ECTS credits ECTS credits: 4.5
ECTS Hours Rules/Memories Student's work ECTS: 76.5 Hours of tutorials: 4.5 Expository Class: 13.5 Interactive Classroom: 18 Total: 112.5
Use languages Spanish, Galician
Type: Ordinary subject Master’s Degree RD 1393/2007 - 822/2021
Departments: Electronics and Computing
Areas: Computer Architecture and Technology
Center Higher Technical Engineering School
Call: First Semester
Teaching: With teaching
Enrolment: Enrollable | 1st year (Yes)
The every time greater quantity of accessible information through Internet does that the efficient processing of big quantities of data was every time of greater interest. This has carried to the development of new techniques of storage and processing of large quantities of information, techniques that adapt of natural form to the systems distributed.
The main aim of this matter is to give to know different techniques of processing of big amounts of information, instructing to the student in their utilisation for the processing of the so named Big Data.
1. Big Data and MapReduce
2. Introducing Hadoop
3. HDFS
4. MapReduce with Hadoop
5. Apache Spark
6. Other technologies: Apache Flink
Basic bibliography
- Classnotes provided by the teacher
- T. White, Hadoop: The Definitive Guide, 4th Edition, O'Reilly, 2015
- B. Chambers, M. Zaharia, Spark: The Definitive Guide, O'Reilly, 2018
Complementary bibliography
- Holden Karau, Andy Konwinski, Patrick Wendell, Matei Zaharia, Learning Spark. Lightning-Fast Big Data Analysis, O'Reilly, 2015
- Chuck Lam, Hadoop in Action, Manning, 2011
- Fabian Hueske, Vasiliki Kalavri, Stream Processing with Apache Flink", O'Reilly, 2019
-Students will be able to install, configure and manage the basic software for processing massive data.
- Students will be able to implement specialized codes in different languages in the massive data processing.
- The student will know and learn to use some of the tools available to develop and run applications for massive data cloud.
- The student will acquire the necessary skills for search, selection and management of resources (literature, software, etc.) related to Big Data.
Degree competences that work (see memory title):
- Basic: CB6, CB10.
- Transverse / General: T1, G2, G5, T4.
- Specific: E3, E4, E5.
-Lectures, in which the content of each subject is discussed. The student will have copies of the slides in advance and the teacher will promote an active attitude, asking questions that may clarify specific aspects and leaving open issues for student reflection.
- Practical classes in the computer classroom, allowing students to become familiar from a practical standpoint with the issues discussed in the lectures.
EDUCATIONAL ACTIVITIES character and its relationship with the competences of the degree
- Lectures: given by the teacher and presentation of seminars. Worked competencies: CB6, E3, E4, E5.
- Practical classes of laboratory, problem solving and case studies. Worked competencies: CB10, T1, T4, G2.
- Scheduled tutorials: guidance for the conduct of individual or group work, solving doubts and ongoing evaluation activities. Worked competencies: T1.
- Consideration. Worked competencies: CB6, T1, G5, E3, E4, E5
Training activities not attending classes and their relationship to the competences of the degree:
- Personal work: consulting literature, self-study, development of programmed activities, preparing presentations and papers. Number of hours: 76.5. Worked competencies: CB10, T1, T4, G2, G5
IN CASE OF THAT THE USC DETERMINES THE SHIFT TOWARDS SCENARIO 2 (DISTANCE) OR SCENARIO 3 (CLOSURE OF FACILITIES), THE TEACHING METHODOLOGY WILL BE MODIFIED ACCORDING TO THE CONTINGENCY PLAN INDICATED IN THE SECTION "OBSERVATIONS".
- Evaluation of the practical part: 90%
- Continued monitoring and objectified active participation: 10%
To pass the subject, a total score of 5 or above must be achieved.
Students who are not new enrollment do not keep grades from previous years.
Recovery opportunity (July) and extraordinary:
The evaluation will be the same as in the ordinary opportunity. Students who did not submit the proposed works throughout the semester must submit them before the established date.
Condition for Not Submitted qualification: no practice submitted.
In the case of fraudulent performance of exercises or tests, the regulations of the Normativa de avaliación do rendemento académico dos estudantes e de revisión de cualificacións will be applied.
In the application of the Normativa da ETSE sobre plaxio (approved by the ETSE Council on 12/19/2019), the total or partial copy of any practical ot theory exercise will mean failure on both opportunities of the course, with a grade of 0.0 in both cases.
IN CASE OF THAT THE USC DETERMINES THE SHIFT TOWARDS SCENARIO 2 (DISTANCE) OR SCENARIO 3 (CLOSURE OF FACILITIES), THE SYSTEM OF EVALUATION WILL BE MODIFIED ACCORDING TO THE CONTINGENCY PLAN INDICATED IN THE SECTION "OBSERVATIONS".
-Blackboard classes: 12 contact hours + 20 h autonomous work of the student
- Practical classes: 18 contact hours + 46.5 h autonomous work of the student
- Tutorials and evaluation activities: 6 contact hours + 10 h autonomous work of the student
- Total: 112.5 h
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- Classes are taught in Spanish. Videoconferencing, chat, etc.: intensive use of online communication tools will be made
The software tools used in this subject are open source.
Contingency plan:
In the event that the health situation advises establishing a Scenario 2 (distance):
1) all the theory classes will be taught online (synchronously by Microsoft Teams or asynchronously through the publication of videos recorded by the teaching staff),
2) interactive classes will be taught face-to-face in a computer room,
3) the weight of the different parts of the subject and the requirements to pass the subject will remain unchanged
4) the final test will be done in face-to-face
In the event that the health situation advises establishing a Scenario 3 (closure of the facilities):
1) all the expository classes will be taught online (synchronously by Microsoft Teams or asynchronously through the publication of videos recorded by the teaching staff),
2) all interactive classes will be taught online (synchronously by Microsoft Teams or asynchronously through the publication of videos recorded by the teaching staff),
3) the weight of the different parts of the subject and the requirements to pass the subject will remain unchanged
4) The final test will be done online, using Microsoft Teams and the tools of the Moodle virtual classroom.
Anselmo Tomás Fernández Pena
Coordinador/a- Department
- Electronics and Computing
- Area
- Computer Architecture and Technology
- Phone
- 881816439
- tf.pena [at] usc.es
- Category
- Professor: University Professor
| Monday | |||
|---|---|---|---|
| 16:00-17:30 | Grupo /CLE_01 | Spanish | PROJECTS |
| 01.17.2022 16:00-20:45 | Grupo /CLE_01 | PROJECTS |
| 01.17.2022 16:00-20:45 | Grupo /CLIL_01 | PROJECTS |
| 06.24.2022 16:00-20:45 | Grupo /CLIL_01 | PROJECTS |
| 06.24.2022 16:00-20:45 | Grupo /CLE_01 | PROJECTS |