Distributed Data Processing
| Title | Κατανεμημένη Επεξεργασία Δεδομένων / Distributed Data Processing |
| Code | DWS202 |
| Faculty | Sciences |
| School | Informatics |
| Cycle / Level | 2nd / Postgraduate |
| Teaching Period | Spring |
| Coordinator | Anastasios Gounaris |
| Common | No |
| Status | Active |
| Course ID | 600016261 |
Programme of Study: PMS EPISTĪMĪ DEDOMENŌN KAI PAGKOSMIOU ISTOU (2018 éōs sīmera) PF
Registered students: 16
| Orientation | Attendance Type | Semester | Year | ECTS |
|---|---|---|---|---|
| KORMOS | Elective Courses belonging to the selected specialization | 2 | 1 | 7.5 |
| Academic Year | 2025 – 2026 |
| Class Period | Spring |
| Faculty Instructors |
|
| Weekly Hours | 3 |
| Class ID | 600290238
|
Course Type 2021
Specialization / Direction
Course Type 2016-2020
- Scientific Area
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
- Face to face
Digital Course Content
- e-Study Guide https://qa.auth.gr/en/class/1/600290238
- eLearning:
Language of Instruction
- Greek (Instruction, Examination)
Prerequisites
General Prerequisites
Knowledge of programming in Java is considered very significant.
Learning Outcomes
Cognitive:
Μethodologies for big data management. Understanding of the main methodologies for distributed database design and query processing. Deeper study of database technologies and familiarization with data warehouses.
Skills:
Acquisition of skills in applying big data management techniques, and in using existing tools.
General Competences
- Apply knowledge in practice
- Retrieve, analyse and synthesise data and information, with the use of necessary technologies
- Adapt to new situations
- Make decisions
- Work autonomously
- Work in teams
- Work in an international context
- Generate new research ideas
- Design and manage projects
- Be critical and self-critical
- Advance free, creative and causative thinking
Course Content (Syllabus)
Basic concepts of Distributed Databases (DDB), Distributed Database Systems, DDB Architecture, Autonomy and Heterogeneity Issues, Design of DDBs and Data Allocation, Distributed query processing and optimization, Distributed Database Transactions, reliability and data replication, Parallel databases and relationship with DDBs, Grid data management, Adaptive query processing, Map-Reduce techniques, Modern systems, NoSQL DBMSs and current research issues.
Keywords
distributed databses, Map-Reduce, συστήματα NoSQL
Educational Material Types
- Notes
- Slide presentations
- Book
Use of Information and Communication Technologies
Use of ICT
- Use of ICT in Course Teaching
- Use of ICT in Laboratory Teaching
Course Organization
| Activities | Workload | ECTS | Individual | Teamwork | Erasmus |
|---|---|---|---|---|---|
| Lectures | 39 | ✓ | |||
| Reading Assigment | 50 | ✓ | |||
| Project | 100 | ✓ | |||
| Written assigments | 36 | ✓ | |||
| Total | 225 |
Student Assessment
Description
Written exams, project, presentations
Student Assessment methods
- Written Exam with Short Answer Questions (Formative, Summative)
- Written Assignment (Formative, Summative)
- Oral Exams (Formative, Summative)
- Performance / Staging (Formative, Summative)
- Written Exam with Problem Solving (Formative, Summative)
Bibliography
Course Bibliography (Eudoxus)
Principles of Distributed Database Systems, M. Tamer Özsu, Patrick Valduriez, 3rd edition
Additional bibliography for study
- Garcia-Molina, J.D. Ullman, J.D. Widom ΣΥΣΤΗΜΑΤΑ ΒΑΣΕΩΝ ΔΕΔΟΜΕΝΩΝ
- "Data-Intensive Text Processing with MapReduce" των Jimmy Lin και Chris Dyer
Last Update
08-02-2024
