Details

Faculty	Faculty of Science and Medicine
Domain	Computer Science
Code	UE-SIN.07612
Languages	English
Type of lesson	Lecture
Level	Master
Semester	AS-2022

Schedules and rooms

Summary schedule	Wednesday 14:15 - 17:00, Hebdomadaire (Autumn semester)
Struct. of the schedule	3h par semaine durant 14 semaines
Contact's hours	42

Teaching

Responsibles	Cudré-Mauroux Philippe
Teachers	Cudré-Mauroux Philippe Lerner Alberto
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.
Training objectives	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.
Comments	MSc-CS BENEFRI - (Code Ue: 63021 / Track: T6) The exact date and time of this course as well as the complete course list can be found at http://mcs.unibnf.ch/. Course and exam registration on ACADEMIA (not myunifr.ch). Please follow the instructions on https://mcs.unibnf.ch/organization/
Softskills	No
Off field	No
BeNeFri	Yes
Mobility	Yes
UniPop	No

Written exam

Assessments methods

By rating