Download Data Models

Administração e Optimização
de Bases de Dados
 Enquadramento
 Programa
 Bibliografia
 Planeamento
teóricas e laboratórios
 Avaliação
 Corpo
AOBD07/08
docente
Enquadramento
Cadeiras de gestão de dados e tratamento
de informação DEI 2007/08 :
 BD (3º ano LEIC e LERCI)
 GTI (1º ano MEIC/SIE)
 SAD (1º ano MEIC e MERC)
 AOBD (1º ano MEIC/TSI e MERC)
AOBD07/08
Bibliografia

Database System Concepts, Silberchatz, Korth,
Sudarshan 5ª edição, McGraw Hill, 2005
 Database Management Systems, Raghu
Ramakrishnan, Johannes Gehrke 3ª edição, Mc
Graw Hill, 2002
 Database Tuning: Principles, Experiments, and
Troubleshooting Techniques, Dennis Shasha &
Philippe Bonnet, Morgan Kaufmann, 2003.
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Programa (1)
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Armazenamento e Sistema de Ficheiros: cap 11
(Silb), 9 (Raghu)
Técnicas de indexação (B+tree e hash-based) – cap
12 (Silb), 10 e 11 (Raghu)
Processamento de interrogações – cap 13(Silb), 12 e
13 (Raghu),
Optimização de interrogações – cap 14 (Silb), 15
(Raghu)
Gestão de Transações – cap 15 (Silb), 16 (Raghu)
Controlo de Concorrência – cap 16(Silb), 17 (Raghu)
Gestão de Recuperação – cap 17(Silb), 18 (Raghu)
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Programa (2)
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Principios de tuning
Lock tuning
Log tuning
Storage tuning
OS tuning
Index tuning
Query processing tuning
API tuning
(Shasha & Bonnet e alguns capítulos do Raghu e/ou
Silberchatz)
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Planeamento
 Aulas
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Matéria (slides baseados no livro e artigos)
 Aulas
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teóricas: 1H30
laboratóro: 1H30
SQLServer 2005
Material de apoio adicional: livros on-line e
guias de laboratório
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Avaliação
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Exame (52%):
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Nota mínima: 9,5v
Mini-projectos (48%):
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Grupos de 3 pessoas
Exercícios “de papel e lápis” e/ou com SQLServer
2005.
Nota mínima: 9,5v
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Corpo docente
 Helena
Galhardas (responsável)
 Pável Calado
 Bruno
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Martins (laboratórios)
Chapter 1: Introduction
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Purpose of database systems
Data abstraction levels
Data models
SQL :Data Definition Language and Data
Manipulation Language
Transaction management
Database users
DBMS structure
Typical database architectures
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Database management systems
(DBMS)

Collection of interrelated data and a set of programs
to access the data
 DBMS contains relevant information about a
particular enterprise
 DBMS provides an environment that is both
convenient and efficient to use.
 Database applications:
•
•
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•
Banking: all transactions
Airlines: reservations, schedules
Universities: registration, grades
Sales: customers, products, purchases
Manufacturing: production, inventory, orders, supply chain
Human resources: employee records, salaries, tax deductions
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DBMS vs File Systems (1)
 In
the early days, database applications were
built on top of file systems
 Drawbacks of using file systems to store data:
Data redundancy and inconsistency: Multiple file
formats, duplication of information in different files
 Difficulty in accessing data: Need to write a new
program to carry out each new task
 Data isolation: Multiple files and formats
 Integrity problems: Integrity constraints (e.g.
account balance > 0) become part of program
code; Hard to add new constraints or change
existing ones
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DBMS vs File Systems (2)
 Drawbacks

of using file systems (cont.)
Atomicity of updates
• Failures may leave database in an inconsistent
state with partial updates carried out
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E.g. transfer of funds from one account to another
should either complete or not happen at all
Concurrent access by multiple users
• Concurrent access needed for performance
• Uncontrolled concurrent accesses can lead to
inconsistencies
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E.g. two people reading a balance and updating it at the
same time
Security problems
…. DBMS offer solutions to all the above
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problems!
Why use a DBMS?
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Data independence and efficient access
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Reduced application development time.
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Data integrity and security.
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Uniform data administration.
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Concurrent access, recovery from crashes.
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Levels of data abstraction (1)
Physical level: describes how data are
stored.
Logical level: describes data stored in the
database, and the relationships among the
data.
View level: application programs hide details
of data types. Views can also hide
information (e.g., salary) for security
purposes.
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Levels of data abstraction (2)
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Data Models
 A collection
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of conceptual tools for describing:
data
data relationships
data semantics
data constraints
Ex:
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Entity-Relationship model, UML class diagram
Relational model
Other models:
• semi-structured data models (XML used to represent sstr.
data)
• older models: network model and hierarchical model
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Entity-Relationship Model
Example of schema in the entity-relationship
model
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A Sample Relational Database
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Data Independence
 Applications
insulated from how data is
structured and stored.
Logical data independence: Protection from
changes in the logical structure of data.
CustomerPublic(customer-id, customer-name)
CustomerPrivate(customer-id, salary)
Physical data independence: Protection from
changes in the physical structure of data.
* One of the most important benefits of using a DBMS!
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Instances and Schemas
Schema: the logical structure of the database, a
description of a particular collection of data, using
a given data model
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Analogous to type information of a variable in a
program
Physical schema: database design at the physical level
Logical schema: database design at the logical level
Instance: the actual content of the database at a
particular point in time
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Analogous to the value of a variable
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Example
External schema (View):
CustomerPublic (customer-id, customer-name)
Logical schema:
Customer(customer-id, customer-name, customer-street,
customer-age)
Account(account-number, balance)
Depositor(account-number, customer-id)
Physical schema:
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Relations stored as unordered files.
Index on first column of Customer.
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SQL: Structured Query Language
 A DBMS
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provides:
a Data Definition Language (DDL)
a Data Manipulation Language (DML)
as part of a single DB language: SQL
 Most
widely used declarative query language
• Procedural – user specifies what data is required and
how to get those data
• Declarative – user specifies what data is required
without specifying how to get those data
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SQL: Data Definition Language
(DDL)
 DDL:
Specification notation for defining the
database
• Ex:
create table account( account-number char(10),
balance
integer)
 DDL compiler
generates a set of tables stored
in a data dictionary
 Data dictionary contains metadata (i.e., data
about data)
Ex: Database schema, consistency constraints,
access methods
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SQL: Data Manipulation
Language (DML)
 Language
for accessing and manipulating
data
 Ex: find the name of the customer with
customer-id 192-83-7465
select customer.customer-name
from customer
where customer.customer-id = ‘192-83-7465’
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Transaction Management
 A transaction
is a collection of operations that
performs a single logical function in a
database application
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Ex: funds transfer includes withdraw from account
A and deposit into account B
 Transaction
management component ensures
that the database remains in a consistent
(correct) state despite system failures (e.g.,
power failures and operating system crashes)
and transaction failures.
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Database Users (1)
 Users
are differentiated by the way they
expect to interact with the system
Application programmers: interact with system
through DML calls
Sophisticated users: form requests in a
database query language
Naïve/End users: invoke one of the permanent
application programs that have been written
previously
• E.g. people accessing database over the web,
bank tellers, clerical staff
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Database Users (2)
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Database administrators Coordinates all the activities
of the database system; has a good understanding of
the enterprise’s information resources and needs.
Duties include:
• Schema definition
• Storage structure and access method definition
• Schema and physical organization modification
• Granting user authority to access the database
• Specifying integrity constraints
• Acting as liaison with users
• Monitoring performance, tuning the system and responding
to changes in requirements
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Overall DBMS Structure
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Database Tuning
Database Tuning is the activity of making
a database application run more quickly.
“More quickly” usually means higher
throughput, though it may mean lower
response time for time-critical applications.
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Application
Programmer
(e.g., business analyst,
Data architect)
Application
Sophisticated
Application
Programmer
Query Processor
(e.g., SAP admin)
Indexes
Storage Subsystem
Concurrency Control
Recovery
DBA,
Tuner
Operating System
Hardware
[Processor(s), Disk(s), Memory]
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Next lecture
 Ch
AOBD07/08
11: Storage and File Structure