Budapest University of Technology and Economics, Faculty of Electrical Engineering and Informatics

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    Database Management

    A tantárgy neve magyarul / Name of the subject in Hungarian: Adatbáziskezelés

    Last updated: 2021. szeptember 1.

    Budapest University of Technology and Economics
    Faculty of Electrical Engineering and Informatics

    Faculty of Natural Sciences

    Mathematics BSc

    Applied Specialization  
    Course ID Semester Assessment Credit Tantárgyfélév
    VISZA027   2/2/0/v 4 5
    3. Course coordinator and department Dr. Gajdos Sándor,
    Web page of the course https://www.db.bme.hu/Adatbaziskezeles/
    4. Instructors

    Dr. Sándor Gajdos,

    associate professor

    Department of Telecommunications and Media Informatics

    Dr.  Levente Erős

    assistant professor

    Department of Telecommunications and Media Informatics

    5. Required knowledge Basic programming skills; general awareness programming languages; data structures, basic knowledge of algorithms.
    6. Pre-requisites
    Kötelező:
    NEM
    (TárgyEredmény( "BMEVITMAB00" , "jegy" , _ ) >= 2
    VAGY
    TárgyEredmény("BMEVITMAB00", "FELVETEL", AktualisFelev()) > 0
    VAGY
    TárgyEredmény( "BMEVITMA027" , "jegy" , _ ) >= 2
    VAGY
    TárgyEredmény("BMEVITMA027", "FELVETEL", AktualisFelev()) > 0
    VAGY
    TárgyEredmény( "BMEVITMA027" , "aláírás" , _ ) = -1)

    A fenti forma a Neptun sajátja, ezen technikai okokból nem változtattunk.

    A kötelező előtanulmányi rend az adott szak honlapján és képzési programjában található.

    Ajánlott:

    Combinatorics and graph theory (BMEVISZA025)

    Theory of  Algorithms (BMEVISZAB01)

     Not intended for students of Software Engineering

    7. Objectives, learning outcomes and obtained knowledge Basic knowledge about the use, operation and creation of database management systems. How to apply these in practice.
    8. Synopsis
    1. Database Management Systems, expectations on the system, parts of the system. The history of database management systems, database management systems incidence levels.

    2. Data Modeling Concepts, E/R diagrams, Data Modeling Concepts, entities, attributes, specifying relationships, E/R link types, changing multiple connections to binary, subclasses, constraints.

    3. Relational data model, relational algebra operations, derivative transactions, E/R conversion to relational schema.

    4. Tuple relational and domain relational calculus, examples safe expressions.

    5. SQL basic concepts, statements, DML, DDL, nested queries, examples.

    6. Using MySQL

    7. Functional dependence, logical consequences, Armstrong axioms. Closure, truth and completeness theorem.

    8. Key, key algorithms in the closure, decomposition and faithful decomposition, BCNF, normalization, dependency preserving decomposition.

    9. 3NF, decmposition to 3NF. Implementation of queries, physical design, optimization of queries.

    10. Physical organization: basic concepts, sequential organization, hash, dynamic hash, increasing hash, indexing concepts, sparse and dense index.

    11. Transaction Management Concepts: Concept of transactions, atomicity, isolation, consistency, durability. Multi-user operation: serial, serializability, serializability with locks.

    12. serializability testing in simple transaction model with serialization graph; Serialization graph, 2PL. RLOCK / WLOCK model: lock types and thier use, problems with locks, two  methods to test serializability.


    13. System errors:  logging, recovery, UNDO, REDO protocol UNDO / REDO protocol archiving.

    14. Non-relational databases.
    9. Method of instruction lectures and practice sessions
    10. Assessment

    Midterm during the semester.

    Final: written and oral. 

     

    11. Recaps One midterm retake during the semester.
    13. References, textbooks and resources

    Ullman, Widom: A First Course in Database Systems   (2014)  Pearson

    Garcia-Molina, Ullman, Widom: Database systems: The complete book (2009) Prentice Hall

    14. Required learning hours and assignment
    In class 56
    Preparation for classes 30
    Preparation for midterm 10
    Homework 
    Reading assignment 
    Preparation for final 24
    Total 120
    15. Syllabus prepared by

    Dr. Gyula Katona,

    associate professor

    Department of Computer Science and Information Theory

    Dr.  Judit Csima

    associate professor

    Department of Computer Science and Information Theory