Architectures for big data

A.Y. 2020/2021
6
Max ECTS
48
Overall hours
SSD
INF/01
Language
English
Learning objectives
The course aims at describing the big data processing framework, both in terms of methodologies and technologies. Part of the lessons will focus on Apache Spark and distributed patterns.
Expected learning outcomes
Students will learn:

How to distribute computation over clusters using Map Reduce model
How to write Apache Spark code
How Hadoop works and why it works that way
What a software architecture is
How to design batch architectures to manage data workflows
Several design patterns that could be used in a distributed environment
The limit of traditional SQL with Big Data
Course syllabus and organization

Single session

Responsible
Lesson period
First semester
INF/01 - INFORMATICS - University credits: 6
Lessons: 48 hours
Professor: Condorelli Andrea
Professor(s)