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.