Teaching Responsibility

LJMU Schools involved in Delivery:

Computer Science and Mathematics

Learning Methods

Lecture

Practical

Tutorial

Module Offerings

7123COMP-JAN-CTY

Aims

To allow students to develop new advanced cloud-based software development skills To combine existing and new networking and software development skills in a practical ‘Big Data’ context To use real-world Cloud-based and locally administered systems to apply their knowledge to ‘Big Data’ problems

Learning Outcomes

1.
Evaluate new paradigms and techniques for data management, systems and programming
2.
Design solutions using a big data paradigm that access and manipulate in a massively parallel fashion for offline stored data
3.
Apply big data programming tools to build applications that access and manipulate in a massively parallel fashion for online streaming data
4.
Interpret and categorise challenges involved in developing large scale applications with big data systems

Module Content

Outline Syllabus:Distributed systems issues (fault tolerance, high performance, resource utilisation, caching, load balancing) Distributed file systems Data Management with data modelling, consistency, query processing, indexing Functional language that underpins large scale parallelism, e.g. Map-Reduce Parallel programming model Query languages and environments for big data systems Publish/subscribe systems for large scale information dissemination
Additional Information:The theoretical work will build on students existing knowledge of distributed system, refocussing on its application to building large scale cloud applications. The practical element will involve hands-on cloud application development using real-world cloud services.

Assessments

Report

Centralised Exam