Course - Very Large, Distributed Data Volumes - TDT4225
Very Large, Distributed Data Volumes
About
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
3. indexing- and data storage methods
4. formats for encoding of data
5. models of replication
6. models of partitioning
7. theory of transactions and concurrency
8. fault models
9. consistency and consensus
10. synchronization of clocks
11. distributed debugging
12. content delivery networks and dirstibuted hash tables
13. database-as-a-service
14. trustworthy data systems
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. Each of these counts for 20% of the final grade. Total: 40%.
The final exam counts for 60% of the final grade.
Compulsory assignments
- Exercises
Further on evaluation
The exam is given in English.
If there is a re-sit examination in August, the examination form may change from written to oral.
In case of voluntary resit the entire course must not be repeated.
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