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- Undergraduate major in Mechanical Engineering
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- 工学院，物質理工学院，環境・社会理工学院共通科目
- Liberal arts and basic science courses
- First-Year Courses
- School of Science
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- School of Computing
- School of Life Science and Technology
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School of Environment and Society
- Department of Architecture and Building Engineering
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- Graduate major in Technology and Innovation Management
- Common courses
- Liberal arts and basic science courses
- Academic unit or major
- Graduate major in Computer Science
- Instructor(s)
- Yoshioka Nobukazu Sakamoto Kazunori
- Class Format
- Lecture / Exercise
- Media-enhanced courses
- Day/Period(Room No.)
- Intensive ()
- Group
- -
- Course number
- CSC.T429
- Credits
- 2
- Academic year
- 2016
- Offered quarter
- 2Q
- Syllabus updated
- 2016/12/14
- Lecture notes updated
- -
- Language used
- Japanese
- Access Index
-
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 generally 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 are able to 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.
Keywords
Distributed file system, big data processing, testing, performance tuning.
Competencies that will be developed
| ✔ Specialist skills | Intercultural skills | Communication 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 |
Textbook(s)
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.
