dbms basic reference

7/30/2019 DBMS Basic Reference

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DATA BASE

This Is About Managing and structuring the

collections of data held on computers. Adatabase consists of an organized collection

of data for one or more uses, typically in

digital form. Database involves the type of

their contents.

Eg:- bibliographic, document - text,statistical.


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Project database

Centraldatabase

UserDB 1

UserDB 2

UserDB 43

userDB 4


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Architecture

Database architecture consists of there

levels external, conceptual and internal.Clearly separating the three levels was a

major feature of the relational databasemodel that dominates 21st century database.


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Database Management System

A database management system(DBMS)

consists of software that operates databases,providing storage, access, security, backup and

other facilities. Examples of some commonly

used DBMS are My SQL, Postgre SQL,

Microsoft access, SQL server, file maker, oracle,

RDBMS and clipper etc.


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Components of DBMS

Most DBMS as of 2009 implement a relational model. Other

DBMS system , such as object DBMS, offer specific feature formore specialized requirements. Their components are similar,

but not identical.


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RDBMS Components

Sublanguage

Language(DDL)

Language(DCL)

Language(DML)

Relation DBMS(RDBMS)

for defining the structureof database and data

control

for defining security/access

controls, and data

manipulation.

For querying and updating

data.


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RDBMS Components

Interface drivers these drivers are code

libraries that provide methods to preparestatements, execute statement, fetch results

etc. E.g. ODBC,JDBC

SQL engine the components interpretsand execute the DDL,DCL and DML

statements, it include three majorcomponents computer, optimizer and

executer.


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RDBMS Components

Transaction engine ensure that multiple SQL

statements either or fail as a group, according toapplication dictates.

Relation engine relation objects such as Table,

Index, and referential integrity constraints are

implemented in this components.


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ODBMS Components

object DBMS (ODBMS) has transaction and

storage components that are analogous to thosein an RDBMS. Some ODBMS handles DDL,DCL

and update tasks. differently instead of using

sublanguages, they provide APIs for these

purposes E.g. OQL,LING


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Types of Database

Operational database these database store

the detailed database about the operations of anorganization they are typically organized by

subject matter, process relatively high volumes

of update using transaction E.g. include

customers database that record cont, credit.


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Types of Database

Data Warehouse data ware houses archive

modern data from operational database andoften from external sources such as market

research firms. Often operational data

undergoes transformation on its way into the

warehouse, getting summarized, anonymized,

reclassified etc. E.g. sales data might be arrangedto weekly totals and converted from internal

product codes into UPC code.


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Types of Database

Analytical database it may do their work

directly against, a data warehouse , or credit aseparate analytic database for online analytical

processing. E.g. a company might extract sales

records for analyzing the effectiveness of

advertising and other sales promotions of an

aggregate level.


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Types of Database

Distributed database it is local work-groups and

departments at regional offices, branch offices,manufacturing plants and other work sites.

External database it contain data collected for user

across multiple organization, either freely or via

subscription.


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Types of Database

End-user database it consist of data developed

by individuals end-users. E.g. these arecollections of documents in spreadsheet, word

processing and downloaded files.

Hypermedia database - the worldwide web can

through of as a database, albeit one spread

across million s of independent computingsystem.


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Models

Post-relation database models product

offering a more general data model than arerelational model are sometime classified as post-

relational alternate term include hybrid

database, object-enhanced RDBMS and

others. The data model in such products

incorporates relations but not constrained by E.F.codds information principle.


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Models

Object database models In recent year, the

object-oriented paradigm has been applied inarea such as engineering and spatial database

telecommunication and in various scientific

domain. The conglomeration of object oriented

programming and database technology led to

this new kind of database.


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Storage structure

Database may store relational tables/indexes in memory or onhard disk in one of many forms.

Ordered/unordered flat files

ISAM

Heaps

Hash buckets

B+ tree

The most commonly used b+ tree and ISAM.


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Indexing

Indexing is a technique for improving database

performance. The simplest form of index is avalues that can be searched using a binary

search with an adjacent reference to the location

of the entry, analogous to the index in the black

of a book.

Transaction

as every s/w system, a DBMS

operates in a faulty computing environment and

prone of failures of many kinds


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The ACID rules

Most DBMS provide some form of support for

transaction, which allow multiple data item to beupdated in a consistence fashion, such that are

part of transaction succeed or fail in unison.

Concurrency control and looking - it essential

for the correctness of transactions executed

concurrently in a DBMS, which is commonexecution mode for performance reason


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Lock types

Locks can be shared or exclusive, and can look out

readers and/or writers locks can be createdimplicitly by the DBMS when a transaction

performance an operation or explicitly at the

transactions request.

Dead locks dead lock occur when two

transaction each requires data that the other hasalready locked exclusively.


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THE

HOUSE

IS

OPEN

4QUERIES


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Copyright @ www.bcanotes.com

S t r u c t u r e o f D B M S

Data Definition Language Compiler

The DDL Compiler converts the data definition

statements into a set of tables. These tables contain

the metadata concerning the database and are in a

form that can be used by other components of DBMS.


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Data Manager

The data manager is the central software component of the

DBMS. It is sometimes referred to as the database control systemOne of the functions of the data manager is to convert operations

in the users queries coming directly via the query processor or

indirectly via an application program from users logical view to a

physical file system. The data manager is responsible for

interfacing with the file system. In addition, the tasks of enforcing

constraints to maintain the consistency and integrity of the data, aswell as its security, are also performed by the data manager

Synchronizing the simultaneous operations performed by

concurrent users is under the control of the data manager. It is also

entrusted with the backup and recovery operations.


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ile Manager

Responsibility for the structure of the files and managing thefile space rests with the file manager. It is also responsible for

locating the block containing the required record, requesting

this block from the disk manager, and transmitting the

required record to the data manager. The file manager can be

implemented using an interface to the existing file subsystem

provided by the operating system of the host computer or it

can include a file subsystem written especially for DBMS.


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Disk Manager

The disk manager is part of the operating system of the host

computer and all physical input and output operations are

performed by it. The disk manager transfers the block or page

requested by the file manager so that the latter need not be

concerned with the physical characteristics of the underlying

storage media.


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Query Processor

The database user retrieves data by formulating a query in the data

manipulation language provided with the database. The query

processor is used to interpret the online users query and convert it

into an efficient series of operations in a form capable of being

sent to the data manager for execution. The query processor uses

the data dictionary to find the structure of the relevant portion of

the database and uses the information in modifying the query and

preparing an optimal plan to access the database.


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atch

er

Data files and data

dictionary

Telecom System

Compiled

user interface

Compiled application

program

Nave user Casual User

Telecom system

Query Processor

DBMS and its data

manager

OS or own file

manager

OS disk

manager

Telecom system

DDL Compiler

DBA

Data files and

data dictionary


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Data Files

Data files contain the data portion of the database.

Data dictionary

Information pertaining to the structure and usage of data containe

in the database, the metadata, is maintained in a data dictionary

The term system catalog also describes this meta data. The dat

dictionary, which is a database itself, documents the data. Eac

database user can consult the data dictionary to learn what eac

piece of data and various synonyms of the data fields mean.


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Data dictionary

In an integrated system (i.e., in a system where the data

dictionary is a part of the DBMS) the data dictionary store

information concerning the external, conceptual, and interna

levels of the database. It contains the source of each data-field

value, the frequency of its use, and an audit trail concerning

updates, including the who and when of each update.

Currently data dictionary systems are available as add-onto the DBMS. Standards have yet to be evolved for integrating the

data dictionary facility with the DBMS so that the two databases

one for metadata and the other for data, can be manipulated using

an unified DDL/DML.


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Access Facilities

To improve the performance of a DBMS, a set of

access facilities in the form of indexes are usually

provided in a database system. Commands are provided

to build and destroy additional temporary indexes.


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An Architecture for a Database System

The architecture is divided into three general levels: internal

conceptual, and external

External Level

(Individual user view)

Conceptual Level

(Community user view)

Internal Level

(storage view)


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Broadly speaking,

The internal levelis the one closest to the physical storage.

The external levelis the one closest to the users, that is, the one

concerned with the way in which the data is viewed by

individual users.

The conceptual level is a level of indirection between the

other two.


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If the external levelis concerned with the individual user views,

theconceptual levelmay be thought of as defining a community

user view. In other words, there will be many externalviews,

each consisting of a more or less abstract representation of some

portion of the database, and there will be a single conceptual

view, consisting of a similarly abstract representation of the

database in its entirety.(Remember that most users will not be

interested in the total database, but only in some restricted portion

of it.) Likewise, there will be a single internal view,

representing the total database as actually stored.


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E x t e r n a l (PL/I)

DCL 1 EMPP,

2 EMP# CHAR(6),

3 SAL FIXED BIN(31);

E x t e r n a l (COBOL)

01 EMPC.

02 EMPNO PIC X(6).

03 DEPTNO PIC X(4).

C o n c e p t u a l

EMPLOYEE

EMPLOYEE_NUMBER CHARACTER (6)

DEPARTMENT_NUMBER CHARACTER (4)

SALARY NUMRIC (5)

I n t e r n a l

STORED_EMP LENGTH=18

PREFIX TYPE=BYTE(6), OFFSET=0

EMP# TYPE=BYTE(6), OFFSET=6, INDEX=EMPX

DEPT# TYPE=BYTE(4), OFFSET=12

PAY TYPE=FULLWORD, OFFSET=16

A

n

E

x

a

m

p

l

e

o

f

T

hr

e

e

L

e

ve

l

s


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Figure shows the conceptual structure of a simple personnel

database, the corresponding internal structure, and two

corresponding external structure (one for a PL/I user, the other for

COBOL user). The example is completely hypotheticalit is not

intended to resemble any actual system and many irrelevant

details have been deliberately omitted.


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At the conceptual level, the database contains information

concerning an entity type called EMPLOYEE. Each EMPLOYEE

has an EMPLOYEE_NUMBER (six character), a

DEPARTMENT_NUMBER (four characters), and a SALARY

(five digits).


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At the internal level, employees are represented by a stored

record type called STORED_EMP, eighteen bytes long

STORED_EMP contains four stored field types: a six-byte prefix

(presumably containing control information such as flags or

pointers) and three data fields corresponding to the three

properties of EMPLOYEE. In addition, STORED_EMP records

are indexed on the EMP# field by an index called EMPX.


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The PL/I user has an external view of the database in which

each employee is represented by a PL/I record containing two

fields (department numbers are of no interest to this user and are

omitted from the view). The record type is defined by an ordinary

Pl/I structure declaration in accordance with the normal Pl/I rules.


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Similarly, the COBOL user has an external view in which each

employee is represented by a COBOL record containing, again,

two fields (salaries are omitted). The record type is defined by an

ordinary COBOL record description in accordance with normal

COBOL rules.


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Notice that corresponding objects at the three levels can have

different names at each level. For example, the COBOL employee

number field is called EMPNO, the corresponding stored field is

called EMP#, and the corresponding conceptual object is called

EMPLOYEE_NUMBER.( The system must be aware of the

correspondences. For example, it must be told that the COBOL

field EMPNO is derived from the conceptual object

EMPLOYEE_NUMBER, which in turn is represented by the

stored field EMP#. Such correspondences, or mapping, have not

been shown in the figure).


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Components of A r c h i t e c t u r e

The users are either application programmers or on-line terminal

users of any degree of sophistication. Each user has a language at

his or her disposal. For the application programmer it will be a

conventional programming language, such as COBOL or PL/I

for the terminal user it will be either a query language or a special

purpose language tailored to that users requirements and

supported by an on-line application program.

Users


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An individual user will generally be interested only in some

portion of the total database; moreover, the users view of that

portion will generally be some what abstract when compared with

the way in which the data is physically stored. In ANSI terms an

individual users view is called an external view.

External View


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An external view is thus the content of the database as it is seen

by some particular user, for example, a user from personnel

department, users in the purchasing department. In general, then,

an external view consists of multiple occurrences of multiple

types of external records. An external record is not necessarily the

same as a stored record. The users data sub language is defined

in terms of external records.

xternal View


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Each external view is defined by means of an external schema,

which consists basically of definitions of each of the various

types of external record in the that external view. The external

schema is written using the DDL portion of the data sub

language. That DDL is therefore sometimes called an external

DDL.

xternal View


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The conceptual view is a representation of the entire information

content of the database, again in a form that is somewhat abstract

in comparison with the way in which the data is physically

stored.(It may also be quite different from the way in which the

data is viewed by any particular user. Broadly speaking, it is

intended to be a view of the data as it really is, rather than as

users are forced to see it by the constraints of the particular

language or hardware they are using.

Conceptual View


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A conceptual record is not necessarily the same as either an

external record, on the one hand, or a stored record, on the other.

The conceptual view is defined by means of the conceptual

schema, which includes definitions of each of the various types of

conceptual record. The conceptual schema is written using

another data definition languagethe conceptual DDL.

Conceptual View


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The conceptual view, then, is a view of the total database content,

and the conceptual schema is a definition of this view. However,

it would be misleading to suggest that the conceptual schema is

nothing more than a set of definitions much like the simple record

definitions in a COBOL program today. The definitions in the

conceptual schema are intended to include a great many

additional features, such as authorization checks and validation

procedures.

Conceptual View


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The internal view is a very low level representation of the entiredatabase; it consists of multiple occurrences of multiple types of

internal record. Internal record is the ANSI term for the

construct that we have been calling a stored record; the internal

view is thus still at one remove from the physical level, since it

does not deal in terms of physical records or blocks, nor with any

device-specific constraints such as cylinder or track sizes.

nternal Level


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nternal Level

The internal view is described by means of the internal schema,

which not only defines the various types of stored record but also

specifies what indexes exist, how stored fields are represented,

what physical sequence the stored record are in, and so on. The

internal schema is written in using yet another data definition

language - the internal DDL.


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Mapping between Conceptual & Internal

The conceptual/internal mapping defines the correspondence

between conceptual view and the stored database; it specifies how

conceptual records and fields map into their stored counterparts

If the structure of the stored database is changedi.e., if a change

is made to the storage structure definition the

conceptual/internal mapping must be changed accordingly, so thatthe conceptual schema may remain invariant. In other words, the

effects of such changes must be contained below the conceptual

level, so that data independence can be achieved.


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Mapping between External & Conceptual

An external/conceptual mapping defines the correspondence

between a particular external view and the conceptual view. In

general, the same sort of differences may exist between these two

levels as may exist between the conceptual view and stored

database. For example, fields may have different data types

records may be differently sequenced and so on. Any number ofexternal views may exist at the same time; any numbers of users

may share a given external view; different external views may

overlap.


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Database System Environment

The term database system refers to anorganization of components that define andregulate the collection, storage, management,and use of data within a databaseenvironment. These are:

Hardware Software People Procedures Data



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It identifies all the systems physicaldevices. The database systems main and mosteasily identified hardware component is thecomputer, which might be a microprocessor, a

minicomputer, or a mainframe computer. Italso include peripherals like keyboard, mice,modems, printers, etc.

Hardware



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Software refers to the collection ofprograms used by the computers within thedatabase system.

Operating system Software- managesall hardware components and makes it

possible for all other software to run on thecomputers. DOS,OS/2, and Windows used bymicro computers. UNIX and VMS used bymini computers, and MVS used by IBMmainframe computers.

Software



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DBMS Software- manages the databasewithin the database system. MS-Access, MS-SQL Server, Oracle, DB2 etc. are some famousDBMS software.

Application Programs & Utilities

Software- are used to access and manipulatethe data in the DBMS to manage the computerenvironment in which data access andmanipulation take place.



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System Administrator: oversee thedatabase systems general operations.

Database Administrator: manage theDBMSs use and ensure that the database isfunctioning properly.

Database Designers: design the databasestructure. They are in effect the databasearchitects. If the database design is poor, eventhe best application programmers and the mostdedicated DBAs will fail to produce a usefuldatabase environment.

People



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System Analysts and Programmers: designand implement the application programs. They

design and create the data entry screens, reports,and procedures through which end user accessand manipulate the databases data.

End Users: are the people who use the

application programs to run the organizationsdaily operations. E.g. sales clerks, supervisors,managers, and directors are all classified as endusers. High-level end users employ theinformation obtained from the database to maketactical and strategic business decisions.



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Procedures

Procedures are the instructions and rules thatgovern the design and use of the databasesystem. Procedure are a critical, althoughoccasionally forgotten, component of thesystem. Procedures play a very important role ina company, because they enforce the standards

by which business is conducted within theorganization and with customers. These also areused to ensure that there is an organized way tomonitor and audit both the data andinformation.



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Data

The word data covers the collection of factsstored in the database. Because data are theraw material from which information isgenerated, the determination of which data areto be entered into the database and how such

data are to be organized is a vital part of thedatabase designers job.



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DBMS Functions

A DBMS performs several important functions

that guarantee the integrity and consistency of

the data in the database. Most of these functions

are transparent to end users, and most can beachieved only through the use of a DBMS.



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Data dictionary management: The DBMSrequires that definitions of the data elements

and their relationships(metadata) be stored in a

data dictionary. In turn, all programs that

access the data in the database work through

the DBMS. The DBMS uses the data dictionary

to look up the required data component

structures and relationships, thus relieving us

from having to code such complex relationships

in each program.



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Data Storage Management: The DBMScreates the complex structures required for data

storage, thus relieving us from the difficult task

of defining and programming the physical data

characteristics. A modern DBMS system provides

storage not only for the data, but also for the

related data entry forms or screen definitions,

report definitions, data validation rules,

procedural code, structures to handle video and

picture formats, and so on.



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Data transformation and presentation: theDBMS transforms entered data to conform to thedata structures that are required to store data.Therefore, the DBMS relieves us of the chore ofmaking a distinction between the data logicalformat and the data physical format. By

maintaining the data independence, the DBMStranslates logical requests into commands thatphysically locate and retrieve the requested data.That is, the DBMS formats the physicallyretrieved data to make it confirm to the userslogical expectations.



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Security Management: The DBMS creates asecurity system that enforces user security anddata privacy within the database. Security rulesdetermines which user can access the database,which data items each user may access, and

which data operations the user may perform.This is especially important in multi userdatabase systems where many users can accessthe database simultaneously.



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Multi user access control: The DBMScreates the complex structures that allow multiuser access to the data. In order to provide dataintegrity and data consistency, the DBMS usessophisticated algorithms to ensure that multiple

users can access the database concurrentlywithout compromising the integrity of thedatabase.



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Backup and recovery management: TheDBMS provides backup and data recoveryprocedures to ensure data safety and integrity.Current DBMS system provide special utilitiesthat allow the DBA to perform routine andspecial backup and restore procedures. Recovery

management deals with the recovery of thedatabase after a failure, such as a bad sector inthe disk or a power failure. Such capability iscritical to the preservation of the databasesintegrity.



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Data Integrity Management: The DBMSpromotes and enforces integrity rules toeliminate data integrity problems, thusminimizing the data duplicity and maximizingdata consistency. The data relationships stored inthe data dictionary are used to enforce data

integrity. Ensuring data integrity is especiallyimportant in transaction-oriented databasesystems.



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Database access languages and applicationprogramming interface: The DBMS providesdata access via a query language. A querylanguage is a nonprocedural language that is,one that lets the user specify what must be donewithout having to specify how it is to be done. TheDBMS query language contains two components:

a DDL and DML. The DBMS also provides dataaccess to programmers via procedurallanguages.It also provides administrative utilitiesused by the DBA and the database designer tocreate, implement, monitor, and maintain thedatabase.



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Database communication interfaces:Current-generation DBMSs provide specialcommunications routines designed to allow thedatabase to accept end user requests within acomputer network environment. In fact,database communications capabilities are an

essential feature of the modern DBMS. E.g. theDBMS might provide communications functionsto access the database through the Internet,using Internet browsers such as Netscape orExplorer as the front end.



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There are many definitions of the termdatabaseand one of the most common oneis that the database is a collection ofinformation/ knowledge stored in digital

format.

The database can be in form of a flattext file or can be a relational database.

The term "database" is used to describeboth the collection of data and the softwaretool used to manage the data (i.e. DBMS).

What is a database?



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Databases are used in most of themodern software applications. Databasesprovide the means of storing data, accessiblesimultaneously by many users.

Databases use a programming languagecalled SQL (Structured Query Language),which makes accessing and storing relationaldata very easy.



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RDBMS stands for Relational Database ManagemenSystem. RDBMS data is structured in database tablesfields and records. Each RDBMS table consists odatabase table rows. Each database table rowconsists of one or more database table fields

RDBMS store the data into collection of tables, whicmight be related by common fields (database tablcolumns). RDBMS also provide relational operators tmanipulate the data stored into the database tablesMost RDBMS use SQL as database query language

What is RDBMS?

http://localhost/var/www/apps/conversion/tmp/scratch_1/


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Edgar Codd introduced the relationaldatabase model. Many modern DBMS do notconform to the Codds definition of a RDBMS,but nonetheless they are still considered to be

RDBMS.

The most popular RDBMS are MS SQLServer, DB2, Oracle and MySQL.



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SQL stands for Structured QueryLanguage. SQL language is used to create,transform and retrieve information fromRDBMS. SQL is pronounced SEQUEL. SQL wasdeveloped during the early 70s at IBM.

SQL is a declarative programminglanguage designed for creating and queryingrelational database management systems. SQLis relatively simple language, but its also verypowerful.

What is SQL?



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SQL can insert, modify data in existingdatabase tables. SQL can delete data from SQLdatabase tables. Finally SQL can modify thedatabase structure itself create/ modify/ deletetables and other database objects.

SQL uses set of commands to manipulatethe data in relational databases. For example SQLINSERT is used to insert data in database tables.SQL SELECT command is used to retrieve datafrom one or more database tables. SQL UPDATE isused to modify existing database records.



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Most RDBMS like MS SQL Server, MSAccess, Oracle, MySQL, DB2, Sybase,PostgreSQL and Informix use SQL as adatabase querying language. Even though SQLis defined by both ISO and ANSI there aremany SQL implementation, which do not fully

comply with those definitions. Some of theseSQL implementations are proprietary. Examplesof these SQL dialects are MS SQL Serverspecific version of the SQL called T-SQL andOracle version of SQL called PL/SQL.



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E n t i t y R e l a t i o n s h i p M o d e l

Entity Sets Relationship Sets Design Issues Mapping Constraints Keys E-R Diagram Extended E-R Features Design of an E-R Database Schema Reduction of an E-R Schema to

Tables



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E n t i t y S e t s

Adatabase can be modeled as:

a collection of entities, relationship among entities.

An entity is an object that exists and isdistinguishable from other objects. Example: specific person, company, event, plant

Entities have attributes

Example: people have names and addresses An entity setis a set of entities of the same type that

share the same properties. Example: set of all persons, companies, trees, holidays



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E n t i t y S e t s c u s t o m e r a n d l o a n

customer-id customer- customer- customer- loan- amountname street city number



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A t t r i b u t e s

An entity is represented by a set of attributes, that isdescriptive properties possessed by all members ofan entity set.

Domain the set of permitted values for eachattribute

Attribute types: Simple and composite attributes.

Single-valuedand multi-valuedattributes E.g. multivalued attribute:phone-numbers

Derivedattributes Can be computed from other attributes E.g. age, given date of birth

Example:

customer = (customer-id, customer-name,customer-street, customer-city)loan = (loan-number, amount)



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C o m p o s i t e A t t r i b u t e s



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R e l a t i o n s h i p S e t s

Arelationship is an association among severalentitiesExample:

Hayes depositor A-102customer entityrelationship setaccountentity

Example:(Hayes, A-102) depositor



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Relationship Set borrower



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Relationship Sets (Cont.)

An attribute can also be property of a relationship set. For instance, the depositor relationship set between entity sets

customer and accountmay have the attribute access-date



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Degree of a Relationship Set

Refers to number of entity sets that participate in arelationship set.

Relationship sets that involve two entity sets arebinary (or degree two). Generally, most relationshipsets in a database system are binary.

Relationship sets may involve more than two entitysets.

Relationships between more than two entity sets arerare. Most relationships are binary.

E.g. Suppose employees of a bank may have jobs(responsibilities) at multiple branches, with different jobs atdifferent branches. Then there is a ternary relationship setbetween entity sets employee, job and branch



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Mapping Cardinalities

Express the number of entities to which another

entity can be associated via a relationship set. Most useful in describing binary relationship sets.

For a binary relationship set the mappingcardinality must be one of the following types: One to one

One to many

Many to one

Many to many



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Mapping Cardinalities

One to one One to many

Note: Some elements in A and B may not be mapped to any elements in the other



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Mapping Cardinalities ...

Many to one Many to many

Note: Some elements in A and B may not be mapped to any elements in the other



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Mapping Cardinalities affect ER Design

Can make access-datean attribute of account, instead of arelationship attribute, if each account can have only one customer

I.e., the relationship from account to customer is many to one,or equivalently, customer to account is one to many



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E - R D i a g r a m s

Rectangles represent entity sets.

Diamonds represent relationship sets.

Lines link attributes to entity sets and entity sets to relationship sets.

Ellipses represent attributes

Double ellipses represent multivalued attributes.

Dashed ellipses denote derived attributes.

Underline indicates primary key attributes (will study later)



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- agram t ompos te, u t va ue , an er veAttributes



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Relationship Sets with Attributes



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Roles

Entity sets of a relationship need not be distinct The labels manager and worker are called roles; they specify how

employee entities interact via the works-for relationship set.

Roles are indicated in E-R diagrams by labeling the lines that connectdiamonds to rectangles.

Role labels are optional, and are used to clarify semantics of therelationship



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Cardinality Constraints

We express cardinality constraints by drawing eithera directed line (), signifying one, or anundirected line (), signifying many, between therelationship set and the entity set.

E.g.: One-to-one relationship: A customer is associated with at most one loan via the

relationship borrower A loan is associated with at most one customer via borrower



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One-To-Many Relationship

In the one-to-many relationship a loan is associatedwith at most one customer via borrower, a customeris associated with several (including 0) loans via

borrower



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Many-To-One Relationships

In a many-to-one relationship a loan is associated with several(including 0) customers via borrower, a customer isassociated with at most one loan via borrower



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Many-To-Many Relationship

A customer is associated with several (possibly0) loans via borrower

A loan is associated with several (possibly 0)customers via borrower



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Participation of an Entity Set in a Relationship Set

Totalparticipation (indicated by double line): every entity in the entityset participates in at least one relationship in the relationship set

E.g. participation of loanin borroweris total

every loan must have a customer associated to it via borrower Partial participation: some entities may not participate in any

relationship in the relationship set

E.g. participation of customerin borroweris partial



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K e y s

Asuper key of an entity set is a set of one or moreattributes whose values uniquely determine each entity. Acandidate key of an entity set is a minimal super key

Customer-idis candidate key ofcustomer account-number is candidate key ofaccount

Although several candidate keys may exist, one of thecandidate keys is selected to be theprimary key.



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Keys for Relationship Sets

The combination of primary keys of the participatingentity sets forms a super key of a relationship set. (customer-id, account-number) is the super key ofdepositor NOTE: this means a pair of entity sets can have at most one

relationship in a particular relationship set. E.g. if we wish to track all access-dates to each account by each

customer, we cannot assume a relationship for each access. We can usea multivalued attribute though

Must consider the mapping cardinality of therelationship set when deciding the what are thecandidate keys

Need to consider semantics of relationship set inselecting the primary key in case of more than onecandidate key



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E-RDiagram with a Ternary Relationship



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Cardinality Constraints on Ternary Relationship

We allow at most one arrow out of a ternary (or greaterdegree) relationship to indicate a cardinality constraint

E.g. an arrow from works-on to job indicates eachemployee works on at most one job at any branch.

If there is more than one arrow, there are two ways ofdefining the meaning. E.g a ternary relationshipRbetweenA, B and Cwith arrows toB

and Ccould mean

1. eachA entity is associated with a unique entity fromB and Cor

2. each pair of entities from (A, B) is associated with a unique Centity, and each pair (A, C) is associated with a uniqueB

Each alternative has been used in different formalisms

To avoid confusion we outlaw more than one arrow



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Design Issues

Use of entity sets vs. attributesChoice mainly depends on the structure of the enterprise

being modeled, and on the semantics associated with the

attribute in question. Use of entity sets vs. relationship sets

Possible guideline is to designate a relationship set todescribe an action that occurs between entities

Binary versus n-ary relationship setsAlthough it is possible to replace any nonbinary (n-ary, forn > 2) relationship set by a number of distinct binaryrelationship sets, a n-ary relationship set shows moreclearly that several entities participate in a singlerelationship.

Placement of relationship attributes



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Weak Entity Sets

An entity set that does not have a primary key is referredto as a weak entity set.

The existence of a weak entity set depends on theexistence of a identifying entityset it must relate to the identifying entity set via a total, one-to-many

relationship set from the identifying to the weak entity set Identifying relationship depicted using a double diamond

The discriminator (or partial key) of a weak entity set isthe set of attributes that distinguishes among all the

entities of a weak entity set. The primary key of a weak entity set is formed by the

primary key of the strong entity set on which the weakentity set is existence dependent, plus the weak entitysets discriminator.



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Weak Entity Sets (Cont.)

We depict a weak entity set by double rectangles. We underline the discriminator of a weak entity set with a

dashed line. payment-number discriminator of thepaymententity

set Primary key forpayment (loan-number, payment-number)



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Weak Entity Sets (Cont.)

Note: the primary key of the strong entity set is not

explicitly stored with the weak entity set, since it isimplicit in the identifying relationship. Ifloan-number were explicitly stored,paymentcould be

made a strong entity, but then the relationship betweenpaymentand loan would be duplicated by an implicitrelationship defined by the attribute loan-numbercommon topaymentand loan



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More Weak Entity Set Examples

In a university, a course is a strong entity and a

course-offering can be modeled as a weak entity The discriminator ofcourse-offering would be

semester (including year) and section-number (ifthere is more than one section)

If we model course-offering as a strong entity wewould model course-number as an attribute.Then the relationship with course would be implicit

in the course-number attribute



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Specialization

Top-down design process; we designate subgroupingswithin an entity set that are distinctive from other entitiesin the set.

These subgroupings become lower-level entity sets thathave attributes or participate in relationships that do notapply to the higher-level entity set.

Depicted by a triangle component labeled ISA (E.g.customeris aperson).

Attribute inheritance a lower-level entity set inheritsall the attributes and relationship participation of thehigher-level entity set to which it is linked.



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Specialization Example



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Generalization

A bottom-up design process combine a number of entity setsthat share the same features into a higher-level entity set. Specialization and generalization are simple inversions of each

other; they are represented in an E-R diagram in the sameway.

The terms specialization and generalization are usedinterchangeably.



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Specialization and Generalization

Can have multiple specializations of an entity setbased on different features.

E.g.permanent-employeevs. temporary-employee,in addition to officervs. secretaryvs. teller

Each particular employee would be a member of one ofpermanent-employee or temporary-

employee,

and also a member of one ofofficer, secretary, or teller

The ISA relationship also referred to as superclass -subclass relationship



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Design Constraints on a Specialization/ Generalizatio

Constraint on which entities can be members of agiven lower-level entity set. condition-defined

E.g. all customers over 65 years are members ofsenior-citizen entity set; senior-citizen ISAperson.

user-defined

Constraint on whether or not entities may belongto more than one lower-level entity set within asingle generalization. Disjoint

an entity can belong to only one lower-level entity set Noted in E-R diagram by writing disjointnext to the ISA

triangle

Overlapping an entity can belong to more than one lower-level entity set



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Des gn Constra nts on a Spec a zat on Genera zat on

Completenessconstraint -- specifies whether or notan entity in the higher-level entity set must belong to

at least one of the lower-level entity sets within ageneralization. total : an entity must belong to one of the lower-level entity

sets

partial: an entity need not belong to one of the lower-levelentity sets



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Aggregation

Consider the ternary relationship works-on, which we saw earlier

Suppose we want to record managers for tasks performed by anemployee at a branch



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Aggregation (Cont.)

Relationship sets works-on and manages representoverlapping information Everymanages relationship corresponds to a works-on relationship

However, some works-on relationships may not correspond to anymanages relationships

So we cant discard the works-on relationship

Eliminate this redundancy via aggregation Treat relationship as an abstract entity

Allows relationships between relationships

Abstraction of relationship into new entity

Without introducing redundancy, the following diagramrepresents: An employee works on a particular job at a particular branch

An employee, branch, job combination may have an associatedmanager



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E-R Diagram With Aggregation



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E-R Design Decisions

The use of an attribute or entity set to represent anobject.

Whether a real-world concept is best expressed by anentity set or a relationship set.

The use of a ternary relationship versus a pair of binaryrelationships.

The use of a strong or weak entity set. The use of specialization/generalization contributes to

modularity in the design. The use of aggregation can treat the aggregate entity

set as a single unit without concern for the details of itsinternal structure.



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E-R Diagram for a Banking Enterprise



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Summary of Symbols Used in E-R Notation



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Summary of Symbols (Cont.)



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Alternative E-R Notations



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Reduction of an E-R Schema to Tables

Primary keys allow entity sets and relationship sets tobe expressed uniformly as tableswhich represent thecontents of the database.

A database which conforms to an E-R diagram can berepresented by a collection of tables. For each entity set and relationship set there is a

unique table which is assigned the name of thecorresponding entity set or relationship set.

Each table has a number of columns (generallycorresponding to attributes), which have uniquenames.

Converting an E-R diagram to a table format is thebasis for deriving a relational database design from anE-R diagram.



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Representing Entity Sets as Tables

A strong entity set reduces to a table with the sameattributes.



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Composite and Multivalued Attributes

Composite attributes are flattened out by creating aseparate attribute for each component attribute E.g. given entity set customer with composite attribute name with

component attributesfirst-name and last-name the tablecorresponding to the entity set has two attributes

name.first-name and name.last-name

A multivalued attribute M of an entity E is representedby a separate table EM Table EM has attributes corresponding to the primary key of E and

an attribute corresponding to multivalued attribute M E.g. Multivalued attribute dependent-names ofemployee is

represented by a tableemployee-dependent-names( employee-id, dname)

Each value of the multivalued attribute maps to a separate row ofthe table EM E.g., an employee entity with primary key John and

dependents Johnson and Johndotir maps to two rows:(John, Johnson) and (John, Johndotir)



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Representing Weak Entity Sets

A weak entity set becomes a table that includes a column forthe primary key of the identifying strong entity set



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Representing Relationship Sets as Tables

A many-to-many relationship set is represented as a table withcolumns for the primary keys of the two participating entity sets,and any descriptive attributes of the relationship set.

E.g.: table for relationship set borrower



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Redundancy of Tables

Many-to-one and one-to-many relationship sets that are totalon the many-side can be represented by adding an extraattribute to the many side, containing the primary key of theone side

E.g.: Instead of creating a table for relationship account-branch, add an attribute branchto the entity set account



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Redundancy of Tables (Cont.)

For one-to-one relationship sets, either side can bechosen to act as the many side That is, extra attribute can be added to either of the tables

corresponding to the two entity sets

If participation ispartialon the many side,replacing a table by an extra attribute in the relationcorresponding to the many side could result in null

values The table corresponding to a relationship set linking

a weak entity set to its identifying strong entity set is

redundant. E.g. Thepaymenttable already contains the information that

would appear in the loan-paymenttable (i.e., the columnsloan-number andpayment-number).



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Representing Specialization as Tables

Method 1:

Form a table for the higher level entity

Form a table for each lower level entity set, include primary key ofhigher level entity set and local attributes

table table attributesperson name, street, citycustomer name, credit-ratingemployee name, salary

Drawback: getting information about, e.g., employee requiresaccessing two tables



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Representing Specialization as Tables

Method 2: Form a table for each entity set with all local and inherited attributes

table table attributes

person name, street, citycustomer name, street, city, credit-ratingemployee name, street, city, salary

If specialization is total, table for generalized entity (person) notrequired to store information

Can be defined as a view relation containing union of

specialization tables But explicit table may still be needed for foreign key constraints

Drawback: street and city may be stored redundantly for personswho are both customers and employees



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Relations Corresponding to Aggregation

To represent aggregation, create a table containing

primary key of the aggregated relationship,

the primary key of the associated entity set

Any descriptive attributes



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Relations Corresponding to Aggregation

E.g. to represent aggregation managesbetween relationshworks-onand entity set manager, create a tablemanages(employee-id, branch-name, title, manager-name

Table works-onis redundant provided we are willing to stonull values for attribute manager-namein table manages



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RELATIONAL MODEL

Structure of Relational Databases

Relational Algebra

Tuple Relational Calculus Domain Relational Calculus

Extended Relational-Algebra-Operations

Modification of the Database

Views



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EXAMPLE OF A RELATION



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BASIC STRUCTURE

Formally, given sets D1, D2, . Dn a relation ris a subsetofD1 x D2 x x Dn

Thus a relation is a set of n-tuples (a1, a2, , an) whereeach ai Di

Example: if

customer-name = {Jones, Smith, Curry, Lindsay}customer-street = {Main, North, Park}customer-city = {Harrison, Rye, Pittsfield}

Thenr= { (Jones, Main, Harrison),

(Smith, North, Rye),(Curry, North, Rye),(Lindsay, Park, Pittsfield)}

is a relation overcustomer-name x customer-street xcustomer-city



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ATTRIBUTE TYPES

Each attribute of a relation has a name

The set of allowed values for each attribute is called thedomain of the attribute

Attribute values are (normally) required to be atomic,that is, indivisible E.g. multivalued attribute values are not atomic

E.g. composite attribute values are not atomic

The special value null is a member of every domain

The null value causes complications in the definition ofmany operations we shall ignore the effect of null values in our main

presentation and consider their effect later



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RELATION SCHEMA

A1,A2, ,Anare attributes

R = (A1,A2, ,An ) is arelation schema

E.g. Customer-schema =(customer-name, customer-street,

customer-city)

r(R) is arelation on therelation schema R

E.g. customer (Customer-schema)



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RELATION INSTANCE

The current values (relation instance) of arelation are specified by a table

An element t ofris a tuple, represented by arow in a table

JonesSmithCurry

Lindsay

customer-name

MainNorthNorthPark

customer-street

HarrisonRyeRye

Pittsfield

customer-city

customer

attributes(or columns)

tuples

(or rows)



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RELATIONS ARE UNORDERED

Order of tuples is irrelevant (tuples may be stored in an arbitrary order

E.g. accountrelation with unordered tuples



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DATABASE

A database consists of multiple relations Information about an enterprise is broken up into parts, with

each relation storing one part of the information

E.g.: account : stores information about accountsdepositor: stores information about which

customerowns which account

customer: stores information about customers Storing all information as a single relation such as

bank(account-number, balance, customer-name, ..)results in repetition of information (e.g. two customers own an account) the need for null values (e.g. represent a customer without an

account)

Normalization theory deals with how to design relationalschemas



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THE CUSTOMER RELATION



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THE DEPOSITOR RELATION



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E-R DIAGRAM FOR THE BANKINGENTERPRISE



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SCHEMA DIAGRAM FOR THE BANKINGENTERPRISE



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QUERY LANGUAGES

Language in which user requests information from

the database.

Categories of languages

procedural

non-procedural

Pure languages:

Relational Algebra

Tuple Relational Calculus

Domain Relational Calculus

Pure languages form underlying basis of querylanguages that people use.



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RELATIONAL ALGEBRA

Procedural language

Six basic operators

select

project

union

set difference

Cartesian product

rename

The operators take one or more relations as inputsand give a new relation as a result.



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SELECT OPERATION EXAMPLE

Relation r A B C D

1

5

12

23

7

7

3

10

A=B ^ D > 5(r)A B C D

1

23

7

10



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SELECT OPERATION

Notation: p(r)

p is called the selection predicate

Defined as:

p(r) = {t | trand p(t)}

Where p is a formula in propositionalcalculus consisting of terms connected by : (and), (or), (not)Each term is one of:

op or

where op is one of: =, , >, .


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PROJECT OPERATION EXAMPLE

Relation r: A B C

10

20

30

40

1

1

1

2

A C

1

1

1

2

=

A C

1

1

2

A,C (r)



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PROJECT OPERATION

Notation:

A1, A2, , Ak (r)

whereA1, A2 are attribute names andris a relationname.

The result is defined as the relation of k columnsobtained by erasing the columns that are not listed

Duplicate rows removed from result, since relationsare sets

E.g. To eliminate the branch-name attribute ofaccount

account-number, balance (account)Copyright @ www.bcanotes.com


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UNION OPERATION EXAMPLE

Relationsr, s:

r s:

A B

12

1

A B

23

r

s

A B

1

2

1

3



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UNION OPERATION

Notation: rs

Defined as:

r s = {t | trorts}

Forrs to be valid.

1. r,s must have thesame arity (same number of

attributes)2. The attribute domains must be compatible (e.g.,2nd column

ofrdeals with the same type of values as doesthe 2nd

column ofs) Copyright @ www.bcanotes.com


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SET DIFFERENCE OPERATION EXAMPLE

Relationsr, s:

r s:

A B

12

1

A B

23

r

s

A B

1

1



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SET DIFFERENCE OPERATION

Notationrs

Defined as:

rs = {t | trand t s}

Set differences must be taken between compatiblerelations.

rands must have thesame arity

attribute domains ofrands must be compatible



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CARTESIAN-PRODUCTOPERATION-EXAMPLE

Relations r, s:

rx s:

A B

1

2

A B

1

1112222

C D

10

10201010102010

E

a

abbaabb

C D

10

102010

E

a

abbr

s



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CARTESIAN-PRODUCT OPERATION

Notation rx s

Defined as:

rxs = {t q | t rand q s}

Assume that attributes of r(R) and s(S) are disjoint.(That is,R S = ).

If attributes ofr(R) ands(S) are not disjoint, thenrenaming must be used.



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COMPOSITION OF OPERATIONS

Can build expressions using multiple operations

Example: A=C(r x s)

r x s

A=C(r x s)

A B

1111222

2

C D

10102010101020

10

E

aabbaab

b

A B C D E

122

102020

aab



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RENAME OPERATION

Allows us to name, and therefore to refer to, the

results of relational-algebra expressions.

Allows us to refer to a relation by more than onename.

Example:

x (E)

returns the expression E under the nameXIf a relational-algebra expression E has arity n, then

x(A1, A2, , An) (E)

returns the result of expression E under the nameX,and with the

attributes renamed toA1, A2, ., An.Copyright @ www.bcanotes.com


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BANKING EXAMPLE

branch (branch-name, branch-city, assets)

customer (customer-name, customer-street,customer-only)

account (account-number, branch-name,balance)

loan (loan-number, branch-name, amount)

depositor (customer-name, account-number)

borrower (customer-name, loan-number)



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EXAMPLE QUERIES

Find all loans of over $1200

Find the loan number for each loan of an amount greater than

$1200

amount> 1200 (loan)

loan-number

(amount

> 1200 (loan))



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EXAMPLE QUERIES

Find the names of all customers who have a loan,

an account, or both, from the bank

Find the names of all customers who have a loan and an

account at bank.

customer-name (borrower) customer-name (depositor)

customer-name

(borrower) customer-name

(depositor)



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EXAMPLE QUERIES

Find the names of all customers who have a loan atthe Perryridge branch.

Find the names of all customers who have a loan at thePerryridge branch but do not have an account at any branch ofthe bank.

customer-name(branch-name = Perryridge(borrower.loan-number = loan.loan-number(borrower x loan))) customer-name(depositor)

customer-name(branch-name=Perryridge(borrower.loan-number = loan.loan-number(borrower x loan)))



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EXAMPLE QUERIES

Find the names of all customers who have a loan at thPerryridge branch.

Query 2

customer-name(loan.loan-number = borrower.loan-number((branch-name = Perryridge(loan)) x borrower))

Query 1

customer-name(branch-name = Perryridge(borrower.loan-number = loan.loan-number(borrower x loan)))



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EXAMPLE QUERIES

Find the largest account balance

Rename account relation as d

The query is:balance(account) - account.balance

(account.balance < d.balance(account xd(account)))



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FORMAL DEFINITION

A basic expression in the relational algebra consists

of either one of the following: A relation in the database

A constant relation

Let E1 and E2 be relational-algebra expressions; thefollowing are all relational-algebra expressions:

E1E2

E1 - E2

E1 x E2

p (E1), P is a predicate on attributes in E1

s(E1), S is a list consisting of some of the attributes in E1 x(E1), x is the new name for the result of E1



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ADDITIONAL OPERATIONS

We define additional operations that do not addany power to the

relational algebra, but that simplify commonqueries.

Set intersection

Natural join

Division

Assignment



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SET-INTERSECTION OPERATION

Notation:rs

Defined as:

rs ={ t | trandts }

Assume:

r,s have thesame arity

attributes of r and s are compatible

Note:rs =r- (r-s)



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SET-INTERSECTION OPERATION -EXAMPLE

Relation r, s:

r s

A B

121

A B

2

3

r s

A B

2



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Notation: r s

NATURAL-JOIN OPERATION

Letrands be relations on schemas R and Srespectively.

Then, r s is a relation on schema R S obtainedas follows: Consider each pair of tuples trfromrand ts froms.

If trand ts have the same value on each of the attributes inRS, add a tuple t to the result, where

t has the same value as tronr

t has the same value as ts ons

Example:

R = (A, B, C, D)

S = (E, B, D)

Result schema = (A, B, C, D, E)

r s is defined as: Copyright @ www.bcanotes.com


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NATURAL JOIN OPERATION EXAMPLE

Relations r, s:

A B

12412

C D

aabab

B

13123

D

aaabb

E

r

A B

11112

C D

aaaab

E

s

r s



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DIVISION OPERATION

Suited to queries that include the phrasefor all.

Letrands be relations on schemas R and Srespectively where R = (A1, ,Am, B1, , Bn)

S = (B1, , Bn)

The result of r s is a relation on schema

RS = (A1, ,Am)

rs = { t | t R-S(r) u s ( tu r) }

rs



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DIVISION OPERATION EXAMPLE

Relations r, s:

rs: A

B

1

2

A B

1

23111346

12

r

s



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ANOTHER DIVISION EXAMPLE

A B

aaaaaaaa

C D

aabababb

E

11113111

Relations r, s:

rs:

D

ab

E

11

A B

aa

C

r

s



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DIVISION OPERATION (CONT.)

Property Let qr s

Then q is the largest relation satisfying q xsr

Definition in terms of the basic algebraoperationLetr(R) ands(S) be relations, and let S R

rs = R-S (r)R-S ( (R-S(r) xs)R-S,S(r))

To see why R-S,S(r) simply reorders attributes ofr

R-S(R-S(r) xs)R-S,S(r)) gives those tuples t in

R-S(r) such that for some tuple u s, tu r.Copyright @ www.bcanotes.com


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ASSIGNMENT OPERATION

The assignment operation () provides a convenient wayto express complex queries. Write query as a sequential program consisting of

a series of assignments

followed by an expression whose value is displayed as a resultof the query.

Assignment must always be made to a temporary relationvariable.

Example: Writers as

temp1R-S (r)

temp2 R-S ((temp1 xs)R-S,S(r))

result = temp1temp2

The result to the right of the is assigned to the relation variable

on the left of the .

May use variable in subsequent expressions.



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EXAMPLE QUERIES

Find all customers who have an account from atleast the Downtown and the Uptownbranches.

where CNdenotes customer-name and BNdenotes

branch-name.

Query 1

CN(BN=Downtown(depositor account))

CN(BN=Uptown(depositor account))

Query 2

customer-name, branch-name(depositor account)

temp(branch-name) ({(Downtown), (Uptown)})



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EXAMPLE QUERIES

Find all customers who have an account at all

branches located in Brooklyn city.

customer-name, branch-name(depositor account)

branch-name(branch-city= Brooklyn (branch))



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VIEWS

In some cases, it is not desirable for all users tosee the entire logical model (i.e., all the actualrelations stored in the database.)

Consider a person who needs to know acustomers loan number but has no need to seethe loan amount. This person should see arelation described, in the relational algebra, by

customer-name, loan-number(borrower loan)

Any relation that is not of the conceptual modelbut is made visible to a user as a virtual relationis called a view.



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VIEW DEFINITION

A view is defined using the create view statement

which has the form

create view v as


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VIEW EXAMPLES

Consider the view (named all-customer)consisting of branches and their customers.

We can find all customers of the Perryridge branch by writing:

create viewall-customer

as

branch-name, customer-name(depositor account)

branch-name, customer-name(borrower loan)

customer-name(branch-name= Perryridge(all-customer))



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UPDATES THROUGH VIEW

Database modifications expressed as views must be

translated to modifications of the actual relations inthe database.

Consider the person who needs to see all loan datain the loan relation except amount. The view givento the person, branch-loan, is defined as:

create view branch-loan as

branch-name, loan-number(loan)

Since we allow a view name to appear wherever arelation name is allowed, the person may write:

branch-loan branch-loan {(Perryridge, L-Copyright @ www.bcanotes.com


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TUPLE RELATIONAL CALCULUS

A nonprocedural query language, where eachquery is of the form

{t | P (t) } It is the set of all tuples t such that predicate P is

true fort

t is a tuple variable, t[A] denotes the value of tuplet on attributeA

trdenotes that tuple t is in relationr

P is a formula similar to that of the predicatecalculus



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PREDICATE CALCULUS FORMULA

1. Set of attributes and constants

2. Set of comparison operators: (e.g., , , , , ,)

3. Set of connectives: and (), or (v) not ()

4. Implication (): x y, if x if true, then y is true

xyx v y

5. Set of quantifiers: t r (Q(t)) there exists a tuple in t in relationr

such that predicate Q(t) is true

t r(Q(t)) Qis true for all tuples t in relationr



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BANKING EXAMPLE

branch (branch-name, branch-city, assets)

customer (customer-name, customer-street,customer-city)

account (account-number, branch-name,balance)

loan (loan-number, branch-name, amount)

depositor (customer-name, account-number) borrower (customer-name, loan-number)



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EXAMPLE QUERIES

Find the loan-number, branch-name, andamount for loans of over $1200

Find the loan number for each loan of an amount greater than $1200

Notice that a relation on schema [loan-number] is implicitly definedby the query

{t |sloan (t[loan-number] = s[loan-number] s[amount] 1200)}

{t| tloant[amount] 1200}



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Evolutionof DistributedDatabase Management System

During the 1970s, corporations implementedcentralized database management systems tomeet their structured information needs.

Structured information is usually presented asregularly issued formal reports in a standard

format.

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The use of centralized database required that corporatedata be stored in a single central site, usually a mainframecomputer.

Data access was provided through serially connecteddumb terminals.

The centralized approach worked well to fill thestructured information needs of corporations, but it felshort when quickly moving events required faster reponsetimes and equally quick access to information.



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The 1980s gave birth to a series of crucial social andtechnological changes that affected database developmentand design, such as:

Business operations became more decentralizedgeographically.

Competition increased at the global level.

Customer demands and market needs favored adecentralized management style.



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Rapid technological change low costmainframe.

The large number of applications based on DBMSand the need to protect investments in centralizedDBMS software made the notion of data sharing

attractive.



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During 1990s the factors we have just described becameeven more firmly pressured. However, how these factorswere addressed was strongly influenced by:

The growing acceptance of internet and, particularly, theWWW, as the platform for data access and distribution. TheWWW is, in effect, the repository for distributed data.

The increased focus on data analysis that led to data miningand warehousing. Although a data warehouse is not usually adistributed database, it does rely on techniques-such as datareplication and distributed queries-that facilitate its dataextraction and integration.



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The decentralized database is especially desirable becausecentralized database management is subject to problemssuch as:

Performance degradation due to a growing number oremote locations over greater distance.

High Cost associated with maintaining and operatinglarge central (mainframe) database systems.

Reliability problems created by dependence on centrasite.



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Advantages of DDBMS

Data are located near thegreatestdemandsite:

The data in a distributed database system ar

dispersed to match business requirements.



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Faster Data Processing:A distributed database system makes it possible tprocess data at several sites, thereby spreading outhe systems workload.



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Faster Data Access:

End users often work with only a subset of thcompanys data. If such data subsets are locally storeand accessed, the database system will deliver fast

data access than is possible with remotely locatecentralized data.



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Growth Facilitation:New sites can be added to the network withouaffecting the operations of other sites. Such flexibilitenables the company to expand relatively easily and

rapidly.



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Improved Communications:Because local sites are smaller and located closer tocustomers, local sites foster better communicationsamong departments and between customers and

company staff. Quicker and better communicationoften help to improve information systems.



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Reduced operating costs:It is much more cost-effective to add workstations ta network than to update a mainframe system. Thcost of dedicated data communication lines and

mainframe software is reduced proportionallyDevelopment work is done more cheaply and morquickly on low-cost PCs than on mainframe.



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User Friendly Interface:PCs and workstations are usually endowed with aeasy-to-use GUI. The GUI simplifies use and trainin

for end users.



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Less danger of a single-pointfailure: In a centralized system, thmainframes failure brings down all the systemoperations. In contrast, a distributed system is able

to shift operations when one of the computefails.The system workload picked up by otheworkstations, because one of the distributed systemfeatures is that data exist at multiple sites.



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Proce

dbms basic reference

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