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LARGE-SCALE COMPUTING

CODICE 101799
ANNO ACCADEMICO 2020/2021
CFU
  • 9 cfu al 1° anno di 10852 COMPUTER SCIENCE (LM-18) - GENOVA
    		•
    SETTORE SCIENTIFICO DISCIPLINARE INF/01
    LINGUA Inglese
    SEDE
  • GENOVA
    		•
    PERIODO 1° Semestre
    MATERIALE DIDATTICO AULAWEB

    PRESENTAZIONE

    We will study principles and algorithms, architectures and technologies, programming models and frameworks needed to support data-intensive applications

    OBIETTIVI E CONTENUTI

    OBIETTIVI FORMATIVI

    Learning the theoretical, methodological, and technological fundamentals of advanced data processing architectures, large-scale distributed environments, and data intensive programming including Docker, HDFS, Hadoop, Spark, and Cloud/IoT platforms.

    OBIETTIVI FORMATIVI (DETTAGLIO) E RISULTATI DI APPRENDIMENTO

     

    Labs will be focused on map-reduce architectures and libraries
    Technology: HDFS, Hadoop, Spark using Python and Java/Scala
    Intermediate lab activities (5/6 labs)
    Final project

    PREREQUISITI

    Sequential, Concurrent and Distributed Programming
    Database Theory and Practice
    Basic notions of Data Analysis
     

    MODALITA' DIDATTICHE

    Frontal lectures
    Lab sessions

    PROGRAMMA/CONTENUTO

    Distributed Systems and Distributed Programming
    Virtualization and containers 
    Parallel Python
    Distributed data systems and shared nothing architectures
    Partitioning
    Replication
    Fault Tolerance
    CAP Theorem
    Map/Filter/Reduce and Generators in Python
    Map in Multiprocessing
    Introduction to Hadoop and HDFS
    Map Reduce
    Map Reduce: Simple Design Patterns and Relational Algebra Operators
    Hadoop Runtime System
    Apache Spark
    Apache Spark Internals
    PySpark, Java/Scala Spark
    Streaming Data 
    Streaming Spark

    DOCENTI E COMMISSIONI

    Commissione d'esame

    GIORGIO DELZANNO (Presidente)

    GIOVANNA GUERRINI

    BARBARA CATANIA (Presidente Supplente)

    FEDERICO DASSERETO (Supplente)

    LEZIONI

    Orari delle lezioni

    L'orario di tutti gli insegnamenti è consultabile su EasyAcademy.

    ESAMI

    MODALITA' D'ESAME

    Final online test with open and closed questions
    Project presentation and discussion 
    Bonusf for at least 70% attendance rate (if in presence) and lab assignments successfully delivered

    MODALITA' DI ACCERTAMENTO

    The proposed exercises, project and final test cover both conceptual and practical aspects presented in the course

    Calendario appelli

    Data Ora Luogo Tipologia Note
    18/01/2021 09:00 GENOVA Esame su appuntamento
    14/06/2021 09:00 GENOVA Esame su appuntamento
    06/09/2021 09:00 GENOVA Esame su appuntamento
    10/01/2022 09:00 GENOVA Esame su appuntamento