database
Content
Chapter 1: Introduction
Database System Concepts - 6th Edition
1.1
©Silberschatz, Korth and Sudarshan
Database Management System (DBMS)
What is a DBMS? What are some examples of Database Applications?
Database System Concepts - 6th Edition
1.2
©Silberschatz, Korth and Sudarshan
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 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
Database Applications:
Databases touch all aspects of our lives
Database System Concepts - 6th Edition
1.3
©Silberschatz, Korth and Sudarshan
University Database Example
What are some examples of Application program?
In the early days, database applications were built directly on top of file
systems
Database System Concepts - 6th Edition
1.4
©Silberschatz, Korth and Sudarshan
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
What would be some of the disadvantages of such a strategy?
Database System Concepts - 6th Edition
1.5
©Silberschatz, Korth and Sudarshan
Purpose of Database Systems
Drawbacks of using file systems to store data:
Data redundancy and inconsistency
Multiple file formats, duplication of information in different files Need to write a new program to carry out each new task
Difficulty in accessing data
Data isolation ² multiple files and formats Integrity problems
Integrity constraints (e.g., account balance > 0) become ³buried´ in program code rather than being stated explicitly Hard to add new constraints or change existing ones
Database System Concepts - 6th Edition
1.6
©Silberschatz, Korth and Sudarshan
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 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
Database System Concepts - 6th Edition
1.7
©Silberschatz, Korth and Sudarshan
Levels of Abstraction
An architecture for a database system
Database System Concepts - 6th Edition
1.8
©Silberschatz, Korth and Sudarshan
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 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.
Database System Concepts - 6th Edition
1.9
©Silberschatz, Korth and Sudarshan
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 Analogous to the value of a variable
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
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.
Database System Concepts - 6th Edition
1.10
©Silberschatz, Korth and Sudarshan
Data Models
What is a Data Model? And why have these?
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
Database System Concepts - 6th Edition
1.11
©Silberschatz, Korth and Sudarshan
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
Database System Concepts - 6th Edition
1.12
©Silberschatz, Korth and Sudarshan
Relational Model
Database System Concepts - 6th Edition
1.13
©Silberschatz, Korth and Sudarshan
Relational Model
Relational model (Chapter 2) Example of tabular data in the relational model
Columns
Rows
Database System Concepts - 6th Edition
1.14
©Silberschatz, Korth and Sudarshan
A Sample Relational Database
Database System Concepts - 6th Edition
1.15
©Silberschatz, Korth and Sudarshan
Data Manipulation Language (DML)
Language for accessing and manipulating the data organized by the
appropriate data model
DML also known as query language Procedural ± user specifies what data is required and how to get those data (relational algebra) Declarative (nonprocedural) ± user specifies what data is required without specifying how to get those data (SQL)
Two classes of languages
SQL is the most widely used query language
Database System Concepts - 6th Edition
1.16
©Silberschatz, Korth and Sudarshan
Data Definition Language (DDL)
Specification notation for defining the database schema
create table instructor ( ID char(5), name varchar(20), dept_name varchar(20), salary numeric(8,2)) DDL compiler generates a set of tables stored in a data dictionary Data dictionary contains metadata (i.e., data about data) Database schema Integrity constraints Primary key (ID uniquely identifies instructors) Referential integrity (references constraint in SQL) ± e.g. dept_name value in any instructor tuple must appear in department relation Authorization ~ read, insert, update, delete
Example:
Database System Concepts - 6th Edition
1.17
©Silberschatz, Korth and Sudarshan
SQL
SQL: widely used non-procedural language
Example: Find the name of the instructor with ID 22222 select instructor.ID, department.dept name from instructor, department where instructor.dept name= department.dept name and department.budget > 95000
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
Chapters 3, 4 and 5
Database System Concepts - 6th Edition
1.18
©Silberschatz, Korth and Sudarshan
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 ³good´ 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
Database System Concepts - 6th Edition
1.19
©Silberschatz, Korth and Sudarshan
Database Design?
Is there any problem with this design?
Database System Concepts - 6th Edition
1.20
©Silberschatz, Korth and Sudarshan
Design Approaches
Normalization Theory (Chapter 8)
Formalize what designs are bad, and test for them Models an enterprise as a collection of entities and relationships
Entity Relationship Model (Chapter 7)
Entity: a ³thing´ or ³object´ 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:
Database System Concepts - 6th Edition
1.21
©Silberschatz, Korth and Sudarshan
The Entity-Relationship Model Entity Models an enterprise as a collection of entities and relationships
Entity: a ³thing´ or ³object´ 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:
What happened to dept_name of instructor and student?
Database System Concepts - 6th Edition
1.22
©Silberschatz, Korth and Sudarshan
The Entity-Relationship Model Entity-
Database System Concepts - 6th Edition
1.23
©Silberschatz, Korth and Sudarshan
ObjectObject-Relational Data Models
Relational model: flat, ³atomic´ values.
Atomic is sometimes hard to understand. 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.
Object Relational Data Models
Database System Concepts - 6th Edition
1.24
©Silberschatz, Korth and Sudarshan
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
<bank> <account> <number> A-101 </number> <balance> 3000 </balance> </account> <account> <number> A-101 </number> <balance> 5000 </balance> </account> </bank>
Database System Concepts - 6th Edition 1.25 ©Silberschatz, Korth and Sudarshan
XML: Extensible Markup Language
<bank> <account> <number> A-101 </number> <balance> 3000 </balance> </account> <account> <number> A-101 </number> <balance> 5000 </balance> </account> <account> «. </account> </bank> For $x in /bank/account[balance > 4000] return <number> For $x in /bank/account[balance > 4000] return <ACCT_number>{ $x/@number } </ACCT_number>
Database System Concepts - 6th Edition
1.26
©Silberschatz, Korth and Sudarshan
Database System Internals
Database System Concepts - 6th Edition
1.27
©Silberschatz, Korth and Sudarshan
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 Storage access File organization Indexing and hashing
Issues:
Database System Concepts - 6th Edition
1.28
©Silberschatz, Korth and Sudarshan
Query Processing
1. Parsing and translation 2. Optimization 3. Evaluation
Database System Concepts - 6th Edition
1.29
©Silberschatz, Korth and Sudarshan
Query Processing
Alternate ways of evaluating a given query
Equivalent expressions Different algorithms for each operation Cost difference between good and bad way of query evaluation can be enormous Need to estimate cost of operations
Database System Concepts - 6th Edition
1.30
©Silberschatz, Korth and Sudarshan
Query Processing
Alternate ways of evaluating a given query
Equivalent expressions Customer (id, address info); Balance (id, amount) Print addresses of customers with balance > 2000 Different algorithms for each operation How many seeks? Get to first block; transfer data. Data not contiguous? (more seeks). Using an index? Binary search? Cost difference between good and bad way of query evaluation can be enormous Need to estimate cost of operations Statistical information about relations which a database maintains Estimates for complex expressions
Database System Concepts - 6th Edition
1.31
©Silberschatz, Korth and Sudarshan
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.
Read (A); A = A + 50; Write (A); Read (B); B = B - 50; Write (B);
Database System Concepts - 6th Edition
1.32
©Silberschatz, Korth and Sudarshan
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
Database System Concepts - 6th Edition
1.33
©Silberschatz, Korth and Sudarshan
Database Users and Administrators
Database
Database System Concepts - 6th Edition
1.34
©Silberschatz, Korth and Sudarshan
History of Database Systems
1950s and early 1960s:
Data processing using magnetic tapes for storage
Tapes provided only sequential access
Punched cards for input Hard disks allowed direct access to data Network and hierarchical data models in widespread use Ted Codd defines the relational data model
Late 1960s and 1970s:
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
Database System Concepts - 6th Edition
1.35
©Silberschatz, Korth and Sudarshan
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, ..
Database System Concepts - 6th Edition 1.36 ©Silberschatz, Korth and Sudarshan
End of Chapter 1
Database System Concepts - 6th Edition
1.37
©Silberschatz, Korth and Sudarshan
Figure 1.02
Database System Concepts - 6th Edition
1.38
©Silberschatz, Korth and Sudarshan
Figure 1.04
Database System Concepts - 6th Edition
1.39
©Silberschatz, Korth and Sudarshan
Figure 1.06
Database System Concepts - 6th Edition
1.40
©Silberschatz, Korth and Sudarshan
Database System Concepts - 6th Edition
1.1
©Silberschatz, Korth and Sudarshan
Database Management System (DBMS)
What is a DBMS? What are some examples of Database Applications?
Database System Concepts - 6th Edition
1.2
©Silberschatz, Korth and Sudarshan
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 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
Database Applications:
Databases touch all aspects of our lives
Database System Concepts - 6th Edition
1.3
©Silberschatz, Korth and Sudarshan
University Database Example
What are some examples of Application program?
In the early days, database applications were built directly on top of file
systems
Database System Concepts - 6th Edition
1.4
©Silberschatz, Korth and Sudarshan
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
What would be some of the disadvantages of such a strategy?
Database System Concepts - 6th Edition
1.5
©Silberschatz, Korth and Sudarshan
Purpose of Database Systems
Drawbacks of using file systems to store data:
Data redundancy and inconsistency
Multiple file formats, duplication of information in different files Need to write a new program to carry out each new task
Difficulty in accessing data
Data isolation ² multiple files and formats Integrity problems
Integrity constraints (e.g., account balance > 0) become ³buried´ in program code rather than being stated explicitly Hard to add new constraints or change existing ones
Database System Concepts - 6th Edition
1.6
©Silberschatz, Korth and Sudarshan
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 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
Database System Concepts - 6th Edition
1.7
©Silberschatz, Korth and Sudarshan
Levels of Abstraction
An architecture for a database system
Database System Concepts - 6th Edition
1.8
©Silberschatz, Korth and Sudarshan
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 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.
Database System Concepts - 6th Edition
1.9
©Silberschatz, Korth and Sudarshan
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 Analogous to the value of a variable
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
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.
Database System Concepts - 6th Edition
1.10
©Silberschatz, Korth and Sudarshan
Data Models
What is a Data Model? And why have these?
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
Database System Concepts - 6th Edition
1.11
©Silberschatz, Korth and Sudarshan
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
Database System Concepts - 6th Edition
1.12
©Silberschatz, Korth and Sudarshan
Relational Model
Database System Concepts - 6th Edition
1.13
©Silberschatz, Korth and Sudarshan
Relational Model
Relational model (Chapter 2) Example of tabular data in the relational model
Columns
Rows
Database System Concepts - 6th Edition
1.14
©Silberschatz, Korth and Sudarshan
A Sample Relational Database
Database System Concepts - 6th Edition
1.15
©Silberschatz, Korth and Sudarshan
Data Manipulation Language (DML)
Language for accessing and manipulating the data organized by the
appropriate data model
DML also known as query language Procedural ± user specifies what data is required and how to get those data (relational algebra) Declarative (nonprocedural) ± user specifies what data is required without specifying how to get those data (SQL)
Two classes of languages
SQL is the most widely used query language
Database System Concepts - 6th Edition
1.16
©Silberschatz, Korth and Sudarshan
Data Definition Language (DDL)
Specification notation for defining the database schema
create table instructor ( ID char(5), name varchar(20), dept_name varchar(20), salary numeric(8,2)) DDL compiler generates a set of tables stored in a data dictionary Data dictionary contains metadata (i.e., data about data) Database schema Integrity constraints Primary key (ID uniquely identifies instructors) Referential integrity (references constraint in SQL) ± e.g. dept_name value in any instructor tuple must appear in department relation Authorization ~ read, insert, update, delete
Example:
Database System Concepts - 6th Edition
1.17
©Silberschatz, Korth and Sudarshan
SQL
SQL: widely used non-procedural language
Example: Find the name of the instructor with ID 22222 select instructor.ID, department.dept name from instructor, department where instructor.dept name= department.dept name and department.budget > 95000
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
Chapters 3, 4 and 5
Database System Concepts - 6th Edition
1.18
©Silberschatz, Korth and Sudarshan
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 ³good´ 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
Database System Concepts - 6th Edition
1.19
©Silberschatz, Korth and Sudarshan
Database Design?
Is there any problem with this design?
Database System Concepts - 6th Edition
1.20
©Silberschatz, Korth and Sudarshan
Design Approaches
Normalization Theory (Chapter 8)
Formalize what designs are bad, and test for them Models an enterprise as a collection of entities and relationships
Entity Relationship Model (Chapter 7)
Entity: a ³thing´ or ³object´ 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:
Database System Concepts - 6th Edition
1.21
©Silberschatz, Korth and Sudarshan
The Entity-Relationship Model Entity Models an enterprise as a collection of entities and relationships
Entity: a ³thing´ or ³object´ 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:
What happened to dept_name of instructor and student?
Database System Concepts - 6th Edition
1.22
©Silberschatz, Korth and Sudarshan
The Entity-Relationship Model Entity-
Database System Concepts - 6th Edition
1.23
©Silberschatz, Korth and Sudarshan
ObjectObject-Relational Data Models
Relational model: flat, ³atomic´ values.
Atomic is sometimes hard to understand. 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.
Object Relational Data Models
Database System Concepts - 6th Edition
1.24
©Silberschatz, Korth and Sudarshan
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
<bank> <account> <number> A-101 </number> <balance> 3000 </balance> </account> <account> <number> A-101 </number> <balance> 5000 </balance> </account> </bank>
Database System Concepts - 6th Edition 1.25 ©Silberschatz, Korth and Sudarshan
XML: Extensible Markup Language
<bank> <account> <number> A-101 </number> <balance> 3000 </balance> </account> <account> <number> A-101 </number> <balance> 5000 </balance> </account> <account> «. </account> </bank> For $x in /bank/account[balance > 4000] return <number> For $x in /bank/account[balance > 4000] return <ACCT_number>{ $x/@number } </ACCT_number>
Database System Concepts - 6th Edition
1.26
©Silberschatz, Korth and Sudarshan
Database System Internals
Database System Concepts - 6th Edition
1.27
©Silberschatz, Korth and Sudarshan
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 Storage access File organization Indexing and hashing
Issues:
Database System Concepts - 6th Edition
1.28
©Silberschatz, Korth and Sudarshan
Query Processing
1. Parsing and translation 2. Optimization 3. Evaluation
Database System Concepts - 6th Edition
1.29
©Silberschatz, Korth and Sudarshan
Query Processing
Alternate ways of evaluating a given query
Equivalent expressions Different algorithms for each operation Cost difference between good and bad way of query evaluation can be enormous Need to estimate cost of operations
Database System Concepts - 6th Edition
1.30
©Silberschatz, Korth and Sudarshan
Query Processing
Alternate ways of evaluating a given query
Equivalent expressions Customer (id, address info); Balance (id, amount) Print addresses of customers with balance > 2000 Different algorithms for each operation How many seeks? Get to first block; transfer data. Data not contiguous? (more seeks). Using an index? Binary search? Cost difference between good and bad way of query evaluation can be enormous Need to estimate cost of operations Statistical information about relations which a database maintains Estimates for complex expressions
Database System Concepts - 6th Edition
1.31
©Silberschatz, Korth and Sudarshan
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.
Read (A); A = A + 50; Write (A); Read (B); B = B - 50; Write (B);
Database System Concepts - 6th Edition
1.32
©Silberschatz, Korth and Sudarshan
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
Database System Concepts - 6th Edition
1.33
©Silberschatz, Korth and Sudarshan
Database Users and Administrators
Database
Database System Concepts - 6th Edition
1.34
©Silberschatz, Korth and Sudarshan
History of Database Systems
1950s and early 1960s:
Data processing using magnetic tapes for storage
Tapes provided only sequential access
Punched cards for input Hard disks allowed direct access to data Network and hierarchical data models in widespread use Ted Codd defines the relational data model
Late 1960s and 1970s:
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
Database System Concepts - 6th Edition
1.35
©Silberschatz, Korth and Sudarshan
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, ..
Database System Concepts - 6th Edition 1.36 ©Silberschatz, Korth and Sudarshan
End of Chapter 1
Database System Concepts - 6th Edition
1.37
©Silberschatz, Korth and Sudarshan
Figure 1.02
Database System Concepts - 6th Edition
1.38
©Silberschatz, Korth and Sudarshan
Figure 1.04
Database System Concepts - 6th Edition
1.39
©Silberschatz, Korth and Sudarshan
Figure 1.06
Database System Concepts - 6th Edition
1.40
©Silberschatz, Korth and Sudarshan
