Advanced Database Systems

Subject COMP90050 (2016)

Note: This is an archived Handbook entry from 2016.

Credit Points: 12.5
Level: 9 (Graduate/Postgraduate)
Dates & Locations:

This subject has the following teaching availabilities in 2016:

Semester 1, Parkville - Taught on campus.
Pre-teaching Period Start not applicable
Teaching Period 29-Feb-2016 to 29-May-2016
Assessment Period End 24-Jun-2016
Last date to Self-Enrol 11-Mar-2016
Census Date 31-Mar-2016
Last date to Withdraw without fail 06-May-2016


Timetable can be viewed here. For information about these dates, click here.
Time Commitment: Contact Hours: 36 hours, made up of 24 one-hour lectures (two per week) and 12 one-hour workshops (one per week)
Total Time Commitment:

200 hours.

Prerequisites:

One of the following:

Subject
Study Period Commencement:
Credit Points:
Semester 2
12.50

AND

Completion of 50 points of third year computing study or equivalent.

GRADUATE Admission to Masters degree.

Corequisites:

None

Recommended Background Knowledge:

None

Non Allowed Subjects:
Subject

433-421 Web Technologies and Applications
433-461 High Performance Database Systems
433-621 Web Technologies and Applications
433-661 High Performance Database Systems

Core Participation Requirements:

For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Student Support and Engagement Policy, academic requirements for this subject are articulated in the Subject Overview, Learning Outcomes, Assessment and Generic Skills sections of this entry.

It is University policy to take all reasonable steps to minimise the impact of disability upon academic study, and reasonable adjustments will be made to enhance a student's participation in the University's programs. Students who feel their disability may impact on meeting the requirements of this subject are encouraged to discuss this matter with a Faculty Student Adviser and Student Equity and Disability Support: http://services.unimelb.edu.au/disability

Coordinator

Prof Rao Kotagiri

Contact

Prof Rao Kotagiri

email: kotagiri@unimelb.edu.au

Subject Overview:

AIMS

Many applications require access to very large amounts of data. These applications often require reliability (data must not be lost even in the presence of hardware failures), and the ability to retrieve and process the data very efficiently.

The subject will cover the technologies used in advanced database systems. Topics covered will include: transactions, including concurrency, reliability (the ACID properties) and performance; and indexing of both structured and unstructured data. The subject will also cover additional topics such as: uncertain data; Xquery; the Semantic Web and the Resource Description Framework; dataspaces and data provenance; datacentres; and data archiving.

INDICATIVE CONTENT

Topics include:

  • Introduction to High Performance Database Systems
  • Issues of Performance and Reliability
  • Transaction Processing
  • Recovery from Failures
  • Map Reduce Models.
Learning Outcomes:

INTENDED LEARNING OUTCOMES (ILO)

On completion of this subject the student is expected to:

  1. Understand issues related performance and reliability in building applications involving large-scale database systems
  2. Understand Database Technologies used in large-scale applications such as Google search Engines
  3. Understand the concepts and technologies underpinning new forms of Web data
  4. Deep knowledge of transaction processing and recovery from failures and concepts employed in modern database systems

Assessment:
  • One written assignment (40%), due in approximately week 12, of approximately 3500 words long, requiring approximately 50 - 55 hours of work per student. The assignment is an extensive survey of a research topic related to database technologies and requires an oral presentation to the class.
  • The assignment is designed to address Intended Learning Outcomes (ILOs) 1-4 and all General skills
  • A 2-hour end-of-semester written examination (60%). This test assesses all topics covered in the subject.

Prescribed Texts: None
Breadth Options:

This subject is not available as a breadth subject.

Fees Information: Subject EFTSL, Level, Discipline & Census Date
Generic Skills:

On completion of the subject the student should have the following skills:

  • Ability to undertake problem identification, formulation, and solution
  • Ability to utilise a systems approach to complex problems and to design and operational performance
  • Ability to manage information and documentation
  • Capacity for creativity and innovation
  • Ability to communicate effectively, with the engineering team and with the community at large.
Notes:

LEARNING AND TEACHING METHODS

This course is taught over 12 weeks, each week with two one hour formal lectures and a one hour workshop. During the workshops the students are given problems to solve to reinforce the previous week’s lecturing material. The problem solving nature of the workshops is geared for the students to learn and understand the concepts of the subject material.

INDICATIVE KEY LEARNING RESOURCES

Transaction Processing: Concepts and Techniques (The Morgan Kaufmann Series in Data Management Systems) by Jim Gray and Andreas Reuter

Lecture slides

Addition published articles in Journals and Conferences

CAREERS / INDUSTRY LINKS

The concepts developed in the subject are relevant to many fields including IT, Engineering, Commerce, Government Organizations, Research Institutes and Institutions in Medicine where large scale database are used. Many industries are moving their applications to Cloud Platforms and understanding performance issues will be key to success to such transformations.

Related Course(s): Doctor of Philosophy - Engineering
Master of Information Technology
Master of Information Technology
Master of Philosophy - Engineering
Master of Science (Computer Science)
Related Majors/Minors/Specialisations: B-ENG Software Engineering stream
MIT Computing Specialisation
MIT Distributed Computing Specialisation
MIT Spatial Specialisation
Master of Engineering (Software)

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