Duration:
1 Semester | Turnus of offer:
each winter semester | Credit points:
4 |
Course of studies, specific field and terms: - Bachelor MES 2020 (optional subject), computer science / electrical engineering, 3rd semester at the earliest
- Bachelor Media Informatics 2020 (compulsory), computer science, 5th semester
- Bachelor Computer Science 2019 (compulsory), foundations of computer science, 3rd semester
- Bachelor Robotics and Autonomous Systems 2020 (optional subject), computer science, 5th or 6th semester
- Bachelor Medical Informatics 2019 (compulsory), computer science, 3rd semester
- Bachelor Computer Science 2016 (compulsory), foundations of computer science, 4th semester
- Bachelor Robotics and Autonomous Systems 2016 (optional subject), computer science, 5th or 6th semester
- Bachelor IT-Security 2016 (compulsory), computer science, 3rd semester
- Bachelor Biophysics 2016 (optional subject), computer science, 6th semester
- Bachelor MES 2011 (optional subject), computer science, 4th or 6th semester
- Bachelor Medical Informatics 2014 (compulsory), computer science, 4th semester
- Bachelor MES 2014 (optional subject), computer science / electrical engineering, 4th or 6th semester
- Bachelor Media Informatics 2014 (compulsory), foundations of computer science, 4th semester
- Bachelor Computer Science 2014 (compulsory), foundations of computer science, 4th semester
- Bachelor Medical Informatics 2011 (compulsory), computer science, 2nd semester
- Master CLS 2010 (optional subject), computer science, 2nd semester
- Bachelor CLS 2010 (optional subject), computer science, 6th semester
- Bachelor Computer Science 2012 (compulsory), foundations of computer science, 4th semester
|
Classes and lectures: - Databases (exercise, 1 SWS)
- Databases (lecture, 2 SWS)
| Workload: - 20 Hours exam preparation
- 55 Hours private studies
- 45 Hours in-classroom work
| |
Contents of teaching: | - Introduction, conceptual view of database systems, conceptual data modeling with the Entity-Relationship (ER) modeling language
- The relational data model * Referential integrity, keys, foreign keys, functional dependencies (FDs) * Canonical mapping of entity types and relationships into the relational data model * Update, insertions, and deletion anomalies * Relational algebra as a query language * Database normalization, closure w.r.t. FD set, canonical cover of FD sets, normal forms, correct and dependency preserving decomposition of relation schemata, multi-value dependencies, inclusion dependencies
- Practical query language: SQL * Selection, projection, join, aggregation, grouping, sorting, difference, relational algebra in SQL * Data management * Integrity constraints
- Storage structures and database architecture * Characteristics of storage media, I/O complexity * DBMS architecture: disk space manager, buffer manager, files and access methods, record allocation strategies (row-wise, column-wise, mixed)
- Query processing * Indexing techniques, ISAM index, B+-tree index, hash index * Sorting: Two-way merge sort, blockwise processing, selection trees, query execution plans, join operator: nested loops join, blockwise nested loops join, index-based joins, sort-merge join, partition-based join with hashing * Addition operators: grouping and duplicate elimination, selection, projection, pipeline principle
- Datalog * Syntax, semantics, treatment of negation (stratification) * Evaluation strategies (naive, semi naive, magic set transformation)
- Query optimization * Cost metrics, Estimating sizes of intermediate tables, selectivity * Join optimization, physical plan properties, interesting orders, query transformation * Index cuts, bitmap indexes
- Transactions and recovery * ACID, anomalies, serializability, locks, 2-phase commit protocol, concurrent access to index structures, isolation levels * Implementation of transaction w.r.t. ACID, shadow pages, write ahead log, snapshots
| |
Qualification-goals/Competencies: - For all subjects mentioned in the course contents under the indents students should name the central ideas, which can define relevant terms and explain the functioning of algorithms by means of application examples.
|
Grading through: |
Is requisite for: |
Requires: |
Responsible for this module: Teachers: |
Literature: - A. Kemper, A, Eickler: Datenbanksysteme - Eine Einführung - Oldenbourg-Verlag
|
Language: |
Notes:Admission requirements for taking the module:
- None (the competences of the modules mentioned under ''requires'' are needed for this module, but are not a formal prerequisite).
Admission requirements for participation in module examination(s):
- Successful completion of exercise sheets as specified at the beginning of the semester.
Module Exam(s):
- CS2700-L1: Databases, written exam, 90min, 100% of the module grade. |
Letzte Änderung: 24.7.2023 |
für die Ukraine