LECTURE -1
DATABASE MANAGEMENT SYSTEMS
14 AUGUST 2020
TEXT BOOK : DATABASE SYSTEM CONCEPTS,SILBERCSHATZ,KORTH, SUDERSHAN. MC GRAW HILL,5/E
INTRODUCTION
❑ Good decisions require good information derived from
raw facts
❑ Data managed most efficiently when stored in a database
❑ Databases evolved from computer file systems
❑ Understanding file system characteristics is important
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DATA VS. INFORMATION
❑ Data are raw facts
❑ Information is the result of processing raw data to reveal
meaning
❑ Information requires context to reveal meaning
❑ Raw data must be formatted for storage, processing, and
presentation
❑ Data are the foundation of information, which is the
bedrock of knowledge
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DATA VS. INFORMATION (CONTINUED)
❑ Data: building blocks of information
❑ Information produced by processing data
❑ Information used to reveal meaning in data
❑ Accurate, relevant, timely information is the key to good
decision making
❑ Good decision making is the key to organizational
survival
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DATABASE MANAGEMENT SYSTEM
❑ Database: shared, integrated computer structure that stores a
collection of data
❖ End-user data: raw facts of interest to the end user
❖ Metadata: data about data
❑ Metadata provides description of data characteristics and
relationships in data
❖ Complements and expands value of data
❑ Database management system (DBMS): collection of programs
❖ Manage structure and control access to data
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ROLE OF DBMS
❑ DBMS is the intermediary between the user and the
database
❑ Database structure stored as file collection
❑ Access database through the DBMS
❑ DBMS enables data to be shared
❑ DBMS integrates many users’ views of the data
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DATABASE MANAGEMENT SYSTEM (DBMS)
❑ DBMS contains information about a particular enterprise
▪ Collection of interrelated data
▪ Set of programs to access the data
▪ 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
▪ Online retailers: order tracking, customized recommendations
▪ Manufacturing: production, inventory, orders, supply chain
▪ Human resources: employee records, salaries, tax deductions
❑ Databases touch all aspects of our lives
PURPOSE OF DATABASE SYSTEMS
❑ In the early days, database applications were built directly 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 “buried”
in program code rather than being stated explicitly
▪ Hard to add new constraints or change existing ones
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
▪ Example: 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
▪ Example: Two people reading a balance and updating it at the same
time
❖ Security problems
▪ Hard to provide user access to some, but not all, data
❑ Database systems offer solutions to all the above problems
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
customer_id : interger;
customer_name : string;
customer_street : string;
customer_city : string;
end;
❑ View level: application programs hide details of data types. Views
can also hide information (such as an employee’s salary) for
security purposes.
VIEW OF DATA
❑ An architecture for a database system
INSTANCES AND SCHEMAS
❑ Similar to types and variables in programming languages
❑ Schema – the logical structure of the database
▪ Example: 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
❑ 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.
DATA MODELS
❑ A collection of tools for describing
▪ Data
▪ Data relationships
▪ Data semantics
▪ Data constraints
❑ Relational model
❑ Entity-Relationship data model (mainly for database design)
❑ Object-based data models (Object-oriented and
Object-relational)
❑ Semistructured data model (XML)
❑ Other older models:
▪ Network model
▪ Hierarchical model
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
▪ Declarative (nonprocedural) – user specifies what data is
required without specifying how to get those data
❑ SQL is the most widely used query language
DATA DEFINITION LANGUAGE (DDL)
❑ Specification notation for defining the database schema
Example: 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
▪ Specifies the storage structure and access methods used
❖ Integrity constraints
▪ Domain constraints
▪ Referential integrity (references constraint in SQL)
▪ Assertions
❖ Authorization
RELATIONAL MODEL
Attributes
Example of tabular data in the relational model
A SAMPLE RELATIONAL DATABASE
STRUCTURED QUERY LANGUAGE (SQL)
❑ SQL: widely used non-procedural language
❖ Example: 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’
❖ Example: 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
DATABASE DESIGN
❑ The process of designing the general structure of the database:
❑ Logical Design – Deciding on the database schema. Database design
requires that we find a “good” collection of relation schemas.
▪ Business decision – What attributes should we record in the database?
▪ Computer Science decision – What relation schemas should we have
and how should the attributes be distributed among the various relation
schemas?
❑ Physical Design – Deciding on the physical layout of the database
THE ENTITY-RELATIONSHIP 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:
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
❑ Issues:
▪ Storage access
▪ File organization
▪ Indexing and hashing
QUERY PROCESSING
1. Parsing and translation
2. Optimization
3. Evaluation
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
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.
DATABASE ARCHITECTURE
The architecture of a database systems is greatly influenced by
the underlying computer system on which the database is running:
❑ Centralized
❑ Client-server
❑ Parallel (multi-processor)
❑ Distributed
2-TIER AND 3-TIER ARCHITECTURE
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
▪ Examples, people accessing database over the web, bank tellers,
clerical staff
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
OVERALL SYSTEM STRUCTURE
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