• A
  • A
  • A
  • ABC
  • ABC
  • ABC
  • А
  • А
  • А
  • А
  • А
Regular version of the site
For visually-impairedFor visually-impairedUser profile (HSE staff only)Search
Advanced search
Menu
HSE University
User profile (HSE staff only)Search
Advanced search

Course Syllabus

Master 2020/2021

Data Management Algorithms

Category 'Best Course for Broadening Horizons and Diversity of Knowledge and Skills'
Category 'Best Course for New Knowledge and Skills'
Type: Elective course (Software Development and Data Analysis)
Area of studies: Applied Mathematics and Informatics
Delivered by: Department of Informatics
Where: St. Petersburg School of Physics, Mathematics, and Computer Science
When: 1 year, 1-3 module
Mode of studies: offline
Instructors: Sergei Fedorenko, Anton Kuznetsov, Boris Novikov
Master’s programme: Software Development and Data Analysis
Language: English
ECTS credits: 9
Contact hours: 92

Course Syllabus

Full SyllabusAsk Question

Abstract

The goal of mastering the discipline "Algorithms for data storage" is to develop students' theoretical knowledge and practical skills on the basics of building and working with data storage systems. Students will get an idea of ​​the implementation of processing and execution of queries in database management systems. As a result of mastering the discipline, the student must: - Know the technology of storage (database) and processing of analytical information, including distributed. - Be able to develop effective algorithms for data storage. - Have skills (gain experience) in using the mathematical apparatus and tools used in information-analytical systems.
Learning Objectives

Learning Objectives

  • The purpose of mastering the discipline "Algorithms for data storage" is to develop students' theoretical knowledge and practical skills on the basics of building and working with data storage systems.
Expected Learning Outcomes

Expected Learning Outcomes

  • Knows: the main components of relational DBMS; main stages of request processing; query tree concept. He knows how to implement various relational operations. He has skills in query optimization. Knows: the concept of graph connections; algorithm for constructing bushy trees.
  • Knows: the concept of transparency in distributed DBMS; types of transparency; aspects of distributed DBMS (autonomy, distribution, heterogeneity). Knows: the main types of distributed DBMS; optimization principles in distributed DBMS; query execution in distributed DBMS; query execution in client-server distributed DBMSs, execution strategies.
  • Knows: the concept of a column DBMS; history of column DBMS; prerequisites for the emergence and popularization of this approach; OLAP and OLTP, star and snowflake schemes. Owns the concepts of: computer architecture; column DBMS in memory using the MonetDB system example; BAT-algebras.
  • Knows: XML query language; XPath and XQuery XQuery runtime systems. Owns the concepts of: OODB and ORDB (data schema, queries); architecture of object systems; buffer management in object systems. Knows: hardware and software Pointer Swizzling; The concept of Path Expression, elements of optimization.
  • Owns the concept of an index. Knows multi-dimensional indexing, two-step scheme. Owns the concept of an R-tree (definition, history, properties; variants of an R-tree). Knows the classification of multidimensional indexing methods; construction algorithm; query calculation algorithm
  • Owns the concept of tuning a DBMS. Knows approaches to setting up the physical layer. He knows the classification of solution methods. Owns the concepts of: horizontal fragmentation; distribution of fragments by keys; iterative and combined solution of allocation and fragmentation problems.
Course Contents

Course Contents

  • The principles of building relational DBMS
  • Some issues of building distributed DBMS
  • Column DBMS
  • Nonclassical DBMS types: XML, graph, object
  • Multidimensional Indexing Elements
  • DBMS tuning task
Assessment Elements

Assessment Elements

  • non-blocking Course project
  • non-blocking Exam
    Экзамен проводится на платформе Zoom. Экзамен проводится в устной форме (опрос по материалам курса). По просьбе преподавателя студент должен быть готов выполнить некоторые задания в письменном виде, после чего сфотографировать и выслать на почту преподавателю. К экзамену необходимо подключиться согласно расписанию, высланному преподавателем на корпоративные почты студентов накануне экзамена. Компьютер студента должен удовлетворять требованиям: наличие рабочей камеры и микрофона, поддержка платформы Zoom. Для участия в экзамене студент обязан: выбрать себе имя в Zoom совпадающее с его именем и фамилией, явиться на экзамен согласно точному расписанию, при ответе включить камеру и микрофон. Во время экзамена студентам запрещается выключать камеру. Ипользование конспектов или других справочных материалов допускается только с разрешения преподавателя. Кратковременным нарушением связи во время экзамена считается нарушение связи менее 5 минут. Долговременным нарушением связи во время экзамена считается нарушение 5 минут и более. При долговременном нарушении связи возможность продолжения студентом участие в экзамене определяется преподавателем. Процедура пересдачи подразумевает использование усложненных заданий.
Interim Assessment

Interim Assessment

  • Interim assessment (1 module)
    0.7 * Course project + 0.3 * Exam
  • Interim assessment (3 module)
    0.7 * Course project + 0.3 * Exam
Bibliography

Bibliography

Recommended Core Bibliography

  • Pathak, N. (2008). Database Management System (Vol. 1st ed). Mumbai [India]: Himalaya Publishing House. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=327167

Recommended Additional Bibliography

  • Harrington, J. L., & Harrington, J. L. (2016). Relational Database Design and Implementation (Vol. Fourth edition). Amsterdam: Morgan Kaufmann. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1214612