Com 312 Lecture Notes2010

8/2/2019 Com 312 Lecture Notes2010

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Chapter 1

INTRODUCTION TO DATABASE

Learning Objectives: After reading and studying this chapter you should be able to:

Define Database Define Database management system (DBMS) State various Database system applications Explain purpose of database system Explain the factors driving development of database systems Describe briefly the history of database systems Explain modern organizations needs for information

State the benefits of DBMS1.1 What is a Database?

A database can be termed as a repository (or a store) of data. A collection of

actual data which constitutes the information regarding an organisation is stored in a

database (see figure 1.1). For example, there are 1000 students in a college & we have to

store their personal details, marks details etc., these details will be recorded in a

database.

Database: A Formal Definition

Several definitions could be given for the term database, but let us examine the

following definition:

A database is an ordered collection of related data elements intended to meet the

information needs of an organization and designed to beshared by multiple users.

Note the key terms in the definition:

Ordered collection. A database is a collection of data elements. Not just a random

assembly of data structures, but a collection of data elements put together deliberately

with proper order. The various data elements are linked together in the most logical

manner.

Related data elements. The data elements in a database are not disjointed structures

without any relationships among them. These are related among themselves and also

pertinent to the particular organization.

Information needs. The collection of data elements in a database is there for a specific

purpose. That purpose is to satisfy and meet the information needs of the organization. In


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1.3 Database System Applications

There are many different types of DBMSs, ranging from small systems that run on

personal computers to huge systems that run on mainframes. Databases are applied in

wide no. of applications. Following are some of the examples:-

Banking: For customer information, accounts, loans & other banking transactions

Airlines: For reservation & schedule information

Universities: For student information, course registration, grades etc.

Credit card transaction: For purchase of credit cards & generation of monthly

statements.

Telecommunication: For keeping records of calls made, generating monthly bill etc.

Finance: For storing information about holdings, sales & purchase of financial statements

Sales: For customer, product & purchase information

Manufacturing: For management of supply chain.

Human Resource: For recording information about employees, salaries, tax, benefits etc.

We can say that whenever we need to have a computerised system, we need a

database system

1.4 Purpose of Database system

Before the evolution of DBMS, organisations used to store information in file-oriented

systems. A file-oriented system is one in which we keep the information in files. A typical file

processing system is supported by a conventional operating system. The system stores

permanent records in various files & it need application program to extract records, or to

add or delete records. We will compare both systems with the help of an example.

Assume there is a saving bank enterprise that keeps information about all customers

& saving accounts. Following manipulations has to be done with the system

A program to debit or credit an account A program to add a new account.

A program to find balance of an account.

A program to generate monthly statements.

As the need arises new applications can be added at a particular point of time for

example current account deposit can be added into a saving account of customers who

want lodge cheque into their savings. Using file system for storing data has got following

disadvantages:-


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1.Data Redundancy & Inconsistency:-

Different programmers work on a single project, so various files is created by

different programmers at some interval of time. These files are created in different formats

& different programs are written in different programming languages.

Also same information is repeated in these different files. For example name &

address may appear in saving account file as well as in current account file. This

redundancy results in higher storage space & access cost. It also leads to data

inconsistency which means that if we change some record in one place the change will

not be reflected in all the places. For example, a changed customer address may be

reflected in saving record but not anywhere else.

2. Difficulty in accessing data

Accessing data from a list is also a difficulty in file-oriented system. Suppose we

want to see the records of all customers who has a balance less than N10,000, we can

either check the list & find the names manually or write an application program. If we

write an application program & at some later time, we need to see the records of

customer who have a balance of less than N20,000, then again a new program has to be

written. It means that file processing system do not allow data to be accessed in a

convenient manner.

3. Data IsolationAs the data is stored in various files, & various files may be stored in different format,

writing application program to retrieve the data is difficult.

4. Integrity Problems

Sometimes, we need that data stored should satisfy certain constraints as in a bank

a minimum deposit should be of N1000. Developers enforce these constraints by writing

appropriate programs but if later on some new constraint has to be added then it is

difficult to change the programs to enforce them.

5. Atomicity Problems

Any mechanical or electrical device is subject to failure, and so is the computer

system. In this case we have to ensure that data should be restored to a consistent state.

For example an amount of N50 has to be transferred from Account A to Account B.

Assume this amount has been debited from account A but have not been credited to

Account B and in the mean time, some failure occurred. So, it will lead to an inconsistent

state. So, we have to adopt a mechanism which ensures that either full transaction should


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be executed or no transaction should be executed i.e. the fund transfer should be

atomic.

6. Concurrent access Problems

Many systems allow multiple users to update the data simultaneously. It can also

lead to data being in an inconsistent state. Suppose a bank account contains a balance

of N500 & two customers want to withdraw N100 & N50 simultaneously from that same

balance. Both the transaction reads the old balance( i.e. 500) & withdraw from that old

balance which will result in N 450 & N 400 which is incorrect.

7. Security Problems

All the user of database should not be able to access all the data. For example a

payroll personnel needs to access only that part of data which has information about

various employees & are not needed to access information about customer accounts.

1.5 The Driving Forces for Database system Development

Among others, four major forces drove organizations to adopt database systems (see

Figure 1-3 )

Information as a Corporate Asset. Today, companies strongly realize that information is a

corporate asset similar to other assets such as cash, plant and equipment, or inventory.

Proper management of key assets is essential for success. Companies understand that it is

essential to manage information as a key asset. They understand the need to findimproved methods for storing, retrieving, and using information.

Explosive Growth of Computer Technology. Computer technology, especially data

storage and retrieval systems, has grown in a phenomenal manner. Without growth in this

sector, it is unlikely that we could have progressed to database systems that need

sophisticated ways of data storage and retrieval.

Escalating Demand for Information. We have noted the increase in demand for

information by organizations, not only in volume but in the types of information as well. If

companies did not need more and newer types of information, there would

have been no impetus for development of database systems.The earlier data systems

might have been satisfactory.

Inadequacy of Earlier Data Systems. Suppose the earlier data systems were able to meet

the escalating demand for information. Then why bother to find better methods? But the

fact is that these earlier systems were grossly inadequate to meet the information

demands. Storage and management of large volumes of data were not adequate.


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Finding and retrieving information were extremely difficult. Protecting the information

asset of a company was nearly impossible with the earlier data systems. Why was this so?

How were the earlier systems inadequate? In what ways could they not meet the

information demands? Understanding the limitations will give you a better appreciation

for database systems.

Figure 1.3: Forces behind development of Database systems

1.6 History of Database systems

Before the advent of computers business organizations kept records of their

businesses in manual files. With the incoming of the computer, these manual files were

converted to computer files using file-oriented systems. However, the problems with file

processing system, growth in computer technology, increased demand for information

encouraged the development of database systems

Though the initial movement toward database systems began in the 1960s,software sophistication and widespread use of database systems began in the mid-1970s.

More and more organizations began to adopt database technology to manage their

corporate data. Figure 1.4 provides you with a historical summary of the database

industry. The figure highlights the major events and developments in the various decades.

Generalized Update Access Method (GUAM) contained the first trace of the

forerunner to the hierarchical database systems. In early 1960s, Rockwell developed this

software to manage the data usually associated with manufacturing operations. IBM

picked this up and introduced Information Management System (IMS) as a hierarchical

database management system. Integrated Data Store (IDS), developed at General

Electric, formed the basis for database systems on the network data model. Database

Task Group (DBTG) of the Conference on Data Systems and Languages (CODASYL)

began to produce standards for the network model. CODASYL, a consortium of vendors

and leading businesses, serves as a group to establish standards. Among the many

standards established, a major contribution by CODASYL is the set of standards for


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COBOL, a leading programming language. In the late 1960s, vendors started to release

the first generation of commercial database systems supporting the network data model.

Cincoms TOTAL database management system is a primary example.

The 1970s ushered in the era of relational database technology. Dr. Codds

foundational paper on the relational model revolutionized the thinking on data systems.

The industry quickly realized the superiority of the relational model, and more and more

vendors began to adapt their products to that model. During the 1980s, the use of

database systems gained a lot of ground and a large percentage of businesses made

the transition from file-oriented data systems to database systems. All the three leading

data modelshierarchical, network, and relationalwere quite popular, although the

relational model was steadily gaining ground.

Essentially the 1990s may be considered as a period of maturity of the relational

model and the emergence of that data model as the leading one. Companies

considered moving their data to relational databases from hierarchical and network

databases. Also, vendors started to incorporate the features of both relational and object

technologies in their products. Object-relational database management systems

(ORDBMSs) hit the market. Now in the new millennium, the usage of database technology

is spreading into newer areas. Properly designed databases serve as a chief component

in data warehousing (DW), enterprise resource planning (ERP), data mining (DM), on-lineanalytical processing (OLAP), and customer relationship management (CRM)

applications.

Figure 1.4: history of database systems


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1.7 Organizations Demand for Information

In globalised economy and competitive market of today, organizations are faced

with increasing demand for information. This need for information is of several dimensions.

Consider how billing requirements and sales analysis have changed. In the early years of

computing, organizations were happy if they could bill their customers once a month and

review total sales by product quarterly. Now it is completely different. Organizations must

bill every sale right away to keep up the cash flow. They need up-to-date customer

balance and daily and cumulative sales totals by products. What about inventory

reconciliation? Earlier systems provided reports to reconcile inventory or to determine

profitability only at the end of each month. Now organizations need daily inventory

reconciliation to manage inventory better, daily profitability analysis to plan sales

campaigns, and daily customer information to improve customer service.

In the earlier period of computing, organizations were satisfied with information

showing only current activity. They could use the information to manage day-to-day

business and make operational decisions. In the changed business climate of

globalization and fierce competition, this type of information alone is no longer

adequate. Companies need information to plan and shape their future. They need

information, not just to run day-to-day operations, but to make strategic decisions as well.What about the delivery of information now compared to the early days of computing?

Today, online information is the norm for most companies. Fast response times and access

to large volumes of data have become essential. Earlier computer systems just provided

reports, mostly once a month, a few once a week, and a small number once a day.

Organizations have come to realize that information is a key asset to be carefully

managed and used for greater profitability.

In summary, demand for information by todays enterprises contains the following

attributes:

More information

Information newer purposes

Different information types

Integrated information

Information to be shared

Faster access to information


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Data Sharing This benefit of database systems follows from data integration. The various

departments in any enterprise need to share the companys data for proper

functioning.The sales department needs to share the data generated by the accounting

department through the billing application. Consider the customer service department. It

needs to share the data generated by several applications. The customer service

application needs information about customers, their orders, billings, payments, and

credit ratings. With data integration in a database, the application can get data from

distinct and consolidated data structures relating to customer, orders, invoices, payments,

and credit status.

Data sharing is a major benefit of database systems. Each department shares the

data in the database that are most pertinent to it. Departments may be interested

in data structures as follows:

Sales departmentCustomer/Order

Accounting departmentCustomer/Order/Invoice/Payment

Order processing departmentCustomer/Product/Order

Inventory control departmentProduct/Order/Stock Quantity/Back Order

Quantity

Database technology lets each application use the portion of the database that is

needed for that application. User views of the database are defined and controlled. Wewill have more to say about user views in later chapters.

Uniform Standards We have seen that, because of the spread of duplicate data across

applications in file-oriented data systems, standards cannot be enforced easily and

completely. Database systems remove this difficulty. As data duplication is controlled in

database systems and as data is consolidated and integrated, standards can be

implemented more easily. Restrictions and business rules for a single data element need

to be applied in only one place. In database systems, it is possible to eliminate problems

from homonyms and synonyms.

Security Controls Information is a corporate asset and, therefore, must be protected

through proper security controls. In file-oriented systems, security controls cannot be

established easily. Imagine the data administrator wanting to restrict and control the use

of data relating to employees. In file-oriented systems, control has to be exercised in all

applications having separate employee files. However, in a database system, all data

about employees are consolidated, integrated, and kept in one place. Security controls


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on employee data need to be applied in only one place in the database. Database

systems make centralized security controls possible. It is also easy to apply data access

authorizations at various levels of data.

Data Independence Remember the lack of data independence in file-oriented systems

where computer programs have data structure definitions embedded within the

programs themselves. In database systems, file or data definitions are separated out of

the programs and kept within the database itself. Program logic and data structure

definitions are not intricately bound together. In a client/server environment, data and

descriptions of data structures reside on the database server ,whereas the code for

application logic executes on the client machine or on a separate application server.

Reduced Program Maintenance: This benefit of database systems results primarily from

data independence in applications. If the customer data structure changes by the

addition of a field for cellular phone numbers, then this change made in only one place

within the database itself. Only those programs that need the new field need to be

modified and recompiled to make use of the added piece of data. Within limits, you can

change programs or data independently.

Simpler Backup and Recovery In a database system, generally all data are in one place.

Therefore, it becomes easy to establish procedures to back up data. All the relationships

among the data structures are also in one place. The arrangement of data in databasesystems makes it easier not only for backing up the data but salso for initiating procedures

for recovery of data lost because of malfunctions.

POINTS TO PONDER

A DBMS contains collection of inter-related data & collection of programs to access the

data.

The primary goal of DBMS is to provide an environment that is both convenient &

efficient for people to use in retrieving & storing information.

DBMS systems are ubiquitous today & most people interact either directly or indirectly

with database many times every day.

Database systems are designed to store large bodies of information.

A major purpose of a DBMS is to provide users with an abstract view of data i.e. the

system hides how the data is stored & maintained.


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REVIEW TERMS

Database

DBMS

Database System Application

File System

Data Inconsistency

Consistency constraints

Atomicity

Redundancy

Data isolation

Data Security

STUDENTS ACTIVITY1)What is database? Explain with example?

2)What is DBMS? Explain with example?

3)List four significant difference between file system & DBMS?

4)What are the advantages of DBMS?

5)Explain various applications of database?

6)Explain data inconsistency with example?

7)Explain data security? Why it is needed? Explain with example

8 Explain isolation & atomicity property of database?

9)Explain why redundancy should be avoided in database?

10)Explain consistency constraints in database?

STUDENTS NOTES

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Chapter 2

DATA ABSTRACTION AND DATABASE LANGUAGES

Learning objectives: After reading and studying this chapter you should be able to:

Define data abstraction

Explain Physical level of data abstraction Explain Logical level of data abstraction Explain View level of data abstraction Define query language Describe Data Definition Language Describe Data Manipulation Language

2.1 VIEW OF DATA

A database system contains a no. of files & certain programs to access & modify

these files. But the actual data is not shown to the user, the system hides actual details of

how data is stored & maintained.

2.2 DATA ABSTRACTION

Data abstraction is the process of distilling data down to its essentials. The data

when needed should be retrieved efficiently. As all the details are not of use for all the

users, so we hide the actual (complex) details from users. Various level of abstraction to

data is provided which are listed below:-

Physical level:- It is the lowest level of abstraction & specifies how the data is actually

stored. It describes the complex data structure in details.

Logical level: - It is the next level of abstraction & describes what data are stored in

database & what relationship exists between various data. It is less complex than physical

level & specifies simple structures. Though the complexity of physical level is required at

logical level, but users of logical level need not know these complexities.

View level:- This level contains the actual data which is shown to the users. This is the

highest level of abstraction & the user of this level need not know the actual details

(complexity) of data storage.


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2.3 Database Language

As a language is required to understand any thing, similarly to create or manipulate

a database we need to learn a language. Database language is divided into mainly 2

parts :-

1)DDL (Data definition language)

2)DML (Data Manipulation language)

Data Definition Language (DDL)

Used to specify a database scheme as a set of definitions expressed in a DDL

1. DDL statements are compiled, resulting in a set of tables stored in a special file called a

data dictionary ordata directory.

2. The data directory contains meta data (data about data)3. The storage structure and access methods used by the database system are specified

by a set of definitions in a special type of DDL called a data storage and definition

language

4. Basic idea: hide implementation details of the database schemes from the users

Data Manipulation Language (DML)

1. Data Manipulation includes:

retrieval of information from the database insertion of new information into the database deletion of information in the database modification of information in the database

2. A DML is a language which enables users to access and manipulate data. The goal is

to provide efficient human interaction with the system.

3. There are two types of DML:

procedural: the user specifies what data is needed and how to get it nonprocedural: the user only specifies what data is needed. It easier for user and

may not generate code as efficient as that produced by procedural languages

4. A query language is a portion of a DML involving information retrieval only. The terms

DML and query language are often used synonymously.


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POINTS TO PONDER

DBMS systems are ubiquitous today & most people interact either directly or indirectly

with database many times every day.

Database systems are designed to store large bodies of information.

A major purpose of a DBMS is to provide users with an abstract view of data i.e. the

system hides how the data is stored & maintained.

Structure of a database is defined through DDL. & manipulated through DML.

DDL statements are compiled, resulting in a set of tables stored in a special file called a

data dictionary ordata directory.

A query language is a portion of a DML involving information retrieval only. The terms

DML and query language are often used synonymously.

REVIEW TERMS

Data Security

Data Views

Data Abstraction

Physical level

Logical level

View level

Database language

DDL DML Query language

STUDENTS ACTIVITY

1) Define data abstraction?

2)How many views of data abstraction are there? Explain in details?

3)Explain database language? Differentiate between DDL & DML?

STUDENTS NOTES

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Chapter 3

DATABASE CONCEPTS


Define Data dictionary

Define Meta data Explain Database schema Distinguish different types of schema: physical schema, logical schema, subschema Define Database Instance Explain the term metadata Explain Data independence Differentiate logical data independence and physical data independence

Data Repository All data in the database reside in a data repository. This is the data

storage unit where physical data files are kept. The data repository contains the physical

data. Mostly, it is a central place of storage for the data content.

Data Dictionary The data repository contains the actual data. Let us say that you want to

keep data about the customers of your company in your database. The structure of a

customers data could include fields such as customer name, customer address, city,

state, phone number, and so on. Data about a particular customer could be as follows in

the respective fields: John Bello/1234 Lagos Street/Minna/Niger/08056342345. There are

two aspects of the data about customers. One aspect is the structure of the data

consisting of the field names, field sizes, data types, and so on. This part is the structure of

the data for customers. The other part is the actual data for each customer consisting of

the actual data values in the various fields.

The first part relating to the structure resides separately in storage, and this is called

the data dictionary or data catalog. A data dictionary contains the structures of the

various data elements in the database. It also contains the relationships among data

elements. The other part relating to the actual data about individual customers resides in

the data repository. The data dictionary and the data repository work together to provide

information to users.

Database Software Are Oracle and Informix databases? Oracle and Informix are really the

software that manages data. These are database software or database managementsystems (DBMS). Database software supports the storing, retrieving, and updating of data


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in a database. Database software is not the database itself. The software helps you store,

manage, and protect the data in a database.Data Abstraction Consider the example of customer data again. Data about each

customer consist of several fields such as customer name, street address, city, state,

phone no, credit status, and so on. We can look at customer data at three levels. The

customer service representative can look at the customer from his or her point of view as

consisting of only the fields that are of interest to the representative. This may be just

customer name, phone number, and credit status. This is one level. The next level is the

structure of the complete set of fields in customer data. This level is of interest to the

database designer and application programmer. Another level is of interest to the

database administrator, who is responsible for designing the physical layout for storing the

data in files on disk storage.

Now go through the three levels. The customer service representative is just

interested in what he or she needs from customer data, not the entire set of fields or how

the data is physically stored on disk storage. The complexities of the other two levels may

be hidden from the customer service representative. Similarly, the physical level of how

the data is stored on disk storage may be hidden from the application programmer. Only

the database administrator is interested in all three levels. This concept is the abstraction

of datathe ability to hide the complexities of data design at the levels where they arenot required. The database approach provides for data abstraction.

Data Access The database approach includes the fundamental operations that can be

applied to data. Every database management system provides for the following basic

operations:

READ data contained in the database

ADD data to the database

UPDATE individual parts of the data in the database

DELETE portions of the data in the database

Database practitioners refer to these operations by the acronym CRUD:

CCreate or add data

RRead data

UUpdate data

DDelete data


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Transaction Support Imagine the business function of entering an order from a customer

into the computer system. The order entry clerk types in the customer number, the

product code, and the quantity ordered. The order entry program reads the customer

data and allows the clerk to sight verify the customer data, reads product data and

displays the product description, reads inventory data, and finally updates inventory or

creates a back order if inventory is insufficient. All these tasks performed by the order entry

program to enter a single order comprise a single order entry transaction.

When a transaction is initiated it should complete all the tasks and leave the data in

the database in a consistent state. That is, if the initial stock is 1000 units and the order is

for 25 units, the stock value stored in the database after the transaction is completed

must be 975 units. How can this be a problem? See what can happen in the execution of

the transaction. First, the transaction may not be able to perform all its tasks because of

some malfunction preventing its completion. Second, numerous transactions from

different order entry clerks may be simultaneously looking for inventory of the same

product. Database technology enables a transaction to complete a task in its entirety or

back out intermediary data updates in case of malfunctions preventing completion.

Database schema

The overall structure of a database is called a database schema. Databaseschema is usually graphical presentation of the whole database. Tables are connected

with external keys and key columns. When accessing data from several tables, database

schema will be needed in order to find joining data elements and in complex cases to

find proper intermediate tables. Some database products use the schema to join the

tables automatically.

Database system has several schemas according to the level of abstraction. The physical

schema describes the database design at physical level. The logical schema describes

the database design at logical level. A database can also have sub-schemas (view

level) that describes different views of database.

Database Instance

1. Databases change over time.

2. The information in a database at a particular point in time is called an instance of the

database

3. Analogy with programming languages:


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REVIEW TERMS

Database Instance

Schema

Database Schema

Physical schema

Logical schema

Physical data independence

Database Language

DDL DML Query Language

Data dictionary

Metadata

STUDENT ACTIVITY

1)What is difference between database Schema & database instance?

2) What do you understand by the structure of a database?

3)Define physical schema and logical schema?

4)Define data independence? Explain types of data independence?

5) Define data dictionary, meta-data?

6)Define various elements of data dictionary?

STUDENTS NOTES

__________________________________________________________________________

__________________________________________________________________________

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__________________________________________________________________________

__________________________________________________________________________

__________________________________________________________________________

__________________________________________________________________________

___________________________________________________________________________

________________________________________________________________________________________________________

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________________________________________________________________________________


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Chapter 4

DATABASE ARCHITECTURE


Differentiate between database manager and database administrator

State the different types of Database user Explain Role of Database administrator Explain Roles of Database users Describe the Database architecture

4.1 DATABASE MANAGER

The database manager is a program module which provides the interface

between the low-level data stored in the database and the application programs and

queries submitted to the system.

1. Databases typically require lots of storage space (gigabytes). This must be stored on

disks. Data is moved between disk and main memory (MM) as needed.

2. The goal of the database system is to simplify and facilitate access to data.

Performance is important. Views provide simplification.

3. So the database manager module is responsible for

Interaction with the file manager: Storing raw data on disk using the file systemusually provided by a conventional operating system. The database manager must

translate DML statements into low-level file system commands (for storing, retrieving

and updating data in the database).

Integrity enforcement: Checking that updates in the database do not violateconsistency constraints (e.g. no bank account balance below $25)

Security enforcement: Ensuring that users only have access to information they arepermitted to see

Backup and recovery: Detecting failures due to power failure, disk crash, softwareerrors, etc., and restoring the database to its state before the failure

Concurrency control: Preserving data consistency when there are concurrent users.4. Some small database systems may miss some of these features, resulting in simpler

database managers. (For example, no concurrency is required on a PC running MS-DOS.)

These features are necessary on larger systems


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4.2 DATABASE ADMINISTRATOR

The database administrator is a person having central control over data and

programs accessing that data. Duties of the database administrator include:

Scheme definition: the creation of the original database scheme. This involveswriting a set of definitions in a DDL (data storage and definition language),

compiled by the DDL compiler into a set of tables stored in the data dictionary.

Storage structure and access method definition: writing a set of definitionstranslated by the data storage and definition language compiler

Scheme and physical organization modification: writing a set of definitions used bythe DDL compiler to generate modifications to appropriate internal system tables

(e.g. data dictionary). This is done rarely, but sometimes the database scheme or

physical organization must be modified.

Granting of authorization for data access: granting different types of authorizationfor data access to various users

Integrity constraint specification: generating integrity constraints. These areconsulted by the database manager module whenever updates occur.

4.3 DATABASE USERS

The database users fall into several categories: Application programmers are computer professionals interacting with the system

through DML calls embedded in a program written in a host language (e.g. C, PL/1,

Pascal).

These programs are called application programs. The DML precompiler converts DML calls (prefaced by a special character like $,

#, etc.) to normal procedure calls in a host language.

The host language compiler then generates the object code. Some special types of programming languages combine Pascal-like control

structures with control structures for the manipulation of a database.

These are sometimes called fourth-generation languages. They often include features to help generate forms and display data.

Sophisticated users interact with the system without writing programs. They form requests by writing queries in a database query language.


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These requests are submitted to a query processor that breaks a DML statementdown into instructions for the database manager module.

Specialized users are sophisticated users writing special database applicationprograms. These may be CADD systems, knowledge-based and expert systems,

complex data systems (audio/video), etc.

Naive users are unsophisticated users who interact with the system by usingpermanent application programs (e.g. automated teller machine).

4.4 DATABASE SYSTEM ARCHITECTURE

Database systems are partitioned into modules for different functions as you will observe

in fig. Some functions (e.g. file systems) may be provided by the operating system.

Components include:

File manager manages allocation of disk space and data structures used torepresent information on disk.

Database manager: The interface between low-level data and applicationprograms and queries.

Query processor translates statements in a query language into low-levelinstructions the database manager understands. (May also attempt to find an

equivalent but more efficient form.) DML precompiler converts DML statements embedded in an application program

to normal procedure calls in a host language. The precompiler interacts with the

query processor.

DDL compiler converts DDL statements to a set of tables containing metadatastored in a data dictionary.

In addition, several data structures are required for physical system implementation: Data files: store the database itself. Data dictionary: stores information about the structure of the database. It is used

heavily. Great emphasis should be placed on developing a good design and

efficient implementation of the dictionary.

Indices: provide fast access to data items holding particular values.


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Figure 4.1: The Database Architecture

POINTS TO PONDER Database manager is a program module which provides the interface between the

low-level data stored in the database and the application programs

Database administrator is a person having central control over data

Database user is a person who access the database at various level.

Data files: store the database itself.

Data dictionary: stores information about the structure of the database.

DML precompiler converts DML statements embedded in an application program to

normal procedure calls in a host language.

Data Dictionary


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Chapter 5

DATA MODELS


Define data models

Explain Different types of data models: Hierarchical data model Network data model Relational model

State the property of relational tables5.1 Data models are a collection of conceptual tools for describing data, data

relationships, data semantics and data constraints.

A data model is a "description" of both a container for data and a methodology for

storing and retrieving data from that container. Actually, there isn't really a data model

"thing". Data models are abstractions, oftentimes mathematical algorithms and concepts.

You cannot really touch a data model. But nevertheless, they are very useful. The analysis

and design of data models has been the cornerstone of the evolution of databases. As

models have advanced so has database efficiency.

There are various kinds of data models i.e. in a database records can be arranged

in various ways. The various ways in which data can be represented are:-

1) Hierarchical data model

2) Network data model

3) Relational Model

4) E-R-Model

5.2 The Hierarchical Model

Organization of the records is as a collection of trees. As its name implies, the

Hierarchical Database Model defines hierarchically-arranged data.

Perhaps the most intuitive way to visualize this type of relationship is by visualizing an

upside down tree of data. In this tree, a single table acts as the "root" of the database

from which other tables "branch" out.

You will be instantly familiar with this relationship because that is how all windows-based directory management systems (like Windows Explorer) work these days.


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Relationships in such a system are thought of in terms of children and parents such

that a child may only have one parent but a parent can have multiple children. Parents

and children are tied together by links called "pointers" (perhaps physical addresses inside

the file system). A parent will have a list of pointers to each of their children. If we want to

create a structure where in a course various students are there & these students are given

certain marks in assignment.

However, as you can imagine, the hierarchical database model has some serious

problems. For one, you cannot add a record to a child table until it has already been

incorporated into the parent table. This might be troublesome if, for example, you wanted

to add a student who had not yet signed up for any courses.

Worse, yet, the hierarchical database model still creates repetition of data within the

database. You might imagine that in the database system shown above, there may be a

higher level that includes multiple course. In this case, there could be redundancy

because students would be enrolled in several courses and thus each "course tree" would

have redundant student information.

Redundancy would occur because hierarchical databases handle one-to-many

relationships well but do not handle many-to-many relationships well. This is because a

child may only have one parent. However, in many cases you will want to have the child

be related to more than one parent. For instance, the relationship between student andclass is a "many-to-many". Not only can a student take many subjects but a subject may

also be taken by many students. How would you model this relationship simply and

efficiently using a hierarchical database? The answer is that you wouldn't.

Though this problem can be solved with multiple databases creating logical links

between children, the fix is very kludgy and awkward.

Faced with these serious problems, the computer brains of the world got together and

came up with the network model.

5.3 Network Databases

In many ways, the Network Database model was designed to solve some of the

more serious problems with the Hierarchical Database Model. Specifically, the Network

model solves the problem of data redundancy by representing relationships in terms of

sets rather than hierarchy. The model had its origins in the Conference on Data Systems


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Languages (CODASYL) which had created the Data Base Task Group to explore and

design a method to replace the hierarchical model.

The network model is very similar to the hierarchical model actually. In fact, the

hierarchical model is a subset of the network model. However, instead of using a single-

parent tree hierarchy, the network model uses set theory to provide a tree-like hierarchy

with the exception that child tables were allowed to have more than one parent. This

allowed the network model to support many-to-many relationships.

Visually, a Network Database looks like a hierarchical Database in that you can see it as a

type of tree. However, in the case of a Network Database, the look is more like several

trees which share branches. Thus, children can have multiple parents and parents can

have multiple children.

Nevertheless, though it was a dramatic improvement, the network model was far

from perfect. Most profoundly, the model was difficult to implement and maintain. Most

implementations of the network model were used by computer programmers rather than

real users. What was needed was a simple model which could be used by real end users

to solve real problems.

5.4 Relational Model

The relational model was formally introduced by Dr. E. F. Codd in 1970 and hasevolved since then, through a series of writings. The model provides a simple, yet

rigorously defined, concept of how users perceive data. Network model solves the

problem of data redundancy by representing relationships in terms of sets. A relational

database is a collection of two-dimensional tables. The organization of data into

relational tables is known as the logical view of the database. That is, the form in which a

relational database presents data to the user and the programmer. The way the

database software physically stores the data on a computer disk system is called the

internal view. The internal view differs from product to product and does not concern us

here.

A relational database allows the definition of data structures, storage and retrieval

operations and integrity constraints. In such a database the data and relations between

them are organised in tables. A table is a collection of records and each record in a table

contains the same fields.


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Properties of Relational Tables:

Values Are Atomic

Each Row is Unique

Column Values Are of the Same Kind

The Sequence of Columns is Insignificant

The Sequence of Rows is Insignificant

Each Column Has a Unique Name Certain fields may be designated as keys, which

means that searches for specific values of that field will use indexing to speed them up.

Where fields in two different tables take values from the same set, a join operation can be

performed to select related records in the two tables by matching values in those fields.

Often, but not always, the fields will have the same name in both tables. For example, an

"orders" table might contain (customer-ID, product-code) pairs and a "products" table

might contain (product-code, price) pairs so to calculate a given customer's bill you

would sum the prices of all products ordered by that customer by joining on the product-

code fields of the two tables. This can be extended to joining multiple tables on multiple

fields. Because these relationships are only specified at retreival time, relational databases

are classed as dynamic database management system. The RELATIONAL database

model is based on the Relational Algebra.

A basic understanding of the relational model is necessary to effectively userelational database software such as Oracle, Microsoft SQL Server, or even personal

database systems such as Access or Fox, which are based on the relational model.

POINTS TO PONDER

Data models are a collection of conceptual tools for describing data, data

relationships, data semantics and data constraints.

Types of data models are:-

1. Hierarchial data model

2. Network data model

3. Relational Model

4. E-R-Model

The Hierarchical Database Model defines hierarchically-arranged data.

Network model solves the problem of data redundancy by representing relationships in

terms of sets.


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The relational model is the most popular model in use

REVIEW TERMS

Data models

Hierarchical data model

Network data model

Relational data model

STUDENTS ACTIVITY

1)Define data models?

2)Define hierarchical data model?

3)Define network data model?

4)Define relational data model?

5) State the properties of relational table

STUDENTS NOTES

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Chapter 6

RELATIONAL DATABASE MANAGEMENT SYSTEM


Understand RDBMS Understand data structures Understand data manipulation Understand various relational algebra operations Understand data integrity

The relational model was proposed by E. F. Codd in 1970. It deals with

database management from an abstract point of view. The model provides

specifications of an abstract database management system. To use the

database management systems based on the relational model however,

users do not need to master the theoretical foundations. Codd defined the

model as consisting of the following three components:

1. Data Structure - a collection of data structure types for building the

database.

2. Data Manipulation - a collection of operators that may be used toretrieve, derive or modify data stored in the data structures.

3. Data Integrity - a collection of rules that implicitly or explicitly define a

consistent database state or changes of states

Data Structure

Often the information that an organisation wishes to store in a computer and

process is complex and unstructured. For example, we may know that a

department in a university has 200 students, most are full-time with an

average age of 22 years, and most are females. Since natural language is

not a good language for machine processing, the information must be

structured for efficient processing. In the relational model the information is

structures in a very simple way

We consider the following database to illustrate the basic concepts of the

relational data model.


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Subject_id Subject_name Department

CP302CP304CH001PH101MA111

Database ManagementSoftware EngineeringIntroduction to ChemistryPhysicsPure Mathematics

Comp. ScienceComp. ScienceChemistryPhysicsMathematics

The Relation Subject

We list a number of properties of relations:

1. Each relation contains only one record type.2. Each relation has a fixed number of columns that are explicitly named.

Each attribute name within a relation is unique.

3. No two rows in a relation are the same.

4. Each item or element in the relation is atomic, that is, in each row, every

attribute has only one value that cannot be decomposed and therefore no

repeating groups are allowed.

5. Rows have no ordering associated with them.

6. Columns have no ordering associated with them (although most

commercially available systems do).

The above properties are simple and based on practical considerations. The

first property ensures that only one type of information is stored in each

relation. The second property involves naming each column uniquely. This

has several benefits. The names can be chosen to convey what each

column is and the names enable one to distinguish between the column and

its domain. Furthermore, the names are much easier to remember than the

position of the position of each column if the number of columns is large.

The third property of not having duplicate rows appears obvious but is not

always accepted by all users and designers of DBMS. The property is essential

since no sensible context free meaning can be assigned to a number of rows

that are exactly the same.


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The next property requires that each element in each relation be atomic

that cannot be decomposed into smaller pieces. In the relation model, the

only composite or compound type (data that can be decomposed into

smaller pieces) is a relation. This simplicity of structure leads to relatively

simple query and manipulative languages.

The relation is a set of tuples and is closely related to the concept of relation

in mathematics. Each row in a relation may be viewed as an assertion. For

example, the relation student asserts that a student by the name of Panam

Bitrushasstudent_id 8654321 and lives at Makurdi, Benue.

Similarly the relation subject asserts that one of the subjects offered by the

Department of Computer Science is CP302 Database Management.

In the relational model, a relation is the only compound data structure sincerelation do not allow repeating groups or pointers.

We now define the relational terminology:

Relation- essentially a table

Tuple- a row in the relation

Attribute- a column in the relation Degree of a relation - number of attributes

in the relation

Cardinality of a relation- number of tuples in the relation

Domain- a set of values that an attribute is permitted to take. Same domain

may be used by a number of different attributes.

Primary key - as discussed in the last chapter, each relation must have an

attribute (or a set of attributes) that uniquely identifies each tuple.

Each such attribute (or a set of attributes) is called a candidate keyof the

relation if it satisfies the following properties:

(a) the attribute or the set of attributes uniquely identifies each tuple in the

relation (called uniqueness), and

(b) if the key is a set of attributes then no subset of these attributes has

property (a) (called minimality).


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There may be several distinct set of attributes that may serve as candidate

keys. One of the candidate keys is arbitrarily chosen as the primary key of the

relation.

The three relations above student, enrolment andsubject have degree 3, 2

and 3 respectively and cardinality 4, 6 and 5 respectively. The primary key of

the the relation student is student_id, of relation enrolment is (student_id,

subject_id), and finally the primary key of relation subject is subject_id. The

relationstudent probably has another candidate key. If we can assume the

names to be unique than thestudent_name is a candidate key. If the names

are not unique but the names and address together are unique, then the

two attributes (student_id, address) is a candidate key. Note that both

student_id and (student_id, address) cannot be candidate keys, only one

can. Similarly, for the relation subject, subject_name would be a candidatekey if the subject names are unique.

The relational model is the most popular data model for commercial data

processing applications. It is very much simple due to which the

programmers work is reduced.

Data Manipulation

The manipulative part of relational model makes set processing (or relational

processing) facilities available to the user. Since relational operators are able

to manipulate relations, the user does not need to use loops in the

application programs. Avoiding loops can result in significant increase in the

productivity of application programmers.

The primary purpose of a database in an enterprise is to be able to provide

information to the various users in the enterprise. The process of querying a

relational database is in essence a way of manipulating the relations that are

the database. For example, one may wish to know

1. names of all students enrolled in CP302, or

2. names of all subjects taken by Esther Maidawa.


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The Relational Algebra

The relational algebra is a procedural query language. It consists of a set of

operations that take one or two relations as input and produce a new

relation as their result. The fundamental operations in the relational algebra

are select, project, union, set difference, Cartesian product, and rename. In

addition to the fundamental operations, there are several other operations-

namely, set intersection, natural join, division, and assignment. We will define

these operations in terms of the fundamental operations.

Fundamental Operations

The select, project, and rename operations are called unary operations,

because they operate on one relation. The other three operations operate

on pairs of relations and are, therefore, called binary operations.

Various operations are shown as follows:


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Projection

Projection is the operation of selecting certain attributes from a relation R to

form a new relation S. For example, one may only be interested in the list of

names from a relation that has a number of other attributes. Projection

operator may then be used. Like selection, projection is a unary operator.

loan-number, amount (loan)

loan-number amount

L-11

L-14

L-15

L-16

L-17

L-23

L-93

900000

1500000

1500000

1300000

1000000

2000000

500000

Composition of Relational Operations

The fact that the result of a relational operation is itself a relation is important.

Consider the more complicated query Find those customers who live in

Minna. We write:

customer-name ( customer-city = Minna (customer))

Notice that, instead of giving the name of a relation as the argument of theprojection operation, we give an expression that evaluates to a relation.

In general, since the result of a relational-algebra operation is of the same

type (relation) as its inputs, relational-algebra operations can be composed

together into a relational-algebra expression. Composing relational-algebra

operations into relational-algebra expressions is just like composing arithmetic

operations (such as +, -, *, and %) into arithmetic expressions.


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Cartesian product

The cartesian product of two tables combines each row in one table with

each row in the other table.

Example: The table E (forEMPLOYEE)

ENR ENAME DEPT

121 John Bello A

111 Esther Danmallam B

131 Tunde Gana C

Example: The table D (forDEPARTMENT)

DNUMBER DNAME

A Sales

B Marketing

C Legal

E X D

ENR ENAME DEPT DNUMBER DNAME RELATIONAL

ALGEBRA

121 John Bello A A Sales

E X D

121 John Bello A B Marketing

121 John Bello A C Legal

111 Esther

Danmallam

B A Sales

111 Esther

Danmallam

B B Marketing

111 Esther

Danmallam

B C Legal

131 Tunde Gana C A Sales

131 Tunde Gana C B Marketing

131 Tunde Gana C C Legal

Seldom useful in practice.

Can give a huge result.


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The Union Operation

Consider a query to find the names of all bank customers who have either an

account or a loan or both. Note that the customer relation does not contain

the information, since a customer does not need to have either an account

or a loan at the bank. To answer this query, we need the information in the

depositor relation and in the borrower relation. We know how to find the

names of all customers with a loan in the bank:

customer-name (borrower)

We also know how to find the names of all customers with an account in the

bank:

customer-name (depositor)

To answer the query, we need the union of these two sets; that is, we need

all customer names that appear in either or both of the two relations. We find

these data by the binary operation union, denoted, as in set theory, by U. So

the expression needed is

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

For a union operation r U s to be valid, we require that two conditions hold:

1. The relations r and s must have the same number of attributes.

2. The domains of the ith attribute of rand the ith attribute of s must be the

same, for all i.

Note that r and s can be, in general, temporary relations that are the result of

relational-algebra expressions.

The Set-Intersection Operation

The first additional-relational algebra operation that we shall define is set

intersection (). Suppose that we wish to find all customers who have both a

loan and an account. Using set intersection, we can write

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


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Note that we can rewrite any relational algebra expression that uses set

intersection by replacing the intersection operation with a pair of set-

difference operations as:

rs =r(rs)

Thus, set intersection is not a fundamental operation and does not add anypower to the relational algebra. It is simply more convenient to write r s

than to writer(rs).

The Set Difference Operation

The set-difference operation, denoted by -, allows us to find tuples that are in

one relation but are not in another. The expression rs produces a relation

containing those tuples in r but not in s.

We can find all customers of the bank who have an account but not a loan

by writing

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

As with the union operation, we must ensure that set differences are taken

between compatible relations. Therefore, for a set difference operation rsto be valid, we require that the relations r and s be of the same arity, and

that the domains of the ith attribute of r and the ith attribute of s be the

same.

The Assignment Operation

It is convenient at times to write a relational-algebra expression by assigning

parts of it to temporary relation variables. The assignment operation,

denoted by , works like assignment in a programming language.

temp1 amount>1200000 (loan)

temp2 loan-number, amount (loan)

result = temp1temp2

The evaluation of an assignment does not result in any relation being

displayed to the user. Rather, the result of the expression to the right of the


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Primary key

Foreign key

Relational algebra

STUDENT ACTIVITY

1) Why do we use RDBMS?

2) Define relation, tuple, domain, keys?

3) What is the difference between Intersection, Union & Cartesian product?

RESEARCH THE FOLLOWING TERMS AND ANSWER QUESTIONS THAT FOLLOW:

Aggregate functions

Joins

Natural join

Outer join

Right outer join

Left outer join

Rename operation1) Define aggregate functions with example?

2)Define joins? What is natural join?

3)Differentiate between inner join & outer join?

4)Differentiate between left outer join & right outer join with the help of

example?

5)Define rename operators?STUDENTS NOTES

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Entities defined by the same set of attributes can be grouped into an ENTITY

SET (abbreviated as ESet) as shown in

ESET: CarModel

Name Power NseatsR1222

HZ893

R1293

7.3

6.8

5.4

5

5

4

AN ENTITY SET

A given set of attributes may be referred to as an entity type. All entities in a

given ESet are of the same type, but sometimes there can be more than one

set of the same type. The set of all persons who are customers at a given

bank can be defined as an entity set customer. The individual entity that

constitutes a set are said to be extension to entity set. So all the individual

bank customers are the extension of entity set customer.

Each entity has a value for each of its attributes. For each attribute, there is a

set of permitted values called domain orvalue set.

SIMPLE & COMPOSITE ATTRIBUTES

A simple attribute has got one value for its attribute & a composite attribute

is one which can be divided into sub-parts. For example an attribute namecan be divided into first name middle name & last name .

SINGLE & MULTIVALUED ATTRIBUTES

An attribute which have got only one value is known as single valued

attribute. For ex. the loan_no attribute will have only one loan_no. There may

be cases when an attribute has a set of values for a specific entity. For ex. an

attribute phone_no. may have a value zero, one or several phone_no. This is

known as multivalued attribute.


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Mapping Cardinalities

It express the number of entities to which other entity can be associated via

a relationship set. It can be of the following types:-

1. One to one: An entity in A is associated with at most one entity in B, & an

entity in B is associated with at most one entity in A.

2. One to many: An entity in A is associated with any number(zero or more) of

entities in B. An entity in B however can be associated with at most one entity

in A.

3. Many to one: An entity in A is associated with at most one entity in B.An

entity in B however can be associated with any number(zero or more) of

entities in A.

4. Many to many: An entity in A is associated with any number(zero or more)

of entities in B & an entity in B is associated with any number(zero or more) of

entities in A.

One to many relationship

Many to one relationship

One to one relationship

POINTS TO PONDER

An ENTITY is a `thing' which can be distinctly identified, for example a

person, a car, a subroutine, a wire, an event.

A RELATIONSHIP is an association among entities, eg person OWNS car

A given set of attributes may be referred to as an entity type

A simple attribute has got one value for its attribute & a composite

attribute is one which can be divided into sub-parts.

value is derived from value of other related attributes or entities is known as

derived attribute.

A relationship is an association among several entities

A relationship set is a subset of the cartesian product of entity setsREVIEW TERMS


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Entity

Entity set

Attribute

Domain

Value

Relationship

Relationship set

Cardinality

Association

STUDENT ACTIVITY

1)Define entity, domain,value?

2)Define relationship, relationship set?

3)Differentiate between simple & composit attribute?

4)Define derived attribute?

5)Differentiate between single & multi-valued attribute?

6)Define cardinality?Explain various kinds of cardinality?

7)Define various components of E-R-Diagram?

STUDENTS NOTES

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Com 312 Lecture Notes2010

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