Training and Research
PhD Programme Courses/classes
PhD Course
Credits: 50
Language: inglese
Teacher: Sara Migliorini, Graziano Pravadelli, Ferdinando Cicalese, Giovanni Gerardo Muscolo, Alessandra Di Pierro, Rosalba Giugno, Massimo Merro, Mariano Ceccato, Silvia Francesca Storti, Enrico Gregorio, Matteo Cristani, Zsuzsanna Liptak, Lorenza Brusini, Florenc Demrozi
Big Data
Credits: 3
Language: English
Teacher: Damiano Carra
Chirurgia robotica
Credits: 4
Language: Italian
Teacher: Paolo Fiorini
Big Data (2022/2023)
Teacher
Referent
Credits
3
Language
English
Class attendance
Free Choice
Location
VERONA
Learning objectives
The course offers an overview of the fundamental concepts of distributed computing systems that deal with very large datasets, together with the programming paradigms adopted by these systems. In particular, it will discuss the MapReduce paradigm, and its implementation in Spark. In addition, the system aspects of the distributed computation will be presented, including the data center architectures, and the solutions for storing such large datasets.
Prerequisites and basic notions
Python knowledge
Program
- Introduction to the course
- The MapReduce programming paradigm
- Apache Hadoop and Apache Spark
- Non-relational databases for Big Data
- Datacenter architectures
Bibliography
Didactic methods
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Learning assessment procedures
The exam consists in carrying out a project in which the principles presented in class are applied.
Assessment
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Criteria for the composition of the final grade
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