Show/hide contentOpenClose All
Curricular information is subject to change
On successful completion of this module the learner will be able to:
- Review the data processing using Shell and traditional data management systems using SQL;
- Understand the problem of managing data at scale and why traditional data management systems are failing
- Understand the various data management paradigms used in the context of Big Data (e.g., relational, NoSQL)
- Understand the role of distributed file systems (e.g., using HDFS) that support big data programming
- Understand Big Data programming models such as Map/Reduce and Spark, and how to use them on real examples
- Understand other Spark extensions for various big data applications such as MLlib, GraphX, Spark Streaming, etc.
Student Effort Type | Hours |
---|---|
Lectures | 12 |
Practical | 24 |
Autonomous Student Learning | 64 |
Total | 100 |
Not applicable to this module.
Description | Timing | Component Scale | % of Final Grade | ||
---|---|---|---|---|---|
Examination: 2-hour closed-book paper-based exam | 2 hour End of Trimester Exam | No | Graded | No | 60 |
Class Test: MCQs for basic big data programming concepts | End of trimester MCQ | n/a | Graded | No | 10 |
Group Project: A comparative study on solving a data-intensive task with and without big data programming. | Coursework (End of Trimester) | n/a | Graded | No | 30 |
Resit In | Terminal Exam |
---|---|
Summer | Yes - 2 Hour |
• Feedback individually to students, on an activity or draft prior to summative assessment
• Group/class feedback, post-assessment
• Self-assessment activities
solutions to lab practices will be provided;
Name | Role |
---|---|
Priscilla Adong | Tutor |
Ms Cassidy Aytan Gigan | Tutor |
Riju Das | Tutor |
Zhongping Dong | Tutor |
Mossoun Franck Malick Jaures Ebiele | Tutor |
Mr Patrick English | Tutor |
Jiaying Guo | Tutor |
Nils Höhing | Tutor |
Haotian Li | Tutor |
Xiao Li | Tutor |
Mr Hrishikesh Dilip Mulay | Tutor |
Furqan Rustam | Tutor |
Weijiong You | Tutor |
Practical | Offering 1 | Week(s) - 20, 21, 22, 23, 24, 25, 26 | Fri 09:00 - 10:50 |
External & School Exams | Offering 1 | Week(s) - 28 | Fri 10:00 - 12:50 |
External & School Exams | Offering 1 | Week(s) - 28 | Fri 10:00 - 13:50 |
Lecture | Offering 1 | Week(s) - 20, 21, 22, 23, 24, 25 | Thurs 11:00 - 12:50 |
Lecture | Offering 1 | Week(s) - 26 | Thurs 11:00 - 12:50 |
Lecture | Offering 1 | Week(s) - 26 | Thurs 11:00 - 13:50 |
Practical | Offering 1 | Week(s) - 20, 21, 22, 23, 24, 25 | Thurs 14:00 - 15:50 |