Distributed Data Management
(in German: Distributed Data Management )
Module-ID: FIN-INF-102404 |
| Link: | LSF |
| Responsibility: | Gunter Saake |
| Lecturer: | Eike Schallehn |
| Classes: |
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| Applicability in curriculum: | - M.Sc. INF: Informatik - M.Sc. INGINF: Informatik - M.Sc. WIF: Informatik - M.Sc. DKE: Data Processing for Data Science - M.Sc. DE: Fachliche Spezialisierung - M.Sc. VC: Computer Science |
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Abbreviation DDM |
Credit Points 6 |
Semester Winter |
Term ab 1. |
Duration 1 Semester |
Language english |
Level Master |
Intended learning outcomes:
The students ...
- know basic principles and advantages of distributed data management
- can implement distributed databases
- understand query and transaction processing in distributed and parallel database systems
- optimize the run-time performance and satisfy requirements regarding reliability and availability of distributed systems
Content:
- Overview and classification of distributed data management (distributed DBMS, parallel DBMS, fedrated DBMS, P2P)
- Distributed DBMS: architecture, distribution design, distributed query processing and optimization, distributed transactions, and transactional replication
- Parallel DBMS: fundamentals of parallel processing, types of parallelization in DBMS, parallel query processing
Workload:
56 h contact hours + 124 h self-study
| Pre-examination requirements: | Type of examination: | Teaching method / lecture hours per week (SWS): |
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Written exam |
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| Prerequisites according to examination regulations: | Recommended prerequisites: |
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none |
Database introduction course |
| Media: | Literature: |
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Comments: