DB and DBMS
Adapted from Silberschatz, Korth and Sudarshan
Database System Concepts, 5th Ed.
©Silberschatz, Korth and Sudarshan
See www.db-book.com for conditions on re-use
Summary
 What is a Database (DB)?
 Data Models
 DB Schemas and Instances
 Database Management System (DBMS)
 DB Design
 Centralized DBMS Architecture
 DBMS Users and Administrators
 Advanced DBMS Architectures
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What is a Database (DB)?
 A very large, integrated collection of data
 Models real-world enterprise

Set of Entities (e.g., Student, Course)

Relationships (e.g., Student is Taking Course)

Associations (e.g., Madonna is Taking CS564)
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(Logical) Data Models
 A collection of tools, at a high abstraction level, for describing



Data manipulation
 Data definition, data updating, data querying
Data relationships
Data constraints
 Examples of data models

Entity-Relationship (ER)

Relational

Object-based (Object-oriented and Object-relational)

Semistructured (XML)

Other older models:
 Network model
 Hierarchical model
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ER Model
 Models an enterprise as a collection of entities and relationships

Entity: a “thing” or “object” in the enterprise that is distinguishable
from other objects


Described by a set of attributes
Relationship: an association among several entities
 Represented diagrammatically by an entity-relationship diagram:
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ER Model (Cont.)
 The ER model is static

It does not support operations and data querying
 Other weakness

Atomic attributes
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Relational Model
Attributes
 Example of tabular data in the relational model
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A Sample Relational Database
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Relational Model
 Weaknesses

Atomic columns

Does not explicitly support relationships
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Relational Data Manipulation Language (DML)
 Language for defining, updating and querying the data organized as
relational tables
 SQL is the most widely used DML language

Data Definition Language (DDL)

Data Updating Language

Data Query Language

Declarative: user specifies what data is required without
specifying how to get those data
– Select … From … Where … paradigm

Procedural Language

User specifies how (control) to get data
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SQL DDL
 Specification notation for defining the database
Example:


create table account (
account-number primary key char(13),
balance real)
Data constraints

Domain constraints (char, real)

Key integrity (primary key)

Referential integrity (references)

Assertions check (balance > 0.0)
Authorization
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SQL DDL: Assertion Example

 Every loan has at least one borrower who maintains an account with a
minimum balance or $1000.00
create assertion balance_constraint check
(not exists (
select *
from loan
where not exists (
select *
from borrower, depositor, account
where loan.loan_number = borrower.loan_number
and borrower.customer_name = depositor.customer_name
and depositor.account_number = account.account_number
and account.balance >= 1000)))
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SQL DDL: Authorization
 Forms of authorization on parts of the database:
 Read - allows reading, but not modification of data.
 Insert - allows insertion of new data, but not modification of existing data.
 Update - allows modification, but not deletion of data.
 Delete - allows deletion of data.
Forms of authorization to modify the database schema (covered in Chapter 8):
 Index - allows creation and deletion of indices.
 Resources - allows creation of new relations.
 Alteration - allows addition or deletion of attributes in a relation.
 Drop - allows deletion of relations.
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SQL Data Updating Language
 Insert

insert Into account values (‘1951-150737-7’, 2500.00)
 Update

update account
set balance = 2600.00
where account-number = ‘1951-150737-7’
 Delete

delete from account
where account-number = ‘1951-150737-7’
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SQL Query Language
 Examples

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’

Find the balances of all accounts held by the customer with customer-id
192-83-7465
select account.balance
from
depositor, account
where depositor.customer_id = ‘192-83-7465’ and
depositor.account_number = account.account_number
 Application programs generally access databases through one of

Language extensions – host languages -- to allow embedded SQL

SQL procedural languages

Application program interface (e.g., ODBC/JDBC) which allow SQL
queries to be sent to a database
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SQL Procedural Languages
 MS Transact SQL
 Oracle PL/SQL
 Standard?
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Procedural Constructs
 For loop


Permits iteration over all results of a query

Example: find total of all balances at the Perryridge branch
declare bal real default 0.0;
for r as
select balance from account
where branch_name = ‘Perryridge’
do
set bal = bal + r.balance
end for
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Object Model
 ODMG standard

ODL: Object Definition Language

Persistent classes
– Class attributes
»
Non-atomic attributes
– Class relationships
– Class methods
– Class constraints
– Class repositories

OQL: Object Query Language

Object querying

Declarative
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Object-Relational (OR) Model
Object Model




Extend the relational data model by
including object orientation and
constructs to deal with added data
types
Allow attributes of tuples to have
complex types, including nonatomic values such as nested
relations
Preserve relational foundations, in
particular the declarative access to
data, while extending modeling
power
Provide upward compatibility with
existing relational languages
OR Model
Class
Type
Class repository
Object table
Class
relationships
Type references
Class attributes
Type attributes
Non-atomic
attributes: set,
bag, list and array
Non-atomic
attributes: array,
nested table
(Oracle)
OQL
Extended SQL
query language
Extended SQL
DDL and Updating
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OR Model: Non-1NF Relation
 Example: library information system
 Each book has

title,

a set of authors,

Publisher, and

a set of keywords
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OR Model: Structured Types and Inheritance

 Structured types can be declared and used in SQL
create type Name as
(firstname
varchar(20),
lastname
varchar(20))
final
create type Address as
(street
varchar(20),
city
varchar(20),
zipcode
varchar(20))
not final



Note: final and not final indicate whether subtypes can be created
Structured types can be used to create tables with composite attributes
create table customer (
name
Name,
address Address,
dateOfBirth date)
Dot notation used to reference components: name.firstname
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OR Model: Structured Types (cont.)

create type CustomerType as (
name Name,
address Address,
dateOfBirth date,
<instance_methods)>
)
not final
 Can then create a table whose rows are a user-defined type
create table customer of CustomerType
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OR Model: Methods
 Can add a method declaration with a structured type
method ageOnDate (onDate date)
returns integer
 Method body is given separately
create instance method ageOnDate (onDate date)
returns integer
for CustomerType
begin
return onDate - self.dateOfBirth;
end
 We can now find the age of each customer:
select name.lastname, ageOnDate (current_date)
from customer
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OR Model: Inheritance
 Suppose that we have the following type definition for people

create type Person
(name varchar(20),
address varchar(20))
[not final]
 Using inheritance to define the student and teacher types
create type Student
under Person
(degree
varchar(20),
department varchar(20))
create type Teacher
under Person
(salary
integer,
department varchar(20))
 Subtypes can redefine methods by using overriding method in place of
method in the method declaration
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OR Model: Array and Multiset Types

Example of array and multiset declaration:
create type Publisher as
(name
varchar(20),
branch
varchar(20))
create type Book as
(title
varchar(20),
author-array varchar(20) array [10],
pub-date
date,
publisher
Publisher,
keyword-set varchar(20) multiset )
create table books of Book
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OR Model: Querying Collection-Valued Attributes
 To find all books that have the word “database” as a keyword
select title
from books
where ‘database’ in (unnest(keyword-set ))
 We can access individual elements of an array by using indices
 E.g.: If we know that a particular book has three authors, we could write
select author-array[1], author-array[2], author-array[3]
from books
where title = `Database System Concepts’
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Comparison of O-O and O-R Databases
 Relational systems

simple data types, powerful query languages, high protection
 Persistent-programming-language-based OODBs

complex data types, integration with programming language, high
performance
 Object-relational systems

complex data types, powerful query and procedural languages, high
protection

Performance?

It depends on the DBMS Administrator
 Note: Many real systems blur these boundaries

E.g. persistent programming language built as a wrapper on a
relational database offers first two benefits, but may have poor
performance
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XML: Extensible Markup Language
 Defined by the WWW Consortium (W3C)
 Originally intended as a document markup language not a
database language
 The ability to specify new tags, and to create nested tag structures
made XML a great way to exchange data, not just documents
 XML has become the basis for all new generation data interchange
formats.
 A wide variety of tools is available for parsing, browsing and
querying XML documents/data
 Example of XML DBMS

Tamino
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Schemas and Instances




Schema – the structure of the database at a certain abstraction level
Types of schema
 Logical schema: database design according to an underlying logical data
model
 Example of an ER schema: the database consists of information about an
entity set customer and another entity set account and the relationship
between them
– Other types of schema: relational schema, object schema, OR schema
» Relational and OR schemas: SQL DDL
 Physical schema: database design at the physical level
 Example: the set of customers is an indexed-sequential data file
Instance – the actual content of the database at a particular point in time
Physical Data Independence – the ability to modify the physical schema without
changing the logical schema
 A fundamental requirement for database management systems
 Applications depend on the logical schema
 In general, the interfaces between the various levels and components should
be well defined so that changes in some parts do not seriously influence others
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Database Management System (DBMS)
 DBMS is a software that supports

Database

Set of programs to access the database

An environment that is both convenient and efficient to use
 Benefits of using DBMS

No data redundancy


Make data access easy


No duplication of information in different files
No need to write a new program to carry out each new task
It becomes easy to guarantee integrity constraints

Integrity constraints (e.g. account balance > 0) become
“buried” in program code rather than being stated explicitly

Soft to add new constraints or change existing ones
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DBMS (Cont.)

Support for the Transaction concept

Atomicity of updates
– Failures do not leave database in an inconsistent state since
that partial updates are not carried out
– Example: Transfer of funds from one account to another should
either complete or not happen at all
Controlled concurrent access by multiple users
– Uncontrolled concurrent accesses can lead to inconsistencies
» Example: Two people reading a balance and updating it at
the same time
 Support for Security

Soft to provide user access control to all data
 Access Efficiency
 Query optimization

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DBMS (Cont.)
 Families of DBMSs

Relational DBMSs


MS SQL Server 2000 (?), Oracle 7
Object-relational DBMSs

Oracle 8-10, IBM DB/2
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Database Design
The process of designing the general structure of the database




Conceptual Design – Deciding on the database schema at a higher abstraction level than
relational or object-relational schemas
 ER schema, Object schema
Logical Design – Deciding on the logical database schema implemented by DBMSs
 R schema, OR schema
Physical Design – Deciding on the physical layout of the R(OR) database
Mappings
 Conceptual schema  logical schema
 Case tools
 Manual task
 Logical schema  physical schema
 DBMS
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Database Design (Cont.)
OO Database Design
R Database Design
Object schema
ER schema
OR schema
R schema
Physical OR schema
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Centralized DBMS Architecture
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Query Processing
1. Parsing and translation
2. Optimization
3. Evaluation
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Query Processing (Cont.)
 Alternative ways of evaluating a given query

Equivalent expressions

Different algorithms for each operation
 Cost difference between a good and a bad way of evaluating a query can
be enormous
 Need to estimate the cost of operations

Depends critically on statistical information about relations which the
database must maintain

Need to estimate statistics for intermediate results to compute cost of
complex expressions
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Transaction Management
 A transaction is a collection of operations that performs a single
logical function in a database application
 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

Concurrency-control manager controls the interaction among
the concurrent transactions, to ensure the consistency of the
database

Recovery manager assures atomicity of updates
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DBMS Users
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
 Specialized users – write specialized database applications that do
not fit into the traditional data processing framework
 Naïve users – invoke one of the permanent application programs that
have been written previously

Examples, people accessing database over the web, bank tellers,
clerical staff
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Database Administrator
 Coordinates all the activities of the database system; the
database administrator has a good understanding of the
enterprise’s information resources and needs
 Database administrator's 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 and responding to changes in
requirements
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Advanced DBMS Architectures
 Client-server

Two-tier

Three-tier
 Parallel (multi-processor)
 Distributed
 Data Grid
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DBMS Architectures (Cont.)
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