Kszlt a HEFOP3'3'1P'20040600181'0 projekt keretben

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Készült a HEFOP-3.3.1-P.-2004-06-0018/1.0 projekt
keretében
A szakirány neve

• DATABASE MANAGEMENT SYSTEMS

Modul 1 1.1 Introduction (1 lecture)
Az Európai Szociális Alap támogatásával
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Outline

• What is a DBMS
• -properties
• -users
• -history
• - File Management System versus DBMS
• - DBMS overall structure
• What is Data Modelling
• -notion
• -model classification
• -modern and historical models and examples
• Data abstraction levels, examples

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• DBMS
• Aim
• Averall (simplified, abstract) view
• Basic notions
• Words

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• Notion of a Database
• What is data?
• What is information?
• What is a Database?
• DBMSDataBaseManagementSystem

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• Properties
• 1. DATA DESCRIPTION, NEW DATABASE
• New database can be constructed
• Logical structure of data can be described
• Data Definition Language DDL

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• 2. GETTING DATA FROM THE DATABASE
• Data can be get back through queries efficiently
• Query Language
• Data can be modified easily
• Data Manipulation Language (DML)

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• 3. STORING DATA
• Huge amount of data must be safely stored
• Safe storage
• it must be defended against unauthorized
  users Grants
• - it must be defended against failors
• DBMS Recovery Systems

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• 4. MULTIUSER ENVIRONMENT
• Concurrent usage
• Transaction Management
• Concurrency Control

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• Data(base) models

abstraction

WORLD
DATA MODEL
Data models serve for describing the structure
of the database. In a data model we do
not care with the concret values of a data,
rather only the relationships among these
data. Many database can satisfy a given database
model. The structured data, with the given
values, satisfying the database model is called
the database instance.

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Data abstraction levels
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Abstraction levels

• I. View level
• What a user can see from the database not the
  whole model can be seen ( subschemas - SDDL)
• - what particular relationships are required by
  users?
• -more abstract because partial - typically very
  high-level knowledge
• constitutes the view
• II. Logical/Conceptual level
• The complete database model (schema - DDL)
• - what meaningful relationships are expressed by
  the physical data?
• - entities, and relationships between entities
• III. Physical level
• Storage and access methods, files, indeces, other
  storing structures
• -how is the data actually represented in the
  hardware?
• -bits, bytes

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• Data independence
• logical logical level can be modified without
  modifying physical level
• physical physical level can be modified without
  modifying logical level

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• Example Consider an n x m array.
• Physical level
• m x n (consecutive ) memory location
• Logical level

View level 2(m x n) possible view
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• Model logical level schema
• type tgridarray1..2, 1..3 of integer
• var vgrid1, vgrid2tgrid
• An instance

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• ? Object based models
• Entity/Relationship diagram (graphycal standard)
• Objectumoriented model, ODL (C like standard
  for describing data structures)
• Unified Model Language (UML)

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• Record based models
• Relational model
• Constraint Model
• Network model (historical)
• Hierarchical model (historical)

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• History by topic
• Examples
• Banking systems
• (Airlines) Seat reservation systems
• Company Administration

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• Banking systems
• User Programs
• -accounts-deposits, withdraws
• -new accounts
• -balance
• -monthly reports
• Data items customers(name, address,
  account-no)accounts(account-no, balance,
  type)Type could be savings or checking

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(Airlines) Seat reservation systems

• Data items
• customers(name, address, phone, flight-number)
• flights(flight-number, departure, arrival,
  airport)
• seats(flight-number,seat-id., name)

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Company administration

• sells, bills (in-out)
• - what could be the data items?

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File management systems

• Files could have different structures
  (sequential, ..)- New questions new programs
• Data could be stored in different storage places
  which make writing new programs difficoult
• Constraints can be hardly checked
• - Atomicity level is the whole file
• - Concurrency is almost impossible
• Cont

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File management systems

• Safety can not be guaranteed
• Abstraction level is law-the programmer should
  know the physical level for writing new programs

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History by models

• First DBMS
• - network model (graph)
• - hierarchical model (tree)
• - relational model (Codd, 1970)

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Who use DBMS?

• Administrator
• Tasks
• - logical schema modification
• - logical schema definiton
• - physical schema modification
• - constraints definitions
• - constraints modifications
• - authorization
• - routine maintenance

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Who use DBMS?

• Other users
• -programmers
• -naive users
• -sophisticated users

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DBMS STRUCTURE

• Schema definition

• Storage manager (program)- authorization and
  integrity manager
• file-manager
• buffer manager

Query processing (progams)- DDL / DML
interpreter / compiler - DML precompiler
Query evaluation-optimization
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DBMS STRUCTURE

• Transaction manager (program)
• Controls the correct concurrent running
• Atomicity all-or-none
• Consistency correctness
• Isolation if I were alone..
• Tools locking, validation, time-stamping
• Durability ..forever? Tools
  journal-files, mirroring..

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DBMS STRUCTURE

• Physical storage (device)
• real data (the pure database)
• metadata indeces statistical data
• data dictionary-records data structures

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DBMS STRUCTURE

• Klient - server architectures
• - 2 triers
• - 3 tiers

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• DBMS simplifyied structure

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Slide from Silberschatz-Korth-Sudarsan DATABASE
SYSTEMS CONCEPTS http//db-book.com/, 1.26
slide, completion by BNÁ
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Other directions (will be partly covered)

• Object oriented database systems
• -Active elements - constraints - triggers
• Multimedia databases
• Data Warehouse