Distributed Systems and Parallel Processing WM-I-S2-E1-SRPR
The subject is intended to familiarize participants with the broad issues of distributed systems distributed systems and parallel processing. The purpose of the course is to present issues related to distributed systems: communication between processes, replication and consistency, virtual and real time, and fault tolerance and atomic transactions. The subject also touches on aspects of parallel processing: architecture of computing centers and the cloud, the concept of clusters, the Hadoop system, the Map-Reduce model, the RDD model and Spark, the Scala language.
(in Polish) Dyscyplina naukowa, do której odnoszą się efekty uczenia się
(in Polish) E-Learning
Term 2023/24_Z: (in Polish) E-Learning (pełny kurs) z podziałem na grupy | Term 2024/25_Z: (in Polish) E-Learning | Term 2022/23_Z: (in Polish) E-Learning (pełny kurs) z podziałem na grupy |
(in Polish) Grupa przedmiotów ogólnouczenianych
(in Polish) Opis nakładu pracy studenta w ECTS
Subject level
Learning outcome code/codes
Type of subject
Preliminary Requirements
Course coordinators
Term 2023/24_Z: | Term 2024/25_Z: | Term 2022/23_Z: |
Learning outcomes
Lecture
W1 The student has a basic knowledge of distributed systems and parallel processing.
W2 The student knows the issues of multithreaded operation, socket and gRPC interface, critical section algorithms, time synchronization, replication principles, consistency, fault tolerance and transaction validation algorithms.
W3 The student knows the architecture of computing centers and cloud, Hadoop system and HDFS,
Map-Reduce and RDD model, Spark and Scala language.
Labs
U1 The student can program distributed applications using socket and gRPC interface.
U2 The student can program parallel applications on Hadoop using Map Reduce and Sparc.
U3 The student is able to adapt to the latest technologies in distributed systems and parallel processing using the literature.
K1 The student understands the basic principles of distributed systems and parallel processing and can adapt to the latest technologies in this area.
K2 The student is ready to cooperate with specialists in the field of distributed systems and parallel processing..
Assessment criteria
For all learning outcomes, the following assessment criteria are adopted for all forms of verification:
grade 5: fully achieved (no obvious shortcomings),
grade 4.5: achieved almost fully and criteria for awarding a higher grade are not met,
grade 4: largely achieved and the criteria for a higher grade are not met,
grade 3.5: largely achieved - with a clear majority of positives - and the criteria for granting a higher grade are not met,
grade 3: achieved for most of the cases covered by the verification and criteria for a higher grade are not met,
grade 2: not achieved for most of the cases covered by the verification.
Additional information
Information on level of this course, year of study and semester when the course unit is delivered, types and amount of class hours - can be found in course structure diagrams of apropriate study programmes. This course is related to the following study programmes:
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: