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Database System Concepts, 6th Ed.
©Silberschatz, Korth and Sudarshan
See www.db-book.com for conditions on re-use
Chapter 1: Introduction
©Silberschatz, Korth and Sudarshan
1.2
Database System Concepts - 6th Edition
Outline
 The Need for Databases
 Data Models
 Relational Databases
 Database Design
 Storage Manager
 Query Processing
 Transaction Manager
©Silberschatz, Korth and Sudarshan
1.3
Database System Concepts - 6th Edition
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: 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 can be very large.
 Databases touch all aspects of our lives
©Silberschatz, Korth and Sudarshan
1.4
Database System Concepts - 6th Edition
University Database Example
 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
 In the early days, database applications were built directly on
top of file systems
©Silberschatz, Korth and Sudarshan
1.5
Database System Concepts - 6th Edition
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
©Silberschatz, Korth and Sudarshan
1.6
Database System Concepts - 6th Edition
Drawbacks of using file systems to store data (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
 Example: 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
©Silberschatz, Korth and Sudarshan
1.7
Database System Concepts - 6th Edition
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.
©Silberschatz, Korth and Sudarshan
1.8
Database System Concepts - 6th Edition
View of Data
An architecture for a database system
©Silberschatz, Korth and Sudarshan
1.9
Database System Concepts - 6th Edition
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 – 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.
©Silberschatz, Korth and Sudarshan
1.10
Database System Concepts - 6th Edition
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
©Silberschatz, Korth and Sudarshan
1.11
Database System Concepts - 6th Edition
Relational Model
 All the data is stored in various tables.
 Example of tabular data in the relational model Columns
Rows
©Silberschatz, Korth and Sudarshan
1.12
Database System Concepts - 6th Edition
A Sample Relational Database
©Silberschatz, Korth and Sudarshan
1.13
Database System Concepts - 6th Edition
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
©Silberschatz, Korth and Sudarshan
1.14
Database System Concepts - 6th Edition
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
 Pure – used for proving properties about computational
power and for optimization
 Relational Algebra
 Tuple relational calculus
 Domain relational calculus
 Commercial – used in commercial systems
 SQL is the most widely used commercial language
©Silberschatz, Korth and Sudarshan
1.15
Database System Concepts - 6th Edition
SQL
 The most widely used commercial language
 SQL is NOT a Turing machine equivalent language
 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
©Silberschatz, Korth and Sudarshan
1.16
Database System Concepts - 6th Edition
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:
©Silberschatz, Korth and Sudarshan
1.17
Database System Concepts - 6th Edition
Database Design (Cont.)
 Is there any problem with this relation?
©Silberschatz, Korth and Sudarshan
1.18
Database System Concepts - 6th Edition
Design Approaches
 Need to come up with a methodology to ensure that each of the
relations in the database is “good”
 Two ways of doing so:
 Entity Relationship Model (Chapter 7)
 Models an enterprise as a collection of entities and
relationships
 Represented diagrammatically by an entity-relationship
diagram:
 Normalization Theory (Chapter 8)
 Formalize what designs are bad, and test for them
©Silberschatz, Korth and Sudarshan
1.19
Database System Concepts - 6th Edition
Object-Relational Data Models
 Relational model: flat, “atomic” values
 Object Relational Data Models
 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 non-
atomic 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.
©Silberschatz, Korth and Sudarshan
1.20
Database System Concepts - 6th Edition
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
©Silberschatz, Korth and Sudarshan
1.21
Database System Concepts - 6th Edition
Database Engine
 Storage manager
 Query processing
 Transaction manager
©Silberschatz, Korth and Sudarshan
1.22
Database System Concepts - 6th Edition
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 OS file manager
 Efficient storing, retrieving and updating of data
 Issues:
 Storage access
 File organization
 Indexing and hashing
©Silberschatz, Korth and Sudarshan
1.23
Database System Concepts - 6th Edition
Query Processing
1. Parsing and translation
2. Optimization
3. Evaluation
©Silberschatz, Korth and Sudarshan
1.24
Database System Concepts - 6th Edition
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
©Silberschatz, Korth and Sudarshan
1.25
Database System Concepts - 6th Edition
Transaction Management
 What if the system fails?
 What if more than one user is concurrently updating the same
data?
 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.
©Silberschatz, Korth and Sudarshan
1.26
Database System Concepts - 6th Edition
Database Users and Administrators
Database
©Silberschatz, Korth and Sudarshan
1.27
Database System Concepts - 6th Edition
Database System Internals
©Silberschatz, Korth and Sudarshan
1.28
Database System Concepts - 6th Edition
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
©Silberschatz, Korth and Sudarshan
1.29
Database System Concepts - 6th Edition
History of Database Systems
 1950s and early 1960s:
 Data processing using magnetic tapes for storage
 Tapes provided only sequential access
 Punched cards for input
 Late 1960s and 1970s:
 Hard disks allowed direct access to data
 Network and hierarchical data models in widespread use
 Ted Codd defines the relational data model
 Would win the ACM Turing Award for this work
 IBM Research begins System R prototype
 UC Berkeley begins Ingres prototype
 High-performance (for the era) transaction processing
©Silberschatz, Korth and Sudarshan
1.30
Database System Concepts - 6th Edition
History (cont.)
 1980s:
 Research relational prototypes evolve into commercial systems
 SQL becomes industrial standard
 Parallel and distributed database systems
 Object-oriented database systems
 1990s:
 Large decision support and data-mining applications
 Large multi-terabyte data warehouses
 Emergence of Web commerce
 Early 2000s:
 XML and XQuery standards
 Automated database administration
 Later 2000s:
 Giant data storage systems
 Google BigTable, Yahoo PNuts, Amazon, ..
©Silberschatz, Korth and Sudarshan
1.31
Database System Concepts - 6th Edition
End of Chapter 1

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ch1.ppt

  • 1. Database System Concepts, 6th Ed. ©Silberschatz, Korth and Sudarshan See www.db-book.com for conditions on re-use Chapter 1: Introduction
  • 2. ©Silberschatz, Korth and Sudarshan 1.2 Database System Concepts - 6th Edition Outline  The Need for Databases  Data Models  Relational Databases  Database Design  Storage Manager  Query Processing  Transaction Manager
  • 3. ©Silberschatz, Korth and Sudarshan 1.3 Database System Concepts - 6th Edition 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: 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 can be very large.  Databases touch all aspects of our lives
  • 4. ©Silberschatz, Korth and Sudarshan 1.4 Database System Concepts - 6th Edition University Database Example  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  In the early days, database applications were built directly on top of file systems
  • 5. ©Silberschatz, Korth and Sudarshan 1.5 Database System Concepts - 6th Edition 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
  • 6. ©Silberschatz, Korth and Sudarshan 1.6 Database System Concepts - 6th Edition Drawbacks of using file systems to store data (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  Example: 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
  • 7. ©Silberschatz, Korth and Sudarshan 1.7 Database System Concepts - 6th Edition 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.
  • 8. ©Silberschatz, Korth and Sudarshan 1.8 Database System Concepts - 6th Edition View of Data An architecture for a database system
  • 9. ©Silberschatz, Korth and Sudarshan 1.9 Database System Concepts - 6th Edition 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 – 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.
  • 10. ©Silberschatz, Korth and Sudarshan 1.10 Database System Concepts - 6th Edition 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
  • 11. ©Silberschatz, Korth and Sudarshan 1.11 Database System Concepts - 6th Edition Relational Model  All the data is stored in various tables.  Example of tabular data in the relational model Columns Rows
  • 12. ©Silberschatz, Korth and Sudarshan 1.12 Database System Concepts - 6th Edition A Sample Relational Database
  • 13. ©Silberschatz, Korth and Sudarshan 1.13 Database System Concepts - 6th Edition 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
  • 14. ©Silberschatz, Korth and Sudarshan 1.14 Database System Concepts - 6th Edition 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  Pure – used for proving properties about computational power and for optimization  Relational Algebra  Tuple relational calculus  Domain relational calculus  Commercial – used in commercial systems  SQL is the most widely used commercial language
  • 15. ©Silberschatz, Korth and Sudarshan 1.15 Database System Concepts - 6th Edition SQL  The most widely used commercial language  SQL is NOT a Turing machine equivalent language  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
  • 16. ©Silberschatz, Korth and Sudarshan 1.16 Database System Concepts - 6th Edition 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:
  • 17. ©Silberschatz, Korth and Sudarshan 1.17 Database System Concepts - 6th Edition Database Design (Cont.)  Is there any problem with this relation?
  • 18. ©Silberschatz, Korth and Sudarshan 1.18 Database System Concepts - 6th Edition Design Approaches  Need to come up with a methodology to ensure that each of the relations in the database is “good”  Two ways of doing so:  Entity Relationship Model (Chapter 7)  Models an enterprise as a collection of entities and relationships  Represented diagrammatically by an entity-relationship diagram:  Normalization Theory (Chapter 8)  Formalize what designs are bad, and test for them
  • 19. ©Silberschatz, Korth and Sudarshan 1.19 Database System Concepts - 6th Edition Object-Relational Data Models  Relational model: flat, “atomic” values  Object Relational Data Models  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 non- atomic 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.
  • 20. ©Silberschatz, Korth and Sudarshan 1.20 Database System Concepts - 6th Edition 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
  • 21. ©Silberschatz, Korth and Sudarshan 1.21 Database System Concepts - 6th Edition Database Engine  Storage manager  Query processing  Transaction manager
  • 22. ©Silberschatz, Korth and Sudarshan 1.22 Database System Concepts - 6th Edition 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 OS file manager  Efficient storing, retrieving and updating of data  Issues:  Storage access  File organization  Indexing and hashing
  • 23. ©Silberschatz, Korth and Sudarshan 1.23 Database System Concepts - 6th Edition Query Processing 1. Parsing and translation 2. Optimization 3. Evaluation
  • 24. ©Silberschatz, Korth and Sudarshan 1.24 Database System Concepts - 6th Edition 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
  • 25. ©Silberschatz, Korth and Sudarshan 1.25 Database System Concepts - 6th Edition Transaction Management  What if the system fails?  What if more than one user is concurrently updating the same data?  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.
  • 26. ©Silberschatz, Korth and Sudarshan 1.26 Database System Concepts - 6th Edition Database Users and Administrators Database
  • 27. ©Silberschatz, Korth and Sudarshan 1.27 Database System Concepts - 6th Edition Database System Internals
  • 28. ©Silberschatz, Korth and Sudarshan 1.28 Database System Concepts - 6th Edition 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
  • 29. ©Silberschatz, Korth and Sudarshan 1.29 Database System Concepts - 6th Edition History of Database Systems  1950s and early 1960s:  Data processing using magnetic tapes for storage  Tapes provided only sequential access  Punched cards for input  Late 1960s and 1970s:  Hard disks allowed direct access to data  Network and hierarchical data models in widespread use  Ted Codd defines the relational data model  Would win the ACM Turing Award for this work  IBM Research begins System R prototype  UC Berkeley begins Ingres prototype  High-performance (for the era) transaction processing
  • 30. ©Silberschatz, Korth and Sudarshan 1.30 Database System Concepts - 6th Edition History (cont.)  1980s:  Research relational prototypes evolve into commercial systems  SQL becomes industrial standard  Parallel and distributed database systems  Object-oriented database systems  1990s:  Large decision support and data-mining applications  Large multi-terabyte data warehouses  Emergence of Web commerce  Early 2000s:  XML and XQuery standards  Automated database administration  Later 2000s:  Giant data storage systems  Google BigTable, Yahoo PNuts, Amazon, ..
  • 31. ©Silberschatz, Korth and Sudarshan 1.31 Database System Concepts - 6th Edition End of Chapter 1