81942 - Scalable and Cloud Programming

Learning outcomes

At the end of the course the student will know programming methodologies for data elaboration in the cloud, and will know the issues related with data and process distribution. The student will be able to realize highly scalable applications, both concurrent and distributed, and to parallelize their execution.

Course contents

Analisys of the problems concerning the realization of highly concurrent and distributed applications.

Scalable approaches to the parallelization and distribution of both data and processes, like the MapReduce programming model.

Functional approach to the realization of scalable systems through languages and frameworks like Scala and Spark.

Cloud platforms for the execution of scalable applications like Amazon Web Services (AWS) and Google Cloud Platform (GCP).

Readings/Bibliography

Programming in Scala (3rd edition)
Martin Odersky, Lex Spoon, Bill Venners
Artima

Learning Concurrent Programming in Scala (2nd edition)
Aleksandar Prokopec
Packt Publishing

Learning Spark: Lightning-Fast Big Data Analysis
Holden Karau, Andy Konwinski, Patrick Wendell, Matei Zaharia
O’Reilly

Teaching methods

Theoretical and practical class lectures.

Assessment methods

Project consisting of the realization of a system utilizing the techniques and the platforms discussed during the class lectures.

The final evaluation will be decided by considering the following factors:

- originality and quality of the presented system;

- quality of the oral presentation;

- the knowledge of the course contents.

The presentation of the project work will include also a discussion about the subjects in the course program.

Teaching tools

PC and beamer.

Office hours

See the website of Gianluigi Zavattaro