Course - Very Large, Distributed Data Volumes - TDT4225
Very Large, Distributed Data Volumes
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About the course
Course content
Introduction to large and distributed data volumes. Introduction to distributed techniques. How to design data-intensive applications? Reliability, scalability, and maintainability; how we need to think about them; and how we can achieve them. Data models and query languages. Indexing and storage techniques. Encoding of data. Replication, partitioning and transactions. Fault models, consistency and consensus.
Learning outcome
Learning outcome
Knowledge:
By completion of this course, the candidate should be able to explain
1. reliable, scalable, and maintainable distributed systems
2. data models and query languages- indexing- and data storage methods
3. formats for encoding of data
4. models of replication
5. models of partitioning
6. theory of transactions and concurrency
7. fault models
8. consistency and consensus
9. algorithms for consensus
10. synchronization of clocks
11. distributed debugging
12. examples of distributed databases: Amazon Dynamo and Google Spanner
Skills:
By completion of this course, the candidate should be able to
1. develop applications with big data using standard database products.
2. evaluate existing systems and solutions for distributed storage and management of data
3. combine tools to build the properties you need
4. develop new systems for distributed storing and management of data
General competence:
By completion of this course, the student should be able to explain distributed systems.
Learning methods and activities
Lectures, exercises, projects and self-study.
There are compulsory exercises in the subject.
There are two projects involving programming with big data volumes and which are done in small groups.
Compulsory assignments
- Exercises
Further on evaluation
The exam is given in English.
If there is a re-sit examination, the examination form may change from written to oral.
At re-take of course, all parts of the assessment must be re-done.
Recommended previous knowledge
TDT4120 Algorithms and Data Structures and TDT4145 Data Modelling and Database Systems, or equivalent.
Course materials
Information given at start of term.
Credit reductions
| Course code | Reduction | From |
|---|---|---|
| SIF8050 | 7.5 sp |
Subject areas
- Informatics
- Technological subjects
Contact information
Course coordinator
Department with academic responsibility
Examination
Examination
Ordinary examination - Autumn 2024
School exam
The specified room can be changed and the final location will be ready no later than 3 days before the exam. You can find your room location on Studentweb.