databasemanagementsystempptforbeginners.ppt

©Silberschatz, Korth and Sudarshan
1.1
Database System Concepts
Chapter 1: Introduction
 Database Applications:
 Purpose of Database Systems(FMS Vs DBMS)
 View of Data
 Levels of Abstraction
 Schema and Instance
 Data Models
 Data Definition Language
 Data Manipulation Language
 Database Administrator
 Database Users
 Overall System Structure

1.2
Database Management System (DBMS)
 Collection of interrelated data
 Set of programs to access the data
 DBMS contains information about a particular enterprise
 DBMS provides an environment that is both convenient and
efficient to use.
 Database Applications:
 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
 Databases touch all aspects of our lives

1.3
Purpose of Database System
 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

1.4
Purpose of Database Systems (Cont.)
 Drawbacks of using file systems (cont.)
 Atomicity of updates
 Failures may leave database in an inconsistent state with partial
updates carried out
 E.g. transfer of funds from one account to another should either
complete or not happen at all
 Concurrent access by multiple users
 Concurrent accessed needed for performance
 Uncontrolled concurrent accesses can lead to inconsistencies
– E.g. two people reading a balance and updating it at the same
time
 Security problems: Not every user of the database system should be
able to access all the data.
 Database systems offer solutions to all the above problems

1.5
Data Abstraction(Hiding)
 A major purpose of a database system is to provide users with an
abstract view of the data. That is, the system
hides certain details of how the data are stored and maintained.
 Since many database-system users are not computer trained,
developers hide the complexity from users through several levels
of abstraction, to simplify users’ interactions with the system:

1.6
Levels of Abstraction
 Physical level describes how a record (e.g., customer) is stored.
 Logical level: describes data stored in database, and the
relationships among the data.
type customer = record
name : string;
street : string;
city : integer;
end;
 View level: application programs hide details of data types. Views
can also hide information (e.g., salary) for security purposes.

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 type instructor = record
 ID : char (5);
 name : char (20);
 dept name : char (20);
 salary : numeric (8,2);
 end;

1.8
Levels of Abstraction

1.9
View of Data
An architecture for a database system-3 Level Schema

1.10
Schemas and Instances
 Similar to types and variables in programming languages
 Schema – the logical structure of the database
 e.g., the database consists of information about a set of customers and accounts
and the relationship between them)
 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
 Analogous to the value of a variable

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 Physical Data Independence – the ability to modify the physical schema
without changing the logical schema
 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.
 Logical Data Independence – the ability to modify the logical schema without
changing the view level schema

1.16
View of Data
An architecture for a database system-3 Level Schema

1.17
Data Models
 A collection of tools for describing
 data
 data relationships
 data semantics
 data constraints
 Relational model(We focus in this course)
 Entity-Relationship model
 Other models:
 object-oriented model
 semi-structured data models
 Older models: network model and hierarchical model

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Relational Model
 Example of tabular data in the relational model
customer-
name
Customer-
id
customer-
street
customer-
city
account-
number
Johnson
Smith
Johnson
Jones
Smith
192-83-7465
019-28-3746
192-83-7465
321-12-3123
019-28-3746
Alma
North
Alma
Main
North
Palo Alto
Rye
Palo Alto
Harrison
Rye
A-101
A-215
A-201
A-217
A-201
Attributes

1.23
A Sample Relational Database

1.24
The entity-relationship (E-R) data model uses a
collection of basic objects, called entities, and relationships among
these objects.

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Entity-Relationship Model

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Entity-Relationship Model
Example of schema in the entity-relationship model

1.29
Entity Relationship Model (Cont.)
 E-R model of real world
 Entities (objects)
 E.g. customers, accounts, bank branch
 Relationships between entities
 E.g. Account A-101 is held by customer Johnson
 Relationship set depositor associates customers with accounts
 Widely used for database design
 Database design in E-R model usually converted to design in the
relational model (coming up next) which is used for storage and
processing

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Data Definition Language (DDL)
 Specification notation for defining the database schema
 E.g.
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)
 database schema
 Data storage and definition language
 language in which the storage structure and access methods
used by the database system are specified
 Usually an extension of the data definition language

1.38
MySQL CREATE TABLE Statement
 The MySQL CREATE TABLE Statement
 The CREATE TABLE statement is used to create a new table in
a database.
 Syntax
 CREATE TABLE table_name (
column1 datatype,
column2 datatype,
column3 datatype,
....
);

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MySQL CREATE DATABASE Statement
 The CREATE DATABASE statement is used to create a new SQL
database.
Syntax
CREATE DATABASE databasename;
Example
 CREATE DATABASE testDB;
 Once a database is created, you can check it in the list of
databases with the following SQL command:
 SHOW DATABASES;

1.42
The MySQL DROP DATABASE
 The DROP DATABASE statement is used to drop an existing
SQL database.
 Syntax
 DROP DATABASE databasename;
 Note: Be careful before dropping a database. Deleting a
database will result in loss of complete information stored in the
database!
 Example
 DROP DATABASE testDB;

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 Syntax
 CREATE TABLE table_name (
column1 datatype (length),
);
 Example:see document

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DROP COLUMN
 The DROP COLUMN command is used to delete a column in an
existing table.
 The following SQL deletes the "ContactName" column from the
"Customers" table:
 Example
 ALTER TABLE Customers
DROP COLUMN ContactName;

1.49
 ALTER TABLE - MODIFY COLUMN
 To change the data type of a column in a table, use the following
syntax:
 ALTER TABLE table_name
MODIFY COLUMN column_name datatype;

1.50
 Change Data Type Example
 Now we want to change the data type of the column named
"DateOfBirth" in the "Persons" table.
 We use the following SQL statement:
 Example
 ALTER TABLE Persons
MODIFY COLUMN DateOfBirth year;
 Notice that the "DateOfBirth" column is now of type year and is
going to hold a year in a two- or four-digit format.

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DML

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 The SQL SELECT Statement
 The SELECT statement is used to select data from a database.
 The data returned is stored in a result table, called the result-set.
 SELECT Syntax
 SELECT column1, column2, ...
FROM table_name;
 Here, column1, column2, ... are the field names of the table you
want to select data from.

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 If you want to select all the fields available in the table, use the
following syntax:
 SELECT * FROM table_name;

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 MySQL INSERT INTO Statement
 ❮ PreviousNext ❯

INSERT INTO table_name (column1, column2, column3, ...)
VALUES (value1, value2, value3, ...);

1.66
Data Manipulation Language (DML)
 Language for accessing and manipulating the data organized by
the appropriate data model
 DML also known as query language
 Two classes of languages
 Procedural – user specifies what data is required and how to get
those data
 Nonprocedural – user specifies what data is required without
specifying how to get those data
 SQL is the most widely used query language

1.67
SQL
 SQL: widely used non-procedural language
 E.g. 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’
 E.g. 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 to allow embedded SQL
 Application program interface (e.g. ODBC/JDBC) which allow SQL
queries to be sent to a database

1.68
Database 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
 E.g. 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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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.

1.78
Storage Management
 Storage manager is a program module that provides the
interface between the low-level data stored in the database and
the application programs and queries submitted to the system.
 The storage manager is responsible to the following tasks:
 interaction with the file manager
 efficient storing, retrieving and updating of data

1.79
Overall System Structure

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Application Architectures
Two-tier architecture: E.g. client programs using ODBC/JDBC to
communicate with a database
Three-tier architecture: E.g. web-based applications, and
applications built using “middleware”

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Database Design and E-R Model
1. What are the steps in designing a database?
2. Why is the ER model used to create an initial
design?
3. What are the main concepts in the ER model?
4. What are guidelines for using the ER model
effectively?

1.89
 The (Entity Relationship ER) data model allows us to describe
the data involved in a real-world enterprise in terms of objects
and their relationships and is widely used to (develop an initial
database design.

1.90
ENTITIES, ATTRIBUTES, AND ENTITY
SETS
 The entity-relationship (E-R) data model uses a collection of basic
objects, called entities, and relationships among these objects.
 An entity is a “thing” or “object” in the real world that is
distinguishable from other objects.
 For example, each person is an entity, and bank accounts can be
considered as entities.

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Attributes.
 Entities are described in a database by a set of attributes.

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Attributes.

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For each attribute, there is a set of permitted values, called the
domain, or value
set, of that attribute.
 Simple and composite attributes.
 Single-valued and multivalued attributes.
 Derived attribute.

1.97
1.Can be divided into subparts(Ex:Name-
>(fname,mname,lname)

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 For example, an attribute name could be structured as a
composite attribute consisting of first name, middle initial, and
last name.

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 Derived attribute. The value for this type of attribute can be
derived from the values of other related attributes or entities.
 Ex:age,total,avg,netpay…

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 An attribute takes a null value when an entity does not have a
value for it.
 i.e.. attribute value may be not applicable or unknown

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Relationship Sets
 A relationship is an association among several entities. A
relationship set is a set of relationships of the same type.

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 An entity set is represented by a rectangle, and an attribute is
represented by an oval/ellipse.
 Each attribute in the primary key is underlined.

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 A key is a minimal set of attributes whose values uniquely
identify an entity in the set.

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Constraints
 Mapping Cardinalities
 Participation Constraints

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Mapping cardinalities

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Participation Constraints
 Total Participation
 Partial Participation

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Entity-Relationship Diagrams
 an E-R diagram can express the overall logical structure of a
database graphically. E-R diagrams are simple and clear.
 Basic Structure
 An E-R diagram consists of the following major components:
 Rectangles divided into two parts represent entity sets. The
first part, contains the name of the entity set.
 The second part contains the names of all the attributes of the
entity set.
 Diamonds represent relationship sets.
 Undivided rectangles represent the attributes of a relationship
set.
 Attributes that are part of the primary key are underlined.

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 Lines link entity sets to relationship sets.
 Dashed lines link attributes of a relationship set to the
relationship set.
 Double lines indicate total participation of an entity in a
relationship set.
 Double diamonds represent identifying relationship sets linked
to weak entity sets

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Weak Entity Sets

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E-R diagram for the University Enterprise

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E-R diagram for the University Enterprise

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Design issues
 Use of Entity Sets versus Attributes
 Use of Entity Sets versus Relationship Sets
 Binary versus n-ary Relationship Sets
 Placement of Relationship Attributes

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Design issues
 Use of Entity Sets versus Attributes

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Design issues
 Use of Entity Sets versus Relationship Sets

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 Binary versus n-ary Relationship Sets:
 Relationships in databases are often binary. Some relationships
that appear to be nonbinary could actually be better represented
by several binary relationships.

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 Placement of Relationship Attributes

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Extended E-R Features
 Specialization
 Generalization
 Aggregation

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Specialization
 An entity set may include subgroupings of entities that are
distinct in some way from other entities in the set.
 For instance, a subset of entities within an entity set may have
attributes that are not shared by all the entities in the entity set.
 design process proceed in a top-down manner

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belong to multiple specialized entity sets
 overlapping specialization
 disjoint specialization
 The specialization relationship may also be referred to as a
superclass-subclass relationship.

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Generalization
 design process may proceed in a bottom-up manner

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 Total generalization or specialization. Each higher-level entity
must belong to a lower-level entity set.
 Partial generalization or specialization. Some higher-level
entities may not belong to any lower-level entity set.

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Aggregation
 One limitation of the E-R model is that it cannot express
relationships among relationships.
 To illustrate the need for such a construct, consider the ternary
relationship proj guide, which we saw earlier, between an instructor,
student and project

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Alternative E-R Notations

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