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Introduction to Database
Week # 1
Dr. Zeeshan Rafi
PhD MIS (TR), MPhil IT (PK)
Former Software Engineer
Istanbul University, TR
KHAS University, TR
University of Gujrat, PK
Department of Computing and
Information Systems
Lecture Outline
• Database-System Applications
• Purpose of Database Systems
• View of Data
• Database Languages
• Database Design
• Database Engine
• Database Architecture
• Database Users and Administrators
• History of Database Systems
Database Systems
• DBMS contains information about a particular enterprise, Organization,
business or any other group of data, it consists of
• Collection of interrelated data
• Set of programs to access the data
• An environment that is both convenient and efficient to use
• Database systems are used to manage collections of data that are:
• Highly valuable
• Relatively large
• Accessed by multiple users and applications, often at the same time.
• A modern database system is a complex software system whose task is to
manage a large, complex collection of data.
• Databases touch all aspects of our lives
Database Applications Examples
• Enterprise Information
• Sales: customers, products, purchases
• Accounting: payments, receipts, assets
• Human Resources: Information about employees, salaries, payroll taxes.
• Manufacturing: management of production, inventory, orders, supply chain.
• Banking and finance
• customer information, accounts, loans, and banking transactions.
• Credit card transactions
• Finance: sales and purchases of financial instruments (e.g., stocks and
bonds; storing real-time market data
• Universities: registration, grades
Database Applications Examples (Cont.)
• Airlines: reservations, schedules
• Telecommunication: records of calls, texts, and data usage, generating monthly
bills, maintaining balances on prepaid calling cards
• Web-based services
• Online retailers: order tracking, customized recommendations
• Online advertisements
• Document databases
• Navigation systems: For maintaining the locations of varies places of interest
along with the exact routes of roads, train systems, buses, etc.
Purpose of Database Systems
• Data redundancy and inconsistency: data is stored in multiple file formats
resulting induplication 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
In the early days, database applications were built directly on top of file systems,
which leads to:
Purpose of Database 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 access needed for performance
• Uncontrolled concurrent accesses can lead to inconsistencies
• Ex: Two people reading a balance (say 100) and updating it by withdrawing money (say
50 each) 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
University Database Example
• In this text we will be using a university database to illustrate all the concepts
• Data consists of information about:
• Students
• Instructors
• Classes
• Application program examples:
• Add new students, instructors, and courses
• Register students for courses, and generate class rosters
• Assign grades to students, compute grade point averages (GPA) and generate
transcripts
View of Data
• A database system is a collection of interrelated data and a set of programs that
allow users to access and modify these data.
• A major purpose of a database system is to provide users with an abstract view of
the data.
• Data models
• A collection of conceptual tools for describing data, data relationships,
data semantics, and consistency constraints.
• Data abstraction
• Hide the complexity of data structures to represent data in the
database from users through several levels of data abstraction.
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)
• Semi-structured data model (XML)
• Other older models:
• Network model
• Hierarchical model
Relational Model
• All the data is stored in various tables.
• Example of tabular data in the relational model
Columns
Rows
Ted Codd
Turing Award 1981
A Sample Relational Database
Levels of Abstraction
• Physical level: describes how a record (e.g., instructor) is stored.
• Logical level: describes data stored in database, and the relationships among the
data.
type instructor = record
ID : string;
name : string;
dept_name : string;
salary : integer;
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
• Logical Schema – the overall logical structure of the database
• Example: The database consists of information about a set of customers and
accounts in a bank and the relationship between them
• Analogous to type information of a variable in a program
• Physical schema – the overall physical structure of the database
• Instance – the actual content of the database at a particular point in time
• Analogous to the value of a variable
Physical Data Independence
• 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 Definition Language (DDL)
• Specification notation for defining the database schema
Example: create table instructor (
ID char(5),
name varchar(20),
dept_name varchar(20),
salary numeric(8,2))
• DDL compiler generates a set of table templates stored in a data dictionary
• Data dictionary contains metadata (i.e., data about data)
• Database schema
• Integrity constraints
• Primary key (ID uniquely identifies instructors)
• Authorization
• Who can access what
Data Manipulation Language (DML)
• Language for accessing and updating the data organized by the appropriate data
model
• DML also known as query language
• There are basically two types of data-manipulation
language
• Procedural DML -- require a user to specify what data are
needed and how to get those data.
• Declarative DML -- require a user to specify what data are
needed without specifying how to get those data.
• Declarative DMLs are usually easier to learn and use
than are procedural DMLs.
• Declarative DMLs are also referred to as non-
procedural DMLs
• The portion of a DML that involves information
retrieval is called a query language.
SQL Query Language
• SQL query language is nonprocedural. A query takes as input several tables
(possibly only one) and always returns a single table.
• Example to find all instructors in Comp. Sci. dept
select name
from instructor
where dept_name = 'Comp. Sci.'
• SQL is NOT a Turing machine equivalent language
• To be able to compute complex functions SQL is usually embedded in some
higher-level language
• 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 Access from Application Program
• Non-procedural query languages such as SQL are not as powerful as a universal
Turing machine.
• SQL does not support actions such as input from users, output to displays, or
communication over the network.
• Such computations and actions must be written in a host language, such as
C/C++, Java or Python, with embedded SQL queries that access the data in the
database.
• Application programs -- are programs that are used to interact with the database
in this fashion.
Database Design
• 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 process of designing the general structure of the database:
Database Engine
• A database system is partitioned into modules that deal with each of the
responsibilities of the overall system.
• The functional components of a database system can be divided into
• The storage manager,
• The query processor component,
• The transaction management component.
Storage Manager
• 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 OS file manager
• Efficient storing, retrieving and updating of data
• The storage manager components include:
• Authorization and integrity manager
• Transaction manager
• File manager
• Buffer manager
Storage Manager (Cont.)
• The storage manager implements several data structures as part of the physical
system implementation:
• Data files -- store the database itself
• Data dictionary -- stores metadata about the structure of the database, in
particular the schema of the database.
• Indices -- can provide fast access to data items. A database index provides
pointers to those data items that hold a particular value.
Query Processor
• The query processor components include:
• DDL interpreter -- interprets DDL statements and records the definitions in
the data dictionary.
• DML compiler -- translates DML statements in a query language into an
evaluation plan consisting of low-level instructions that the query evaluation
engine understands.
• The DML compiler performs query optimization; that is, it picks the
lowest cost evaluation plan from among the various alternatives.
• Query evaluation engine -- executes low-level instructions generated by the
DML compiler.
Query Processing
1. Parsing and translation
2. Optimization
3. Evaluation
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
• Centralized databases
• One to a few cores, shared memory
• Client-server,
• One server machine executes work on behalf of multiple client machines.
• Parallel databases
• Many core shared memory
• Shared disk
• Shared nothing
• Distributed databases
• Geographical distribution
• Schema/data heterogeneity
Database Architecture (Centralized/Shared-Memory)
Database Applications
• Two-tier architecture -- the application resides at the client machine, where it
invokes database system functionality at the server machine
• Three-tier architecture -- the client machine acts as a front end and does not
contain any direct database calls.
• The client end communicates with an application server, usually through a
forms interface.
• The application server in turn communicates with a database system to
access data.
Database applications are usually partitioned into two or three parts
Two-tier and three-tier architectures

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01-Database Administration and Management.pdf

  • 2. Dr. Zeeshan Rafi PhD MIS (TR), MPhil IT (PK) Former Software Engineer Istanbul University, TR KHAS University, TR University of Gujrat, PK Department of Computing and Information Systems
  • 3. Lecture Outline • Database-System Applications • Purpose of Database Systems • View of Data • Database Languages • Database Design • Database Engine • Database Architecture • Database Users and Administrators • History of Database Systems
  • 4. Database Systems • DBMS contains information about a particular enterprise, Organization, business or any other group of data, it consists of • Collection of interrelated data • Set of programs to access the data • An environment that is both convenient and efficient to use • Database systems are used to manage collections of data that are: • Highly valuable • Relatively large • Accessed by multiple users and applications, often at the same time. • A modern database system is a complex software system whose task is to manage a large, complex collection of data. • Databases touch all aspects of our lives
  • 5. Database Applications Examples • Enterprise Information • Sales: customers, products, purchases • Accounting: payments, receipts, assets • Human Resources: Information about employees, salaries, payroll taxes. • Manufacturing: management of production, inventory, orders, supply chain. • Banking and finance • customer information, accounts, loans, and banking transactions. • Credit card transactions • Finance: sales and purchases of financial instruments (e.g., stocks and bonds; storing real-time market data • Universities: registration, grades
  • 6. Database Applications Examples (Cont.) • Airlines: reservations, schedules • Telecommunication: records of calls, texts, and data usage, generating monthly bills, maintaining balances on prepaid calling cards • Web-based services • Online retailers: order tracking, customized recommendations • Online advertisements • Document databases • Navigation systems: For maintaining the locations of varies places of interest along with the exact routes of roads, train systems, buses, etc.
  • 7. Purpose of Database Systems • Data redundancy and inconsistency: data is stored in multiple file formats resulting induplication 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 In the early days, database applications were built directly on top of file systems, which leads to:
  • 8. Purpose of Database 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 access needed for performance • Uncontrolled concurrent accesses can lead to inconsistencies • Ex: Two people reading a balance (say 100) and updating it by withdrawing money (say 50 each) 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
  • 9. University Database Example • In this text we will be using a university database to illustrate all the concepts • Data consists of information about: • Students • Instructors • Classes • Application program examples: • Add new students, instructors, and courses • Register students for courses, and generate class rosters • Assign grades to students, compute grade point averages (GPA) and generate transcripts
  • 10. View of Data • A database system is a collection of interrelated data and a set of programs that allow users to access and modify these data. • A major purpose of a database system is to provide users with an abstract view of the data. • Data models • A collection of conceptual tools for describing data, data relationships, data semantics, and consistency constraints. • Data abstraction • Hide the complexity of data structures to represent data in the database from users through several levels of data abstraction.
  • 11. 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) • Semi-structured data model (XML) • Other older models: • Network model • Hierarchical model
  • 12. Relational Model • All the data is stored in various tables. • Example of tabular data in the relational model Columns Rows Ted Codd Turing Award 1981
  • 14. Levels of Abstraction • Physical level: describes how a record (e.g., instructor) is stored. • Logical level: describes data stored in database, and the relationships among the data. type instructor = record ID : string; name : string; dept_name : string; salary : integer; end; • View level: application programs hide details of data types. Views can also hide information (such as an employee’s salary) for security purposes.
  • 15. View of Data An architecture for a database system
  • 16. Instances and Schemas • Similar to types and variables in programming languages • Logical Schema – the overall logical structure of the database • Example: The database consists of information about a set of customers and accounts in a bank and the relationship between them • Analogous to type information of a variable in a program • Physical schema – the overall physical structure of the database • Instance – the actual content of the database at a particular point in time • Analogous to the value of a variable
  • 17. Physical Data Independence • 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.
  • 18. Data Definition Language (DDL) • Specification notation for defining the database schema Example: create table instructor ( ID char(5), name varchar(20), dept_name varchar(20), salary numeric(8,2)) • DDL compiler generates a set of table templates stored in a data dictionary • Data dictionary contains metadata (i.e., data about data) • Database schema • Integrity constraints • Primary key (ID uniquely identifies instructors) • Authorization • Who can access what
  • 19. Data Manipulation Language (DML) • Language for accessing and updating the data organized by the appropriate data model • DML also known as query language • There are basically two types of data-manipulation language • Procedural DML -- require a user to specify what data are needed and how to get those data. • Declarative DML -- require a user to specify what data are needed without specifying how to get those data. • Declarative DMLs are usually easier to learn and use than are procedural DMLs. • Declarative DMLs are also referred to as non- procedural DMLs • The portion of a DML that involves information retrieval is called a query language.
  • 20. SQL Query Language • SQL query language is nonprocedural. A query takes as input several tables (possibly only one) and always returns a single table. • Example to find all instructors in Comp. Sci. dept select name from instructor where dept_name = 'Comp. Sci.' • SQL is NOT a Turing machine equivalent language • To be able to compute complex functions SQL is usually embedded in some higher-level language • 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
  • 21. Database Access from Application Program • Non-procedural query languages such as SQL are not as powerful as a universal Turing machine. • SQL does not support actions such as input from users, output to displays, or communication over the network. • Such computations and actions must be written in a host language, such as C/C++, Java or Python, with embedded SQL queries that access the data in the database. • Application programs -- are programs that are used to interact with the database in this fashion.
  • 22. Database Design • 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 process of designing the general structure of the database:
  • 23. Database Engine • A database system is partitioned into modules that deal with each of the responsibilities of the overall system. • The functional components of a database system can be divided into • The storage manager, • The query processor component, • The transaction management component.
  • 24. Storage Manager • 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 OS file manager • Efficient storing, retrieving and updating of data • The storage manager components include: • Authorization and integrity manager • Transaction manager • File manager • Buffer manager
  • 25. Storage Manager (Cont.) • The storage manager implements several data structures as part of the physical system implementation: • Data files -- store the database itself • Data dictionary -- stores metadata about the structure of the database, in particular the schema of the database. • Indices -- can provide fast access to data items. A database index provides pointers to those data items that hold a particular value.
  • 26. Query Processor • The query processor components include: • DDL interpreter -- interprets DDL statements and records the definitions in the data dictionary. • DML compiler -- translates DML statements in a query language into an evaluation plan consisting of low-level instructions that the query evaluation engine understands. • The DML compiler performs query optimization; that is, it picks the lowest cost evaluation plan from among the various alternatives. • Query evaluation engine -- executes low-level instructions generated by the DML compiler.
  • 27. Query Processing 1. Parsing and translation 2. Optimization 3. Evaluation
  • 28. 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.
  • 29. Database Architecture • Centralized databases • One to a few cores, shared memory • Client-server, • One server machine executes work on behalf of multiple client machines. • Parallel databases • Many core shared memory • Shared disk • Shared nothing • Distributed databases • Geographical distribution • Schema/data heterogeneity
  • 31. Database Applications • Two-tier architecture -- the application resides at the client machine, where it invokes database system functionality at the server machine • Three-tier architecture -- the client machine acts as a front end and does not contain any direct database calls. • The client end communicates with an application server, usually through a forms interface. • The application server in turn communicates with a database system to access data. Database applications are usually partitioned into two or three parts
  • 32. Two-tier and three-tier architectures