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16SDI01 - Distributed Computing

• This is an "optional" course in the Master of Software Engineering in the Data Engineering line of research at CIMAT.

Description

Nowadays, virtually all of the computers form a distributed computing system. Developers, software architects, and project managers need to understand the basis and the real-world application of distributed computing. We will study the basis of distributed computing and its application in Big Data Analysis.

Objective

Implement a system in a distributed computing environment.

Specific objectives

1. Understand the different types of distributed computing environments
2. Implement a distributed computing system in the cloud
3. Basic knowledge of the tools used in the management of a distributed computing environment

Topics

1. Introduction
   1. Basic concepts: Program, Process, Message, Package, Protocol, Network Component, Distributed COmputing system
   2. Characteristics of the Distributed Computing Systems
   3. 8 fallacies of distributed computing systems
2. Types of distributed computing systems
   1. Functionale distribution
   2. Task distribution
3. Task distribution
   1. Real time analysis in Apache Spark
      1. Installation and configuration
      2. Scala programming
   2. Batch processing with Apache Hadoop
      1. Installation and configuration
      2. Python programming
4. Functionale distribution
   1. Queue system architecture
   2. RabbitMQ installation
      1. Workers
      2. Pub/Sub
      3. Routing
      4. RPC
   3. Patterns in distributed computing systems.

Grades

Rules

• Email delivery to luis.dominguez
• Pack your homework and name the file appropriately: t1_lastname.zip
• Use PGP to encrypt your file. Public Key
• Time delivery is at mid-night of the day, 10% penalty per delayed day
• No plagiarism
• Include bibliography
• Add documentation in LNCS format to your homework:
  • For programs, the report must be 4-6 pages + bib
  • For essay, 5-10 pages + bib

Sections available

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