2019 Workshop on Cloud-based Application Development

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Academic unit or major
Graduate major in Computer Science
Yoshioka Nobukazu  Sakamoto Kazunori 
Course component(s)
Lecture / Exercise
Day/Period(Room No.)
Intensive ()  
Course number
Academic year
Offered quarter
Syllabus updated
Lecture notes updated
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Course description and aims

Through the development of cloud computing environments, the demand for efficiently processing and utilizing large-scale data is increasing. However, there are still few opportunities to experience applied examples of distributed processing technology for large-scale data, making it difficult to learn those skills and know-how. In this course, we will use the educational cloud, constructed and operated by the National Institute of Informatics, as an exercise environment. By utilizing material focused on actual examples, students can experience distributed processing application development in practice.

In this course, students will learn about distributed processing technology for practical large-scale data, mainly through exercises.

Student learning outcomes

By the end of this course, students will be able to grasp techniques of practical distributed computation handling big data.


Distributed file systems, big data processing, testing, performance tuning.

Competencies that will be developed

Intercultural skills Communication skills Specialist skills Critical thinking skills Practical and/or problem-solving skills

Class flow

Students will use the educational cloud constructed and operated by the National Institute of Informatics as an exercise environment, and proceed with lessons mainly through exercises.

Course schedule/Required learning

  Course schedule Required learning
Class 1 Construction of Development Environment and Overview of Hadoop Overview of Hadoop
Class 2 Application of MapReduce Application of MapReduce
Class 3 Advanced Technique of MapReduce Advanced Technique of MapReduce
Class 4 Testing of MapReduce Application Software Testing of MapReduce Application Software
Class 5 Performance Tuning in Hadoop Performance Tuning in Hadoop
Class 6 Operation and Monitoring of Hadoop Operation and Monitoring of Hadoop
Class 7 Programming Practices of Hadoop Programming Practices of Hadoop


Handouts will be provided during the course.

Reference books, course materials, etc.

The materials will be provided from the Web site which will be introduced during the course.

Assessment criteria and methods

Practice Q&A: 20%
Report: 80%

Related courses

  • CSC.T428 : Foundation of Cloud Systems
  • CSC.T521 : Cloud Computing and Parallel Processing
  • MCS.T407 : High Performance Computing

Prerequisites (i.e., required knowledge, skills, courses, etc.)

This course is given in Japanese.


This lecture is organized under the collaboration of the National Institute on Informatics, which is given outside the university's campus. The amount number of students is limited due to facilities.
The detailed information on this lecture will be announced on the (offline) bulletin board at West-8E building(3F).

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