Перспективные базы данных

2024/2025

Статус: Маго-лего

Кто читает: Департамент программной инженерии

Когда читается: 2, 3 модуль

Охват аудитории: для всех кампусов НИУ ВШЭ

Преподаватели: Брейман Александр Давидович

Язык: английский

Кредиты: 6

Контактные часы: 56

Full Syllabus

Abstract

The objective of Advanced databases course delivery is to form professional competencies related to design and implementation of non-relational databases, including object-oriented, object-relational, deductive, multidimensional and semistructured database models. Students will get a grasp on strengths and weaknesses of wide spectrum of approaches to data storage, search and retrieval, resulting in informed choice of database model. The course is based on “Advanced databases” course of Eindhoven University of Technology (Eindhoven, Netherlands), Faculty of Math and Computer Science, author and principal lecturer – Prof. Dr. Toon Calders. While Databases course of bachelor curricula covered many of the core concepts behind database modeling, design and implementation, there are many other considerations that should be addressed for successful scientific or industry career in this field. The main objective of this course is to expand students’ view and introduce advanced topics, including object-oriented extensions, deductive databases and appropriate query languages, data warehouses and online analytical data processing, and XML. The additional topics covered in this course will help students become more proficient in choosing appropriate technologies for projects and will expand their knowledge base so that they have a better understanding of the field. By the end of the course, students should have a solid grasp on business intelligence tools and XML, which will prove to be invaluable as they progress further in computer science studies.

Learning Objectives

This course studies different database models and their properties. The models that will be discussed are: • Object-oriented databases; • Deductive databases (Datalog); • Data warehousing and online analytical processing (ROLAP, MOLAP and HOLAP); • The XML data model (query languages XQuery and XPath, DTDs). For these conceptual models the course will concentrate on the following points: Why was the database model introduced? Which of the shortcomings of other models does it address? What are the most important concepts and notions for the database model? How is the model implemented? Which are the main techniques? The importance of understanding the internals of a particular database model cannot be overemphasized as it is closely connected to its limitations.

Expected Learning Outcomes

Can choose dimensions for multidimensional database, group them into hierarchies and define aggregates.
Can create and interpret XLST transformations.
Can reason about expressibility of relational query languages using notion of locality.
Can write and understand XPath and XQuery expressions.
Demonstrate capability of reading and writing queries in SQL and/or relational algebra.
Knows data storage methods usable for object-oriented program systems, including pure object database systems and object-relational mappers, its advantages and disadvantages.
Knows implementation and optimization techniques for Datalog translator.
Knows models and methods of organization of deductive databases using Datalog language.
Knows principles of view choice for materialization
Knows the reference architectures of data warehouses and is aware of the basic functionality offered by available commercial and free data warehousing systems.
Knows the shortcomings and restrictions of relational data model.
Knows XML document model, DTD and XML Schema.
Master methods and tools for creating analytical database solutions.

Course Contents

Advanced topics in databases: introduction
Shortcomings of relational model
Object-oriented databases
Deductive databases
Data warehousing and OLAP
Semistructured data

Assessment Elements

Работа на семинарах
Домашнее задание (Cassandra)
Контрольная работа
Домашнее задание (DWH)
Домашнее задание (Datalog)
Экзамен

Interim Assessment

2024/2025 3rd module
0.2 * Домашнее задание (Cassandra) + 0.1 * Домашнее задание (DWH) + 0.1 * Домашнее задание (Datalog) + 0.2 * Контрольная работа + 0.1 * Работа на семинарах + 0.3 * Экзамен

Bibliography

Recommended Core Bibliography

Foster, E. C., & Godbole, S. (2016). Database Systems : A Pragmatic Approach (Vol. Second edition). [United States]: Apress. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1174505
Greco, S., & Molinaro, C. (2016). Datalog and Logic Databases. San Rafael, California: Morgan & Claypool Publishers. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1100404

Recommended Additional Bibliography

Celko, J. (2006). Joe Celko’s Analytics and OLAP in SQL. San Francisco, Calif: Morgan Kaufmann. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=195632
Elmasri, R., & Navathe, S. (2014). Fundamentals of Database Systems: Pearson New International Edition (Vol. Sixth edition). Harlow, Essex: Pearson. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1418149
Freeman, A., & Rattz, J. C. (2010). Pro LINQ : Language Integrated Query in C# 2010. [New York]: Apress. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=373589
Gang Gou, & Rada Chirkova. (2007). Efficiently querying large XML data repositories: a survey. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.BD4CFD0F
Garcia-Molina, H., Ullman, J. D., Dawson Books, & Widom, J. (2014). Database Systems: Pearson New International Edition : The Complete Book (Vol. Second edition). Harlow, Essex: Pearson. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1418178
Haq, Q. M. R. U. (2016). Data Mapping for Data Warehouse Design. Amsterdam: Morgan Kaufmann. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1115852
Inderpal Singh Mumick, Sheldon J. Finkelstein, Hamid Pirahesh, & Raghu Ramakrishnan. (1990). Magic is Relevant. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.DDFF5305
Inmon, W. H., Linst, D., & Levins, M. (2019). Data Architecture: A Primer for the Data Scientist : A Primer for the Data Scientist (Vol. Second Edition). London: Academic Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1951596
Inmon, W. H., Neushloss, G., & Strauss, D. (2008). DW 2.0: The Architecture for the Next Generation of Data Warehousing. Amsterdam: Morgan Kaufmann. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=239178
Jack Minker. (1996). Logic and Databases: a 20 Year Retrospective. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.317CDD56
Jensen, C. S., Thomsen, C., & Pedersen, T. B. (2010). Multidimensional Databases and Data Warehousing. [San Rafael, Calif.]: Morgan & Claypool Publishers. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=440363
Jukic, N., Vrbsky, S., & Nestorov, S. (2017). Database Systems : Introduction to Databases and Data Warehouses. Burlington, Virginia: Prospect Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1562389
Kimball, R., & Ross, M. (2013). The Data Warehouse Toolkit : The Definitive Guide to Dimensional Modeling (Vol. 3rd edition). Hoboken, New Jersey: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=605991
Lauri Hella, Leonid Libkin, & Juha Nurmonen. (1997). Notions of Locality and Their Logical Characterizations Over Finite Models. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.2F7E6D58
Libkin, L. (2003). Expressive power of SQL. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.47C7A56F
Linstedt, D., & Olschimke, M. (2015). Building a Scalable Data Warehouse with Data Vault 2.0. Amsterdam: Morgan Kaufmann. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1065504
Melton, J., & Buxton, S. (2006). Querying XML : XQuery, XPath, and SQL/XML in Context. San Francisco, Calif: Morgan Kaufmann. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=230831
Paterson, J. (2006). The Definitive Guide to Db4o. Berkeley, CA: Apress. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=182733
Rad, R. (2016). Mastering Hibernate. Birmingham, UK: Packt Publishing. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1239416
Raghu Ramakrishnan, & Jeffrey D. Ullman. (1993). A Survey of Research on Deductive Database Systems. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.B54AD10B
Sun, A. (2016). Comparison of Java Persistence Layer Technologies. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsndl&AN=edsndl.oai.union.ndltd.org.UPSALLA1.oai.DiVA.org.lnu-57667
The Java Data Object (JDO) [1],[2],[3],[4] standard. (2003). Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.EDFE9217
Thuraisingham, B. M. (2002). XML Databases and the Semantic Web. Boca Raton, FL: CRC Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=154600
Venky Harinarayan, Anand Rajaraman, & Jeffrey D. Ullman. (1996). Implementing Data Cubes Efficiently. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.1C7F82F2

Authors

BREYMAN ALEKSANDR DAVIDOVICH
Butskaia Evgeniia Aleksandrovna
MELIKYAN ALISA VALEREVNA

Course Syllabus