Big data infrastructures
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Enseignement
Détails
Faculté Faculté des sciences et de médecine Domaine Informatique Code UE-SIN.07612 Langues Anglais Type d'enseignement Cours
Cursus Master Semestre(s) SA-2020 Horaires et salles
Horaire résumé Mercredi 14:15 - 17:00, Hebdomadaire (Semestre d'automne)
Struct. des horaires 3h par semaine durant 14 semaines Heures de contact 42 Enseignement
Responsables - Cudré-Mauroux Philippe
Enseignants - Cudré-Mauroux Philippe
Assistants - Bhardwaj Akansha
- Rosso Paolo
Description This course focuses on conceptual and architectural issues related to the design and deployment of modern data management infrastructures in a Big Data context. It starts with a review of distributed transaction processing techniques, classical parallel databases systems and ACID-style semantics in shared-nothing architectures. The course then delves into modern wide-area data processing, with an emphasis on recent systems developed to solve large-scale problems using clusters of commodity machines. In this second part, the course covers distributed storage systems (such as Google's BigTable), wide-area hash-tables (like Cassandra), data-intensive computing platforms (Hadoop) and nosql systems. Hands on programming exercises using those platforms will be an important part of this course.
This course focuses on conceptual and architectural issues related to the design and deployment of modern data management infrastructures in a Big Data context. It starts with a review of distributed transaction processing techniques, classical parallel databases systems and ACID-style semantics in shared-nothing architectures. The course then delves into modern wide-area data processing, with an emphasis on recent systems developed to solve large-scale problems using clusters of commodity machines. In this second part, the course covers distributed storage systems (such as Google's BigTable), wide-area hash-tables (like Cassandra), data-intensive computing platforms (Hadoop) and nosql systems. Hands on programming exercises using those platforms will be an important part of this course.Objectifs de formation Students will learn about classical distributed transaction processing and parallel database systems. They will get exposed to modern data management infrastructures deployed by current Web giants like Google or Yahoo! to power a wide range of Web services. Finally, they will understand the fundamental tradeoffs between consistency, availability and fault-tolerance for wide-area data processing on the Internet.
Commentaire MSc-CS BENEFRI - (Code Ue: 63021 / Tracks: T6)
The exact date and time of this course as well as the full course list can be found under http://diuf.unifr.ch/drupal/mcs/program/courses-timetable/courses.Softskills Non Hors domaine Non BeNeFri Oui Mobilité Oui UniPop Non -
Dates et salles
Date Heure Type d'enseignement Lieu 16.09.2020 14:15 - 17:00 Cours PER 21, salle G120 23.09.2020 14:15 - 17:00 Cours PER 21, salle G120 30.09.2020 14:15 - 17:00 Cours PER 21, salle G120 07.10.2020 14:15 - 17:00 Cours PER 21, salle G120 14.10.2020 14:15 - 17:00 Cours PER 21, salle G120 21.10.2020 14:15 - 17:00 Cours PER 21, salle G120 28.10.2020 14:15 - 17:00 Cours PER 21, salle G120 04.11.2020 14:15 - 17:00 Cours PER 21, salle G120 11.11.2020 14:15 - 17:00 Cours PER 21, salle G120 18.11.2020 14:15 - 17:00 Cours PER 21, salle G120 25.11.2020 14:15 - 17:00 Cours PER 21, salle G120 02.12.2020 14:15 - 17:00 Cours PER 21, salle G120 09.12.2020 14:15 - 17:00 Cours PER 21, salle G120 16.12.2020 14:15 - 17:00 Cours PER 21, salle G120 -
Modalités d'évaluation
Examen écrit
Mode d'évaluation Par note -
Affiliation
Valable pour les plans d'études suivants: BcMa - Data Analytics - 30 ECTS
Version: 2020/SA-v01
À choix 9 crédits ECTS > TMD: Technologies and Modelling for DigitalizationÀ choix 9 crédits ECTS > Data Science
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Version: 2020/SA_V01
Cours > Modules informatique de gestion > TMD: Technologies and Modelling for DigitalizationCours > Modules informatique > Data Science
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Version: 2020_1/v_01
Complément au doctorat ( Faculté des sciences et de médecine) > UE de spécialisation en Informatique (niveau master)
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Version: ens_compl_sciences
Paquet indépendant des branches > UE de spécialisation en Informatique (niveau master)
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Version: 2015_1/V_01
Formation continue > UE de spécialisation en Informatique (niveau master)
Informatique [POST-DOC]
Version: 2015_1/V_01
Formation continue > UE de spécialisation en Informatique (niveau master)
MSc en informatique (BeNeFri)
Version: 2023_1/V_01
MSc en informatique (BeNeFri), cours, séminaires et travail de Master > T6: Data Science
Ma - Business Communication : Informatique de gestion - 90 ECTS
Version: 2020/SA_V02
Cours - 60 ECTS > Groupe d'option > Informatique de gestion > Cours > Modules informatique de gestion > TMD: Technologies and Modelling for DigitalizationCours - 60 ECTS > Groupe d'option > Informatique de gestion > Cours > Modules informatique > Data Science
Ma - Informatique de gestion - 90 ECTS
Version: 2020/SA-v01
Cours - min. 45 ECTS > Modules informatique de gestion - min. 22 ECTS > TMD: Technologies and Modelling for DigitalizationCours - min. 45 ECTS > Modules informatique/informatique de gestion > TMD: Technologies and Modelling for DigitalizationCours - min. 45 ECTS > Modules informatique/informatique de gestion > Data Science
Ma - Informatique de gestion - 90 ECTS
Version: 2019/SA_V01
Cours - min. 45 ECTS > Modules informatique/informatique de gestion > TMD: Technologies and Modelling for DigitalizationCours - min. 45 ECTS > Modules informatique/informatique de gestion > Data ScienceCours - min. 45 ECTS > Modules informatique de gestion - min. 22 ECTS > TMD: Technologies and Modelling for Digitalization