical Database Design: The Database Professional's Guide to Exploiting Indexes, Views, Storage, and More. ISBN 0123693896. Morgan Kaufmann; 4th edition (April 4, 2007).
2. A. Meier, M. Kaufmann. SQL & NoSQL Databases: Models, Languages, Consistency Options and Architectures for Big Data Management. ISBN 978-3658245481. Springer Vieweg; 1st ed. 2019. |
1. S. Lightstone, T. Teorey, T. Nadeau. Physical Database Design: The Database Professional's Guide to Exploiting Indexes, Views, Storage, and More. ISBN 0123693896. Morgan Kaufmann; 4th edition (April 4, 2007).
2. A. Meier, M. Kaufmann. SQL & NoSQL Databases: Models, Languages, Consistency Options and Architectures for Big Data Management. ISBN 978-3658245481. Springer Vieweg; 1st ed. 2019. |
| Planned learning activities and teaching methods |
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| Lectures, Tutorials, Project work |
| Assesment methods and criteria |
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| Task Title | Task Type | Maximum Number of Points
(Act. for Subtasks) | Minimum Number of Points for Task Passing |
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| Credit and Examination | Credit and Examination | 100 (100) | 51 |
| Credit | Credit | 45 | 23 |
| Examination | Examination | 55 | 28 |