10g sql e book

Oracle 10g SQL

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Second Edition

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Table of Contents

Oracle 10g SQL

CHAPTER CHAPTER TITLE PAGE
No. NO
1. Database concepts 1-39

2. Introduction to Oracle 10g 40-49

3. Data Retrieval 50-78

4. Enhancing Data Retrieval 79-95

5. Generating formatted reports using isql*plus 96-128

6. SQL single Row Functions 129-154

7. Working with Grouped Data 155-163

8. Joins 164-186

9. Understanding Sub queries 187-201

10. Advanced Sub queries 202-221

11. Data Manipulation 222-248

12. Managing Tables 249-293

13. Managing Constraints 294-318

14. Views 319-342

15. Other Database Objects 343-371

16. Data Dictionary Views 372-380

17. Security Implementation 381-393

18. Manipulating Large Data Sets 394-413

19. Regular Expressions 414-422

© SQL Star International Ltd. ii

Chapter 1

Database Concepts
Typical Database Architecture
DBMS
Types of DBMS
Normalization
Entity Relationship (E-R) Model
Features of SQL

© SQL Star International Ltd. 1

Objectives
At the end of this chapter, you will be able to:

Understand the basic concepts of a database

Identify the disadvantages with Flat File systems

Identify the advantages of a DBMS

Understand the types of DBMS

Understand the E-R Model

Understand the features of SQL

Describe the Codd‘s Rules


Database Management
The approach of the new millennium has brought with it several challenges, thereby
making it mandatory for companies and organizations to maintain high level of
efficiency in their computing systems, so as to stand the test of time. Databases and
database systems are the essential backbone of any organization.

Database
When one hears the word Database, one thinks of a collection or a store of mutually
related data. The implicit properties of a database are as follows:

 A database represents some aspects of the real world and any changes to the
real world should get reflected in the database. For example, a manufacturing
concern keeps details of the products it manufactures and also of the
suppliers it deals with. Any change in the pricing of the product or a change in
the suppliers who supply raw materials must be immediately reflected in the
database.

 A database is a logical collection of relevant data, reflecting some inherent
meaning. Any random grouping of data cannot be referred to as a database.
A manufacturing concern requires data about its customers, products, as well
as its suppliers. Details regarding each of them form a logical group of data.

 A database is populated with data for a purpose. It has an audience that is
interested in its contents. For instance, in the above example, the
manufacturing concern needs the customer details to identify its regular
customers and also their credit worthiness. Similarly product detail helps in
determining the stock depletion level (i.e. when to place fresh order for raw
materials).

Now a day, the term „database‟ is mostly used in connection with computerized
databases. Therefore, today, a study of database systems involves also a study of the
associated technology employed to store, access and manipulate the computerized
databases.

Traditionally, data accessed through computers has been stored on different storage
media in the form of individual files. Files proved to be quite satisfactory as long as
computerization was limited to a few application areas and the use of computers
restricted to a privileged few. However, as actual users grew in number, especially
with the advent of online time-sharing systems, the file systems gave rise to many
serious problems. The discipline of database systems evolved in response to these
problems. Let us first consider what these problems are so as to understand the
different features of database systems more clearly.

File Systems and the Associated Problems
Most data processing systems in existence today, especially in India, use files for
storing, accessing and manipulating data. Files are stored typically on magnetic
tapes and disks.


Most of the problems with files arise out of the fact that files are specific to an
application, e.g., a set of files may be designed for the sales analysis system of a
company.

Programs of the same application system can use these files. However, if some
other new application needs source data from this system, there may be difficulties.
Therefore, in many cases, new files, with considerable data in common with the
existing files, may have to be designed for the new applications.

Therefore, as applications proliferate, the total number of computerized files grows
considerably. Also, as the number of actual users of the computer grows, the
number of applications increases, in turn resulting in an increase in the number of
files.

A large number of files give rise to the following problems:

 Files involve a high level of redundancy in data. As we have mentioned above,
proliferation of files results in the same data item being stored at many
different places.

 Redundancy in data often results in inconsistency of data. The same data item
being used by different applications may exist in different versions. What is
worse, it may exist in different stages of update at different places and thus
may have different values. This may ultimately result in inconsistencies
amongst reports generated by the two application systems.

 Individual files are not amendable to rapid changes, especially with respect to
the way the data items are structured within the file. If an application wants
data from an existing file but structured differently, it cannot be provided
quickly and easily. For this purpose, either conversion programs have to be
written or new files have to be created.

 Because of the inflexibility of files, many ad hoc queries cannot be answered.

 Yet another consequence of the inflexibility of files is that it is usually
expensive to make changes to a file system. It is also a very slow process. It
may even involve modification of application programs.

 What is worse, modification in one program may require modifications in
other programs, which interface with this program. This process may set off a
chain reaction of modifications.

The above problems give rise to further difficulties detailed below:

 The Management Information Systems (MIS) finds it difficult to control data,
especially when the actual users develop applications on their own.

 Major changes required in the system while modifying files increase the
maintenance load on Data Processing (DP) professionals substantially, thus
making them unavailable for development of new systems.

 High-level data redundancy entails repetitive data entry and redundant
storage with the accompanying costs.

As has been already stated, Database Systems provide an effective solution to the
above problems. Let us see how.

Data Independence
You have just seen, files give rise to several problems because they are application
specific. Consequently, the applications become data-dependent, that is, they
depend upon the organization and access method for the data on the secondary
storage. This happens because, with conventional application development tools such
as COBOL, the application logic incorporates the knowledge of data organization and
access methods. Therefore, most changes in data organization or access methods
affect the application logic substantially. If problems arising due to this fact are to be
avoided, the data organization (and the access method) and the application logic
have to be made independent of each other. Database Systems do precisely this.

The first step towards this goal is to distinguish between data as is actually stored
(called as the physical representation of data) and data as is presented to an
individual user (called as the logical representation of data).

The Physical Representation of Data
The smallest named unit of data physically stored in the database is known as a
―stored field‖, and a named collection of associated stored fields is known as a
―stored or physical record‖. The named collection of all occurrences of one type of
physical record is known as a ―stored or a physical file‖. This concept will be clearer
after we discuss the logical representation of data.

The Logical Representation of Data
A logical field, record or file is, the field, record or file as it appears to the users, that
is, as it is defined in the user‘s application programs. In all traditional systems, the
logical and physical data are practically the same, which is the root cause of all the
major problems with traditional files. This is not the case with database systems.

Similarly, the structure of stored and logical records can be different. A logical
record type may be obtained by selectively combining fields from different stored
records.
The logical and physical views of a file could also be different in terms of, say, the
key fields for sequencing the records in the file.

With such a separation of the logical and physical data, the database can be modified
and developed without affecting existing applications. The database architecture
achieves this separation.

A Typical Database System
Typical database architecture divides the database into three levels of abstraction;
the internal, conceptual and external levels.

At the internal level is the physical database, while at the external level; one has the
different logical views corresponding to an individual application. The conceptual
level is an intermediate level, which is a single abstract representation of the entire
database.


Data Base Management System (DBMS) is software, which interacts with all the
three levels enabling the users to deal with the data in terms of its logical view
rather than the actual physical database.

A diagrammatic representation of the typical database architecture is shown below:

Let us now consider the different individual entities in the architecture in further
detail. Let us start with the actual or physical database and see how the architecture
brings about a transformation in the data representation to get the data to the user
in the form he wants.

The Internal Database
The internal (or physical) database is stored on secondary storage devices, mainly
the magnetic disk. It itself can be conceptually viewed at different levels of
abstraction. At its lowest level, it is stored in the form of bits with the associated
physical addresses on the secondary storage device.
At its highest level, it can be viewed in the form of files and simple data structures. It
is this level that we shall study when we discuss the physical organization for
databases in later chapters.


The physical database is described by means of a physical scheme or an internal
scheme. It essentially describes the various types of stored records, the different
indexes that are employed for accessing these and the representations for different
stored fields. It is also called as the ―storage structure definition‖.

The Conceptual Database
The conceptual model, also called as the data model, represents information content
of the database in its entirety, but is abstract with respect to the physical database.
Broadly speaking, the conceptual model provides a view of the data as it really is.
This model consists of multiple occurrences of multiple types of a conceptual record.
A conceptual record represents relevant information content only. In this sense, it is
much closer to the external record than a stored record is.

However, it is not the same as the external record.

It contains all the information to build relevant external records. A conceptual stock
record may consist of the quantity of material and the buying rate but not its value;
still the user‘s external record may consist of the value of the stock. A conceptual
model may consist of occurrences of such stock records, a collection of supplier
record occurrences and a collection of assembly records.

Obviously, the conceptual model is derived from the physical model. For this, the
database needs a conceptual/physical mapping, which specifies how conceptual
records and fields map into their counterparts in the physical database. The
conceptual database is described by means of a conceptual scheme. Needless to
say, the conceptual scheme is independent of the physical characteristics of data,
such as storage structures, physical sequences, stored field representations etc.
Ideally the conceptual scheme should include many features in addition to just the
definitions of conceptual records. These may include relevant authorization checks
and validation procedures, the uses of data, the source and destination of data etc.

The conceptual database is a real-world view of data from the organization point of
view. As the real world changes, changes have to be made to the conceptual
database and scheme as well. In such a case, it is usually possible to limit the
corresponding changes to only those external schemes, which use the conceptual
elements that are changed.

The External Database
The external model (or view) is application-specific. Therefore, the user views the
database through an external model, and there are as many external views as there
are applications. External views are the proper interface between the user and the
database as an individual user can hardly be expected to be interested in the entire
database.

Generally, an external model consists of multiple occurrences of multiple types of
external record. An example of an external record is the record of a file as defined in
the data division of COBOL program.

Each external model is defined by means of an external scheme, which describes
each external record type in the external model.

The external model is derived from the conceptual model. For this purpose, the
correspondence between the particular external models has to be defined. An


external/conceptual mapping similar to the conceptual/physical mapping does this.
However, a separate mapping has to be defined for each external view.

An explicit definition of the mapping should be documented, preferably in the
corresponding external scheme.

The user interacts with the database through a high-level language such as COBOL,
PL/I or some special purpose language. This language is known as the host
language. It includes a data sub-language (DSL). The user carries out the retrieval
and storage operations on the database through the DSL.

In fact, the Database Task Group (DBTG) report published in April 1971, contains
proposals for three distinct languages, two of which relate very closely to the concept
of a DSL. These are sub scheme Data Description Language (DDL) and Data
Manipulation Language (DML). The sub scheme DDL is used for defining the external
views while the DML is used for carrying out operations on the database.

In addition to the languages, the user is also supposed to be provided with a
workspace. This workspace is an area meant for receiving or transmitting all data
transferred between the user and the database. This is simply the input-output area
for a program.

Let us now consider what a database management system is, which interacts with
the three levels and the mappings.

What is a Database Management System?
The DBMS is the software, which handles all accesses to the database. Conceptually,
if a user requests a certain data item, the DBMS intercepts and interprets the
request, retrieves the relevant stored occurrences from the physical database,
constructs the required conceptual record occurrences using the physical/conceptual
mapping, then derives the required external record occurrence from the conceptual
records constructed using the relevant conceptual/external mapping.

Advantages of DBMS

You have seen that data independence and the consequential benefits are both an
essential feature and a major advantage of database systems. Yet another essential
feature is the centralization of related data. This phenomenon results in further
advantages of database systems. These are:

 The stored data can be shared relatively easily

 New applications may be developed using the existing database

 Standards for representation of data can be laid down and enforced among
different installations. This can significantly reduce the maintenance activity
and enhance data compatibility among installations.

 With a centralized control of data, the database system may be designed for
an overall optimal performance from the viewpoint of the entire organization.


 Ensuring data security becomes much easier as access to the database can be
controlled through establishment of proper channels and authorization
checks.

However, to realize the above benefits, proper organizational infrastructure is
needed. The most popular way to support the Database environment is to establish
the office of the Database Administrator (DBA). In fact, the DBA may be a single
person or a team. He is responsible for the centralized control of the database.

The Database Administrator
The database administrator is responsible for the overall planning of the company‘s
data resources, for the design of data, and for the day-to-day operational aspects of
data management.

The overall planning of corporate data is the strategic aspect of the database
administration function and involves company-wide planning of existing data and
assessment of organization-wise data standards.

Some of the design aspects of database administration work are:

 Deciding on the storage structures and access methods

 Selecting database software and hardware

 Designing restart and recovery procedures to take care of system outages or
crashes

 Designing means of reconstructing data in the event of abnormal loss of the
same

 Designing scheme

 Designing the means of reorganizing or tuning databases periodically

 Designing database searching strategies

 Designing authorization checks and validation procedures

 Specifying techniques for monitoring database performance

The operations management of database administration deals with data problems
arising on a day-to-day basis. Specifically, the responsibilities include:

 Investigation of errors found in the data

 Supervision of restart and recovery procedures in the event of a failure

 Supervision of reorganization of databases

 Initiation and control of all periodic dumps of data.


In addition, this aspect of database administration includes maintenance of data
security, which involves maintaining security authorization tables, conducting
periodic security audits, investigating all known security breaches.

To carry out all these functions, it is crucial that the DBA has all the accurate
information about the company‘s data readily on hand. For this purpose he maintains
a data dictionary. The data dictionary contains definitions of all data items and
structures, the various schemes, the relevant authorization and validation checks
and the different mapping definitions. It should also have information about the
source and destination of a data item and the flow of a data item as it is used by a
system. This type of information is a great help to the DBA in maintaining centralized
control of data.

Types of DBMS
The different types of DBMS available are:

 Hierarchical database management system

 Network database management system

 Relational database management system

 Object Relational database management system

Hierarchical DBMS
Hierarchical DBMS (HDBMS) is one of the oldest methods used for organizing and
storing data. In a hierarchical database, data is organized in a pyramid fashion, just
like the branches of a tree extending downwards.

In a hierarchical database you need to understand the concepts of record type and
parent-child relationship. Let us take an example.

In the order processing of any organization, orders are placed for different products.
Orders comprise the following information, which are also called field values:

• Order number

• Order date


• Customer number

• Product number

Similarly, products comprise a collection of:

• Product number

• Product type

• Product name

• Quantity

• Price

The collections of these field values are called records and groupings of records of
the same type are called record types. Related records are grouped together so that
you can have higher-level records and lower-level records, similar to how the parents
in a family tree sit above the subordinated children.

In the example, Orders and Products are the two record types and the relationship
between them is the parent-child relationship.

Hierarchical Database Management System

In the diagram, the parent record (Orders) at the top of the pyramid is called the
root record. The parent record has three child records linked to it. The root of the
hierarchical model cannot act as the child record type. Except the root, every record
type acts as a child record type in exactly one parent-child relationship.
The child records can have only one parent record. In contrast, a parent record may
have more than one child record linked to it. Each child record can also be a parent
with child records underneath it.

Hierarchical DBMS works by moving from the top of the pyramid to its bottom. A
record search is conducted by working down through the pyramid from parent to
child until the suitable child record is found.

The pyramid like structure and the defining of relationship between records in
advance makes it easy to access and update hierarchical databases.


However, there are few limitations with HDBMS. The relationship between child
records is not permitted, even if they make a logical sense. Moreover, the
hierarchical design is so rigid that adding a new record requires the redefinition of
the entire database.

Network DBMS
Network DBMS (NDBMS) is an extension of HDBMS. Instead of having a pyramid like
structure, a NDBMS looks more like a spider web or interconnected network of
records. In NDBMS, child records are called members and parent records are called
owners.

In the network data model too, data is stored in records and descriptions of the
structure of a group of records of the same type are stored in record types. Record
types are linked or related using the set types. Set types consist of:

• A set type name

• An owner record type

• A member record type

Consider an example of orders and it‘s products. The two record types are Order
and Product, the former being the owner record type and the latter being the
member record type. They are linked using the set type ProdOrder, which
represents the relationship between orders and products in them. The relationship is
of 1:N meaning that there will be many set occurrences (or instances) where one
record from the owner record type Order relates to a set of records from the
member record type Product. That is, an order can have one or more products in it.
Therefore, set occurrences are composed of:

• One record from the owner record type

• A number of records (zero or more) from the member record type

Network Database Management System


In the figure there are three set occurrences of ProdOrder set type, which are
Product1, Product2, Product3.

A record of the member record type cannot exist in more than one set occurrence,
that is, two customers cannot buy the same product.

Similar to HDBMS, NDBMS structure and relationship must be defined in advance.
The number of connections that can be made between records is also limited.

Relational Database
The databases mentioned so far including the file system databases were not very
efficient. In the file system, users cannot simultaneously access data from the same
file, managing the files is very tedious when data stored is complex and accessing
data from files is also very tedious. HDBMS and NDBMS does not allow many-to-
many relationships, has complex path to navigate and retrieve data, and the
relationship between data is in the form of pointers.

The objective of developing the relational model was to overcome the shortcomings
of those systems that existed at the end of the 1960s, and to make DBMS products
more appealing to all kinds of users. Dr. E. F. Codd first introduced the relational
model when he proposed the relational model principles in a paper called ―A
Relational Model of Data for Large Shared Data Banks‖ in June 1970.

A relational database stores data using relations where each relation resembles a
table of values. Each row in a table contains collection of data values. For example, a
university stores information about all it‘s students using tables referred to as a
Student table and a Course table.

Student table contains details about students, such as, their student number, name
and the course code. As different data is stored in the two tables, we may need to
combine them to answer particular questions such as details about students pursuing
course ‗Electronics‘. An RDBMS enables to relate data in one table to the data in
another. It does so by identifying the relationships, which are represented by
primary key and foreign key. A primary key is assigned to that column, which will
enable you to identify each row of data in a table uniquely. For example, in the
Course table the column containing the course code is the primary key as it helps to
identify each course uniquely. A foreign key is assigned to a column of a table, which
refers to the primary key column in another table. For example, in the Student table
the column containing the course code refers to CourseCode column of the Course
table.


Object Relational Database
Hierarchical, network and relational database models have been quite successful in
storing data for traditional business applications. But, object oriented databases
evolved to handle more complex applications such as databases for scientific
experiments, geographic information system, engineering design and manufacturing.
An object oriented database stores data, their relationships and the way they
interact with other data. As compared to the relational database approach, which
deals with data at the lowest level, that is, columns and rows, the object oriented
approach deals with data at a higher level, that is, with the objects surrounding the
data.

RDBMS
Dr. E.F.Codd outlined the principles of the relational model, which formed the basis
for the evolution of the Relational Database Management System.
A Relational Database Management System is defined as a collection of tables
related to each other through common values.

Evolution of RDBMS
Before the acceptance of Codd‘s Relational Model, database management systems
was just an ad hoc collection of data designed to solve a particular type of problem,
later extended to solve more basic purposes. This led to complex systems, which
were difficult to understand, install, maintain and use. These database systems were
plagued with the following problems:

 They required large budgets and staffs of people with special skills that were
in short supply.

 Database administrators‘ staff and application developers required prior
preparation to access these database systems.

 End-user access to the data was rarely provided.


 These database systems did not support the implementation of business logic
as a DBMS responsibility.

Hence, the objective of developing a relational model was to address each and every
one of the shortcomings that plagued those systems that existed at the end of the
1960s decade, and make DBMS products more widely appealing to all kinds of users.

The existing relational database management systems offer powerful, yet simple
solutions for a wide variety of commercial and scientific application problems. Almost
every industry uses relational systems to store, update and retrieve data for
operational, transaction, as well as decision support systems.

Basic Relational Database Terminology
In a relational database, the entities of the ERD are represented as tables and their
attributes as the columns of their respective tables in a database schema. The
components of a database schema include:

 Tables: Tables are the basic storage structures of a database where data
about something in the real world is stored. It is also called a relation or an
entity.

 Rows: Rows represent collection of data required for a particular entity. In
order to identify each row as unique there should be a unique identifier called
the primary key, which allows no duplicate rows. For example in a library
every member is unique and hence is given a membership number, which
uniquely identifies each member. A row is also called a record or a tuple.

 Column: Columns represent characteristics or attributes of an entity. Each
attribute maps onto a column of a table. Hence, a column is also known as an
attribute.

 Relationship: Relationships represent a logical link between two tables. A
relationship is depicted by a foreign key column.

Some optional properties of relational tables include the following:

 Data items (fields) must have a single value.

 Data values in columns are of the same kind. This property states that all
values in a given column must come from the same domain.

Let us understand the concept of a domain. Suppose, you have a CourseName
column in the Course table, which is defined to be a character string of length 15.
The possible values this column could have are:

 Oracle10g

 Java

 E-commerce

 C++

 Visual Basic

Let us name this list as ‗course-names’ and define a rule that the contents of
CourseName should not only be characters of length less than 15, but must also
contain values that are part of ‗course-names’. Here, ‗course-names’ becomes the
domain and CourseName is in the domain of ‗course-names’.

Each row is unique

 The sequence of columns (left to right) is insignificant. The benefit of this
property is that columns can be retrieved in any order.

 The sequence of rows (top to bottom) is insignificant. The benefit of this
property is that rows can be retrieved in any order, that is, the third, fourth
or fifth row of member details could be retrieved.

 Each column must have a unique name. As mentioned above, the sequencing
of columns being insignificant, columns must be referred by name and not by
their position.

Normalization
One of the methods of designing a database is normalization of steps.
What do you mean by normalization?
Normalization can be defined as the technique implemented to remove redundancy
from an existing set of tables.

Normalization helps:

 Reduce redundancy

 Increase integrity

 Stabilize design

 Identify any missing data

A relational table is normalized if it satisfies a certain set of constraints, which are
that they should be free of data redundancy and that they can be modified
consistently and correctly. Therefore, normalization is the process of removing
redundant data by splitting a table into smaller tables.
The technique of normalization includes some rules, which when applied, changes
un-normalized data to a structured and normalized state. The process of normalizing
is implemented in levels called normal forms. There are three such stages, they are:

 First normal form

 Second normal form

 Third normal form


First Normal Form (1NF)
The first normal form can be defined as the level where the tables represent a set of
two-dimensional structures and contain no repeating groups.
You need to implement the following set of steps to convert your un-normalized data
to its first normal form.

 Identify the primary key
 Remove all repeating columns
 Create a new table to contain the repeating columns
 Add a primary key column to the newly created table so as to ensure
uniqueness
 Add a foreign key column to the new table. It should be the same column at
the primary key in the base table.

To understand better, follow the example given.

Example

To arrive at a functionally efficient library database schema, you would have to
normalize the tables of the library database. The main table used in the library is
where the transaction details will be stored. You would require:

 All information pertaining to the customers who borrow books

 All information of the borrowed book, such as its author, its publisher‘s
information and the dates of issue and return

 The un-normalized table is as follows 


This table can be brought to the 1NF by removing all the repeating columns. The
repeating columns are put into separate tables in logical groups with a primary key
as a unique identifier for each table. The tables in the first normal form are:

Second Normal Form (2NF)

The second normal form can be defined as the level where tables are in the 1NF, and
where for every table, all its non-primary key columns are dependent on the whole
primary key. A column should not be partially dependent on the primary key. When a
column depends on part of the primary key it is called partial dependency.

To remove partial dependency:

1. Identify the non-primary key columns and remove them from the tables

2. Create another table to contain the removed columns, and the primary key column
that they are dependent on.

To bring a table to the 2NF, any of the following rules should be met:

 The primary key column should not be a composite key. That is, it should be
made up of only one column.

 All the non-primary key columns are dependant only on the primary key.

 There should be no non-primary key dependent columns in the table.

To bring the tables to 2NF, remove all those columns that are partially dependent on
the whole primary key. For instance the book availability does not depend on the
transaction ID but only on the book ID. So that column can be removed into a new
table.

Hence, the tables in the second normal form will be as follows:


Third Normal Form (3NF)

The third normal form is defined as the level where the non-primary key columns in the
tables are directly dependent on the primary key and are not dependent on any other non-
primary key. If you remove the transitive dependencies from a table in 2NF, then it is
said that, “the non-primary key columns are dependent on the primary key, the whole key
and nothing but the key”.

Steps to convert a table to the third normal form are:

1. Identify the non-primary key columns that depend on other non-
primary key columns.

2. Remove the columns arrived at in the first step from the base table.

3. Create another table with the removed columns and include the
non-primary key column that they are dependent on making it the
primary key.

4. Create a foreign key in the base table linking it to the primary key in the
new table.


To bring the tables to their third normal form remove the non-primary keys that are
dependent on other non-primary keys and also remove the columns that are
calculated or derived columns. The membership fee a non-key column depends on
the age of a member, which is another non-key column. Tables in the third normal
form are:

The Entity Relationship Model
The conceptual level model is a very important model in typical database
architecture. To represent or model data at this level, three major data models
namely, network, hierarchical and relational, have been proposed which you shall
examine later. Each of these models has its own pros and cons. The entity
relationship model is not a formal data model, unlike the three mentioned above.
However, this model is a more natural view of the real world, which consists of
entities and relationships, as you shall see shortly. Therefore, this model is very
useful for understanding the concept of data modeling. The three formal models
employ certain ways of representing data known as data structures; essentially to
represent the ―entity relationships‖ existing in the real world.

The entity relationship model (E-R model) clarifies concepts regarding what entity
relationships are, and what modeling entity relationships existing in the real world
means. Therefore, a study of the E-R model should be an appropriate first step
towards understanding the three major data models.


Entities
An entity is a thing, which can be distinctly identified. What is important over here is
that it is individually distinct. Employees, a house, a supplier to an organization, are
all entities. Identification of entities relevant to a database is extremely important,
because, a database contains data about entities.

All entities of the same type form an entity set. ―All Employees‖ form an entity set
and so do ‗All Suppliers‘.

Distinguishing Entities
As has been stated, an entity is a distinctly identifiable thing. To distinguish one
entity or one member of an entity set from another, one needs some means of
distinction. This distinction is achieved through values of what is known as the ―Key
Attribute‖ of the entity.

The database gives information about different entities contained in it. This
information is about different properties of each entity. For example, a personal
database contains information about employees (here employee is the entity). The
properties of an employee about which information is given, may typically be,
employee number, name, date of birth, date of joining the organization, total job
experience and educational qualifications. Each of these properties is called an
attribute of the entity.

Each of the attributes can take on a value from a range of possible values, which is
known as the domain of values for that attribute. The values need not be only
numerical but may also be character strings.

For each entity in an entity set, there is an attribute, which distinguishes the entity
uniquely from the other members of the set. This attribute is the key attribute for
the entity-set. For example, the employee entity-set discussed about can have either
the employee number or the employee name (assuming no two names are identical)
as the key attribute. In some cases, a combination of more than one attribute may
act as a key, instead of just one key attribute. Some times, an arbitrary serial
number may have to be supplied as the key attribute.

There are special cases where the members of an entity-set can be distinguished
from one another only by their relationship to entities of another type. The ‗is a‘
relationship is one such relationship. These cases will be illustrated when we take up
an actual example of an E-R model later.

Relationships
In a real-world situation, certain entities are associated with each other. For
example, referring to the employee entity-set will have a relationship with the
department entity-set signifying the department for which an employee works. This
relationship can be expressed as the ―works-for‖ relationship from ―employee‖ to
―department‖.

A relationship may exist amongst the members of the same entity-set. For example,
in the employee entity-set, some employees may be seniors of certain other
employees. Therefore a relationship ―senior-of‖ may exist between one member of
the employee entity-set and a few other members of the same set.


A diagrammatic representation for the employee-department relationship may be as
given below.

A diagrammatic representation for the ―senior-of‖ relationship may be:

It should be noted that relationships convey very important information regarding
the relevant real world situation just as entities do, and hence should be properly
represented.

There may also be relationships involving more than two entity sets. For example,
Prof. Smith teaching Economics to a student named Sam. This relationship contains
two relationships – (1) Prof. Smith teaches Economics and (2) Prof. Smith teaches
Sam. These two relationships cannot be combined to deduce the information given
by the original relationship.

The same entity-sets may be also linked by more than one relationship. For
example, the Professors and the Students entity-sets may be linked by the two
relationships, viz; (1) TEACHES and (2) ADVISOR-O

Types of Relationship
Relationships between the entity-sets can be classified according to how many
members of one entity-sets are related to one member of the other entity-set and
vice-versa. Accordingly, the following types of relationships can be identified.

One-to-One Relationships
If a one-to-one relationship exists between two entity-sets A and B, it means that
with each entity in A, at most one entity in B is associated and vice-versa. Strict
one-to-one relationships are not very common in real world situations. Consider an
entity set of traffic policemen and another entity-set of traffic control points in the
city and assume that only one policeman controls one traffic control point. Under this
assumption, the relationship CONTROLS between the entity sets POLICEMEN and
CONTROL-SITES will be a one-to-one relationship.

Many-to-one Relationships
This type of relationship is quite common in everyday life. If, with each entity in the
entity-set B, zero or more entities in set A are associated, then we say that a


many-to-one relationship exists from set A to set B. In our earlier employee
database example, the WORKS-FOR relationship is a many-to-one relationship from
the entity-set EMPLOYEES to the entity-set DEPARTMENTS (assuming that an
employee works for only one department at a time).

Many-to-Many Relationships
This is yet another type of relationship which is quite common in real-life situations.
In this case, associated with each entity in set A, there may be zero or more entities
in set B and vice-versa. A very common example of this type would be the
relationship between the entity-set SUPPLIERS and the entity-set PARTS. A supplier
may supply many parts, while a part may be supplied by many suppliers.

Guidelines for Constructing the Entity-Relationship Model
Having understood the basic components, you are now in a position to consider the
construction of an E-R model. The principal steps involved in this exercise are:

• Select relevant entity-sets for the real-life situation under consideration

• Select relevant attributes for each entity-set

• Identify the key-attribute for each entity-set

• Determine the type of each of the relationships between the entity sets

• Draw the E-R diagram

Consider the situation in which the academic administration often finds itself. It has
to handle data regarding students, faculty, and the courses being offered, and
possible areas of specialization. It is worthwhile to consider the following points
before you move to construct the model:

• The students specialize in one or more areas

• The students study a specific course

• A course belongs to an area of specialization

• A faculty member belongs to an area of specialization

• A student can be either a doctoral student or a degree student

• A faculty member guides a doctoral student

• Certain courses have certain other courses as prerequisite

• A faculty member offers a specific course

From the above, the desirable entity-sets, their relevant attributes and the
appropriate key attributes can be determined.

1. Entity-set : Students
Attributes : Roll No, Name, Date-of-birth, Basic Educational
Qualification, No. of years of work experience


Key : Roll No.

2. Entity-set : Faculty-members
Attributes : Name, Date-of-birth, Date of Joining, Educational
Qualifications, Total No. of years of Teaching Experience
Key : Name

3. Entity-set : Courses
Attributes : Course-No, Course-Name
Key : Course-No

4. Entity-Set : Areas (of specialization)
Attributes : Name of the Area
Key : Name of the Area

5. Entity-Set : Doctoral-students
Attributes : None

This entity-set is needed to identify individual doctoral students. The reason for
assigning a separate entity-set to doctoral students is to be able to establish the
relationship between these students and their faculty guides, in the actual database.

Now you are in a position to identify the different relationships amongst the above
entities. These are:

1. SPECIALISES_IN: This is a many-to-many relationship between STUDENTS
and AREAS

2. STUDIES: This is a many-to-many relationship between STUDENTS and
COURSES

3. INCLUDED_IN: This is a many-to-one relationship from COURSES to AREAS

4. BELONGS_TO: This is a many-to-one relationship from FACULTIES to
AREAS

5. GUIDES: This is a one-to-many relationship from FACULTIES to
DOCTORAL- STUDENTS

6. OFFERS: This is a many-to-many relationship from FACULTIES to
COURSES. The assumption here is that a course may be offered by more than
one faculty-member

7. IS A: This relationship is one-to-one between STUDENTS &
DOCTORAL-STUDENTS

8. PREREQUISITE_FOR: This is a many-to-many relationship from COURSES
to COURSES because a course may be a prerequisite for more than one other
course and may have more than one other course as prerequisites for itself

Now you are ready to draw the E-R diagram representing the E-R model. First let us
discuss the relevant diagrammatic conventions and then actually draw the diagram


Conventions for Drawing E-R Diagrams
Following are the conventions for drawing E-R diagrams:

· Entity-sets are represented by rectangles.

· Attributes are represented by circles. These are linked to the appropriate
entity-sets by undirected edges.

· Relationships are represented by diamond shaped boxes. These are linked to
the appropriate entity-sets by directed edges.

An E-R diagram for the Academic Administration database is:

As already stated earlier, the E-R model brings out the essential features of data
modeling for databases. Data modeling in practice, is done according to the one of
the three models, viz., hierarchical, network and relational. The three models too,
establish relevant entities and the relationships amongst them; they differ in the way
they represent data about both entities and their relationships. The E-R model,
however, is free from these relatively physical aspects of data representation and
therefore can be said to be a general view of the three models unifying them at a
relatively abstract level.

Case Study – Entity Relationship for a Library
The library needs to create a database to automate its data storage and processes.
For this you first need to know how a library functions, what are its transactions and
what data it needs to store for activities. To arrive at an ERD for a library, list the
entities and its attributes you require before putting them into a diagram:

 Member

 Member ID

 Name


 Address

 Area

 Zipcode

 phone number

 Age

 Date of membership

 Age group

 Branch ID

 Book

 Book ID

 Book name

 Author name

 Publisher

 Published Year

 Category

 Branch

 No of copies in store

 Transaction

 Transaction ID

 Member ID

 Book ID

 Issue date

 Return date

 The actual return date

 Fine to be paid by the member for default

 Category (for books)

 Category ID

Category description

 MemberFee

 Age group grade

 Minimum value

 Maximum value

 Fee amount

 Branch

 Branch ID

 Branch name

 Address

 Location

 Phone number

 Date of establishment

 Availability

 Book id

 Available copies

 Publisher

 Publisher Id

 Name

 Address

The list arrived at above can be depicted as an ERD in the following manner:


Communicating with RDBMS

In order to communicate with the RDBMS, that is, to access data, you have a query
language called a Structured Query Language (SQL). A query can be defined as a
request made to access data from the database. This definition refers not only to
data retrieval, but also defining, manipulating and controlling data. The need to
access data from the database on an ad-hoc basis led to the origin of SQL. The origin
of SQL can also be associated with one of Codd‘s Twelve Rules, where in he states
that a relational database must have a high level language capable of handling all
communication with the database. Although there are several languages that can
access data from the database, SQL is the primary language for communicating with
RDBMS. SQL can also operate on non-relational databases.


Features of SQL
The features of SQL are as follows:

• SQL is a Declarative Language (non-procedural). You need not provide the
Step wise procedure to be followed in order to access the data. Instead, it
allows you to simply declare what data you want without having to provide
details about where it is located or how to get it. It leaves it to the DBMS to
determine the best way to get it.

On the contrary, procedural languages such as C, or C++ provide a step-wise
procedure telling the computer exactly what is to be done. The advantage
being that these instructions given ahead of time can be compiled into
machine language for fast execution. But these languages lack flexibility, that
is, do not adapt to changes easily.

• SQL is a set-based language. Since the relational model uses the concept of a
mathematical relation that is, has its theoretical basis in set theory, SQL
supports set operations and relational algebra operations.

A set is an unordered collection of elements of the same type and structure. Tables
(or relations) are called sets and rows (or records) are their elements. In a relational
database the physical positioning of rows is not important, that is, they are
unordered, so SQL being a set-based language can operate on an entire table, or
multiple tables at once. In contrast, a procedural language can operate on a single
record at a time as it uses ‗files‘ which are similar to tables, wherein records have a
physical ordering.

Relational algebra operations can be divided into two groups:

 Set operations from mathematical set theories including Union, Intersection
and Set Difference.

 Operations developed for relational databases, which include Select, Project
and Join.

Set Operations
Set operations include the following:

 Union

 Intersection


 Set Difference

Union

To understand the union operation look at the following two tables, States1 and States2:

The above two tables contain names of US states. Some of the state names are
common in both the tables.
In order to return the state names that are in States1 or in States2 or in both
States1 and States2, eliminating duplicate rows, you use the UNION operation.
The notation for union of tables is:
States1 UNION States2 = States3
The result of the union operation is as follows:

States 3
Hawaii
New Jersey
Indiana
Florida
Arizona
Colorado
California
Alaska
Texas
Georgia
Virginia
Wisconsin
Kansas
Kentucky
Iowa

The resulting table contains the state names that are contained in both the tables,
but displaying the common state names only once.


Intersection
The intersection operation returns state names that are in both States1 and
States2, that is, it returns a third table that contains only common state names.
The notation for intersection of tables is:
States1 INTERSECTION States2 = States3
The result of the intersection operation is as follows:

Set Difference

The result of the set difference operation returns state names that occur in the
States1 table but not in the States2 table, or also vice versa. The result is as
follows:

Relational Operations
In addition to set operations, certain other operations were developed for relational
databases, which include:

 Selection

 Projection

 Joins

Selection
The selection operation enables you to retrieve only specific rows that match your
criteria. For example, you have two tables TabA and TabB.


Using the selection capability of SQL, you can retrieve those rows from TabB table
where Col1 value is 2.
The result set of rows would be:

Projection
The projection operation enables you to retrieve only specific columns from the total
columns available. For instance, using the projection capability of SQL, you can
retrieve only Col2 values from TabA table.
The result set would be:

Joins

The join operation enables you to retrieve data from more than one table. For
instance, using the joining capability of SQL, retrieve rows from both TabA and
TabB by joining Col1 as they have equivalent values.
The result set of joining the two tables would be:

Why SQL is Preferred?
SQL is favored due to the following reasons:


 A wide range of users, including those with little or no programming
knowledge can use it.

 It is an English-like language.

 It is non procedural, that is, the user need not specify the method to be
followed to arrive at the result, rather just specify the result that needs to be
arrived at.

 It allows defining, retrieving and manipulating data in the tables.

Relational Data Model Concept
This rule states that all data is represented as tables. Data can be viewed in no other
way.

Codd’s Rules
Dr. E. F. Codd, was the creator of the relational data model. It was published as a two-
part article in ComputerWorld (Codd, 1985). It contains a list of 12 rules that determine
whether a DBMS is relational and to what extent it is relational. These rules are a very
useful yardstick for evaluating a relational system. In the article, Codd mentions that
according to these rules, there is no database yet that is fully a relational system. He says
that rules 6, 9, 10, 11 and 12 are difficult to satisfy. Each of the twelve rules is briefly
discussed below.

The Information Rule

All information in a relational database is represented explicitly at the logical level and in
exactly one way through values in tables.

Guaranteed Access Rule
Each data item must be accessible by providing table name + primary key of the row
+ column name.


Systematic Treatment of Null Values
Handle missing or non-applicable data, that is, nulls, in a consistent manner. Nulls
should have no values and should simply be missing data. Treating Null as a zero for
missing numeric data or as a blank for missing character data violates this rule.
Vendors provide the ability to use default values for missing data, if so desired.

Self-describing Database
In addition to storing user data, a relational database must contain data about itself.
There are two types of tables in RDBMS: user tables, which contain data required by
users, and system tables, which contain data about the database structure. The data
that describes the database structure is called meta-data. The collection of system
tables is called as the system catalog or data dictionary. Storing any part of the data
dictionary in operating system files would violate this rule.

Comprehensive Data Sublanguage
The data access language (SQL) must be the only means of accessing data stored in
the database. The language must support relational operations and set operations
with regard to the following:

 Data definition

 Data manipulation

 Integrity definition

 Transaction control

 Data control

Accessing data files (files that contain the actual data), through a utility other than
an SQL interface, violates this rule.

View Updating Rule
There are situations where users may require only a part of the table information or
information from a collection of tables. Such requirements can be met by creating
‗Views‘. Views are virtual tables, which unlike a table contains no data, just
statements that return data in the form of tables.
This rule states that views should allow updates in the underlying tables and vice
versa.
But SQL supports only updates of single tables at a time (see rule 7), therefore if,
you join three tables to create a view, and try to update that view, then DBMS would
fail to translate these updates to the underlying tables, thereby violating this rule.
Also, a view not including the column that uniquely identifies each record in a table
cannot be updated, thus violating the rule.
This rule will be dealt in depth in the chapter on ―Views‖.

High-level Insert, Update and Delete
This rule states that in a relational database, the query language (SQL) must be
capable of performing manipulations (such as, inserting, updating or deleting data)

on sets of rows in a table. A database that supports only row-at-a-time manipulation
cannot be considered as relational.

Physical Data Independence
This rule states that in a relational database, any changes made in the way data is
physically stored (that is, data stored in file systems specific to the machines
operating system) must not affect applications that access data. If a file supporting a
table was moved from one disk to another or renamed, then this should have no
impact on the application.

Logical Data Independence
This rule states that changes to the database design should be done in a way without
the users being aware of it. The change could be to expand the database (adding a
new table) or to reduce it, but the application that refers to the data (logical) must
work as before. If a single table were split into two, then a view would have to be
provided joining the two back together so that there would be no impact on the
application.

Integrity Independence
In order to be considered as a relational database, all data integrity, which are
definable in the query language referred to in rule 5 must be stored in the database
as data in tables, that is, in the catalog and not in the application programs.

The data integrity rules that should apply to relational databases are:

Entity integrity- the primary key column cannot have missing values

Referential integrity- for every foreign key column value there must exist a
matching primary key column value.

Integrity rules are covered in depth in a later chapter.

Distribution Independence
In a relational database, data can be stored centrally (on a single system) or
distributed (across a network of systems). The data in a centralized database should
remain logically unaffected if they are distributed across systems. For example, a
user should be able to retrieve data from two tables distributed across two terminals,
the same way, as they would retrieve them if stored in the same terminal.

Non-subversion Rule
This rule states that there should be no other access path to the database, other
than SQL. Any other access language may bypass (or subvert) security or integrity
rules, which otherwise would be obeyed by the regular data access language.


Summary
In this chapter, you have learnt that:

Files prove to be inefficient due to their redundant nature when the number of
applications increase. This gave rise to the concept of Database.

Database is a collection of logically related data stored on media.

To handle and maintain this database, a software, Database Management
System (DBMS) came into existence.

They are of 4 types:

1. Hierarchical Database Management System

2. Network Database Management System

3. Relational Database Management System

4. Object Relational Database Management System

 Out of these types, Relational Database Management System (RDBMS) was
popularly used which enables to relate data in one table to the data in
another.

Normalization is the process to stabilize a database, by reducing data
redundancy.

Data can be stabilized through 3 stages:

1. First Normal Form (1NF)

  2. Second Normal Form (2NF)

3. Third Normal Form (3NF)

To access the stabilized data, Structured Query Language (SQL) is widely
used.


Lab Exercise
In the following questions, you are given the Universe of Discourse
(UOD, that is, the general outline at the level a user would normally
describe) of some typical enterprises. Please note that a UOD is not
a smooth and structured description.

Define:

 Entity and associated attributes

 Relationships between entities and type of relations

 Draw the Entity-Relationship diagram

1. LIBRARY SYSTEM:
A library keeps records of current loans of books to borrowers. Each borrower is
identified by a borrower number and each copy of a book by an accession number.
The name and address of each borrower is held so that overdue loan reminders etc.,
can be sent whenever necessary. The information required about books is the title,
authors, publishers, publication date, International Standard Book Number (ISBN),
purchase and price and current price. There is a restriction on the number of books
a borrower may have on loan at any one time, the limit depending on whether a
borrower is classified as having junior or adult status. Books out on loan may be
reserved by other borrowers pending their return. The library stocks only the
hardback version of the book. If a new edition of the book is published, all copies of
earlier editions are withdrawn from stock.

2. A UNIVERSITY:
A University has number of departments. Each department has its faculty.
Departments enroll students.
Each faculty member may conduct one or more courses and one or more students
register for a course. The courses are conducted in classrooms based on a prepared
time-table.
Each subject has a prescribed text book and host of recommended reference books.

A faculty member may guide more than one project and the same project may be
done by more than one student.

3. DEPARTMENTAL STORE:
The data in the database of a department store are defined as follows:

 Each employee is represented. The data about an employee are his employee
number, name, address and the department he works for.

 Each department is represented. The data about departments are its
employees, manager and items sold.

 Each item sold is represented. The data about items are its name,
manufacturer, price, model number (assigned by the manufacturer) and an
internal item number (assigned by the store).


 Each manufacturer is represented. The data about a manufacturer are its
name, address, items supplied to the store and their prices. Various
employees work for a department and each department stores items supplied
by various manufacturers.

A MANUFACTURING ENTERPRISE:
A manufacturing company consists of a number of divisions. Each division, in turn,
consists of one or more departments. Each employee of the company belongs to
only one department at any point of time. Orders are executed at the divisional level.
Any number of departments (as required) may execute an order. A department may
also execute a number of orders. Employees work on various orders in the
organization.

An order needs several parts. A part may be needed by several orders. A part itself
may consist of sub parts. Alternatively, a part may be a support of a super part.
Parts are housed in warehouses which are at specific locations. Suppliers supply
parts.

AN AIRLINES ENTERPRISE:
An Airlines company has a fleet of aircraft‘s which it employs to carry passengers
from one airport to another.

A flight (i.e. an aircraft assigned for trip from one airport to another) is manned by a
crew. A time table is available for all the flights. At each airport, based on the flight
schedules, service schedules are drawn up for the ground staff.

At each airport, for each flight, caterer(s) provide the necessary food and
refreshments according to the catering schedule.

The maintenance of aircraft‘s (that are not in operation and which have been tagged
for maintenance) is done by the maintenance staff according to the maintenance
schedule. Maintenance is conducted at the airports where hangar(s) are available for
the type of aircraft in question.


Chapter 2

Introduction to Oracle10g
Key features of Oracle10g
Components of Oracle10g


Objectives
At the end of the chapter, you will be able to:

 Identify the different components of Oracle10g

 Identify the enhanced features of Oracle10g


Introduction
The traditional database systems such as relational, hierarchical and network have
been successful in developing the database for traditional business applications such
as banking and railway reservations. But, when it comes to more complex business
applications such as databases for scientific work, engineering designs,
telecommunications, geographic information system and multimedia, the traditional
database systems cannot handle them because the requirements and characteristics
of these applications are different from the traditional business applications. These
applications require more complex structures for:

 Storing data related to real world objects such as engineering diagrams,
molecular structures, or financial instruments

 Transactions, which would be for longer durations

 New data types required for storing complex multimedia data such as audio
and video clips, images and maps.

Oracle10g Database meets the above needs as it tightly incorporates ORDBMs
concepts.
Object Relational Database Management System (ORDBMS) is a database
management system that has evolved from the relational model and includes both
the relational and object-oriented technology. Oracle8.0 was the first version of the
Oracle database to incorporate object-oriented technology.

In Oracle10g, ‗g‘ stands for GRID. This release is focused on efficient management of
infrastructure based on its grid computing mechanism.
Now, the question arises what is Grid Computing?

The idea behind the grid computing is to utilize the resources available, to the
maximum extent by dynamically pooling it based on the requirement of the end user
during the peak hours. In this case, the end user need not know the whereabouts of
the resource.

Infrastructure Advantages

Data Availability
Internet database availability is critical for any eBusiness application. Oracle10g
focuses on the following areas to achieve continuous data availability:

 Zero data loss data protection environment

 Support for online reorganization and redefinition architecture to reduce
offline maintenance requirements

 Provides more complete and precise database repair capabilities by ensuring
better prevention and improved handling of disk corruption


Scalability and Performance
Oracle10g enables eBusiness to scale millions of users performing millions of
transactions per hour by focusing on the following key areas:

 Transparent cluster scalability and performance: Oracle10g along with its
grid mechanism includes Real Application Clusters (RAC) that has been designed to
provide continuous data availability while increasing the scalability and performance
of the database infrastructure. RAC was introduced in Oracle9i, which is an
arrangement, where a single database runs on a group of servers that are clustered
together. With Oracle9i RAC all servers in the cluster act as backup to each other
while at the same time increasing the overall computing power within the cluster.

 Scalable session state management: Oracle10g allows more users to be
hosted on the same or larger hardware platforms due to its new grid mechanism
where in new nodes can be added to the cluster when the load increased.

 Optimized features critical for eBusiness: Oracle10g focuses on the following
performance areas, critical for eBusiness:

Support for large datafiles. Enterprises planning to setup Data Warehouse
and transaction systems can extend their Oracle database upto 8
Exabytes, which is equivalent to 8 million terabytes.

 Improving the performance of many of today‘s business applications by
providing support for enhanced native compilation and improved
optimization of PL/SQL.

 Improving optimization plans and reducing resource usage by adding
memory and CPU costs to the cost based optimizer cost calculation
algorithm

 Improving performance in Data Warehouse and Online Transaction
Processing (OLTP) environments by general I/O improvements such as
better sharing of run-time data structures, larger buffer caches and
deferrable constraints.

Security

Oracle10g provides secure application development and deployment
platform by focusing on:

A strong three-tier security, which ensures that a user can access the database
only through the middle tier. As a result user identities are maintained securely
through all tiers of an application, with centralized user and privilege management in
Oracle Internet Directory.

Deep data protection through enhancements in Virtual Private Database, fine-grained
auditing and Oracle Label Security

Development Platform for eBusiness Applications

Oracle10g continues to provide the best development platform for both eBusiness
and traditional application development by focusing on the following key area


 Enterprise Java Engine:

Java support in Oracle10g focuses on improving the performance of the embedded
Java Virtual Machine, new JDBC and SQLJ functionalities, and enhancement to Java
stored procedures.

 SQL and PL/SQL improvements:

Oracle10g has introduced many enhancements in SQL and PL/SQL to meet modern
development requirements. Oracle10g supports inheritance, type evolution, and
dynamic method dispatch to increase the usefulness of objects. Along with the
existing datatypes, new datatypes have been introduced. It also supports CASE
statement, ANSI compliant joins and reserved naming conventions.

 New Dataypes

In addition to the existing datatypes, new datatypes have been
introduced. They are BINARY FLOAT and BINARY DOUBLE. Bioinformatics
and life science applications have benefited from these datatypes to solve
complex computations.

 Alternative Quote operator:

Strings containing single code as literal, can be now be escaped using
customized symbols using Q operator.

 Environmental Scripts after each CONNECT:

Previously glogin.sql and login.sql scripts were read at the startup of
iSQL*Plus. Now, these scripts are automatically run after each user
connects to the database.

 Multiple Pages Output:

Output spanning over multiple pages can now be viewed using NEXT
button or can be viewed on a single page as in the previous version.

SQLPlus Recycle Bin:
SHOW RECYCLEBIN [original_name] command has been introduced to
view the dropped database objects.

Oracle Flashback Feature:

This feature has helped a developer to reduce errors.

 Oracle Flashback Table:
FLASHBACK TABLE statement in SQL allows to recover the accidentally
dropped table.

 PURGE TABLE:
This statement removes the database objects permanently from the
Recycle Bin.


Oracle Flashback

Version Query
Changes in the table data can be viewed using VERSION BETWEEN clause. A
changed transaction‟s undo records stored in the database must be available.

Oracle Flashback Transaction Query
Changes made to the tables can be viewed using
FLASHBACK_TRANSACTION_QUERY view. This can be helpful for auditing,
debugging and even performance analysis.

Improved MERGE Functionality
MERGE Statement has been improved by making WHEN MATCHED and WHEN
NOT MATCHED clauses optional. Also, WHERE clause can now be used in this
statement to restrict the values while inserting into target table.

 Regular Expression functions:
Regular Expression functions have been introduced which works beyond the
POSIX (Portable Operating System For UNIX) standard for matching ASCII
characters.

Improvements to PL/SQL:

 Bulk Binding Enhancements:
Performance related to BULK BINDING has been enhanced by introducing
INDICES OF and VALUES OF clauses. INDICES OF clause permits sparse data in a
collection. VALUES OF clause refers one array values based on another array
values.

 Enhanced Native Compilation:
The number of parameters to be set for Native Compilation has been reduced. A
much more tight integration of SQL and PL/SQL runtime engines is made
possible.

 New Packages:

DBMS_WARNING: Warnings generated during compile time can be
dynamically set using DBMS_WARNING package.

UTL_MAIL: This is an enhancement to UTL_SMTP package. Using this, E-
mails can be sent through a PL/SQL API.

UTL_COMPRESS: This package compresses and uncompressed RAW Byte
stream of Large Object (LOB) data.

DBMS_METADATA: This package extracts the metadata of a database
object, which can be obtained either in XML version or DDL.


 CLOB and NCLOB Implicit Conversions:

You no longer need APIs to convert CLOB to NCLOB and vice versa. This
release supports their implicit conversion.

Oracle10g and the Internet
Oracle8i was the first internet-based database in the world. It recognized that
Internet provided the safest and efficient access to data to all users spread across
the globe.

Oracle10g continues the Oracle9i focus on the Internet by providing a series of
enhancements targeted at eBusiness environments.
To be able to allow commerce on the net, your system needs some important
hardware configuration so that it can support the transactions between the database
and the Internet. One important step is to identify the kind of machines that you
need.

Fat client or Thin client

There are two kinds of client available, fat client and a thin client. Before debating
whether everybody needs a fat client or a thin client, you need to understand what
these terms mean.

A fat client is a traditional PC system, which if purchased today would have 64MB or
more of memory, 6GB or more of disk space, a fast paced processor and/or a CD-
ROM drive. A fat client would have all the codes locally within them.
A thin client is a personal computer used mainly for functions like e-mail,
presentation of information and word processing. It stores no code/programs locally
and only accesses them from the database.

The reasons for shift from fat clients to thin clients are due to the following
limitations:

 Loss of critical pieces of information if they reside only on a disk drive in the
event of a break down

 The need for upgrading the software every time a new version comes into the
market. This raises a lot of questions. Should the release of new versions
force the end users to upgrade their software? Whether to assume that end-
users have the necessary skills to upgrade their software? Should the
support people go out to hundreds of PCs and upgrade them individually?
Isn‘t this a waste of their time when these activities are only for someone who
uses e-mail?

The above complexities of fat client led to the development of a more mature
network known as the Network Computing Architecture (NCA) wherein the end user
would not be required to deal with issues like loss of data due to virus attacks or deal


with upgradations. Trained professionals would handle these at some central
location.

Oracle Internet Platform

The positioning of Oracle as an Internet solution company is due to the adoption of
NCA. This architecture enables the development, deployment and integration of
applications within a networked computing environment. Oracle has developed NCA,
which is based on the following three separate tiers:

 A thin client tier, which is the layer responsible for the presentation of the
information. It is the desktop PC running a web browser.

 An application server tier (the middle tier), which is the layer wherein all the
application codes are processed.

 A database server tier, which is the layer where all the data is stored.

A Three-tier Architecture

The NCA is designed such that the presentation layer is separated from the
application layer. The application layer resides on a server separate from the
database server and it is assumed that the application server is the fat client. The
application server as well as the database server can be moved to a machine with
more resources, which could be placed in a central location and be managed by
trained professionals thereby keeping the end users away from all the complexities.

Based on the above theoretical concepts, Oracle 10g release is broadly divided into:

• Oracle Database 10g

• Oracle Application Server 10g


• Oracle Enterprise Manager 10g Grid Control

• Oracle Database 10g

Oracle10g database supports Grid Computing architecture. Here, multiple database
servers are pooled together to form a cluster. It enhances utilization of resources. It
efficiently stores and manages the structured and unstructured data such as:

• Spreadsheets

• Word documents

• PowerPoint presentations

• XML

• Multimedia data types like MP3, graphics, video and more.

Oracle 10g facilitates two-tiered or multi-layered distributed database environments
like client/server and Web-based applications. Large objects need be stored inside
and outside the database. Oracle Database 10g has services which help to manage
and retrieve data, located outside the database.

• Oracle Application Server 10g
A complete infrastructural platform is provided for developing and deploying
enterprise applications, integrating many functions including a J2EE and Web
services run-time environment, an enterprise portal, an enterprise integration
broker, business intelligence, Web caching, and identity management services. The
existing 9iAS gets further enhanced with the introduction of new grid computing
features. It further integrates users, applications and data across your organization.

• Oracle Enterprise Manager 10g Grid Control
It is the consolidated, core management console that forms the basic framework to
automatically initiate administrative tasks across the networked environment. With
Oracle Grid Control, multiple hardware nodes, databases, application servers and
other targets can be brought together into single logical entities.

Oracle10g continues Oracle Corporation’s lead on providing the best platform support
for business intelligence by focusing on the challenges raised by large volume of data
and the need for real time complex analysis in an eBusiness environment. Oracle10g
provides the business intelligence platform by enhancing and extending database
support for Online Analytical Processing (OLAP), data mining and extraction.


Summary
In this chapter, you have learnt that:

 In Oracle10g, ‗g‘ stands for GRID. It is a technology, which groups similar
resources into a cluster. This allows efficient utilization of resources. This helps
us to design complex business applications.

 Data availability, security and development for e-business applications are
some of the advantages with Oracle10g.

 Oracle10g structure is based on NCA (Networked Computing Architecture),
which is developed to overcome the problems with fat client. It enables
development of applications within networked computing environment.

 Oracle10g has come up with new features in SQL* Plus environment, new
commands in SQL language and improvements in PL/SQL, making it more user
friendly.


Chapter 3

Data Retrieval

iSQL*Plus Interface
Logging into Database using iSQL*Plus
Projection, Selection and Join Terminology
Differences Between SQL and iSQL*Plus
Review of Syntaxes for Basic SQL SELECT statements
Arithmetic and Concatenation Operators in SQL statements
Alternative Quote Operator
Saving SQL Statements to Script Files


Objectives

At the end of this chapter, you will be able to:

 Use the SELECT statement to extract data

 Understand the various categories of SQL statements


Retrieving Data
Oracle uses the Structured Query Language (SQL) to communicate with the
database. The SQL statement used to extract data from the database is the SELECT
statement. The SELECT statement informs the database about the data you want to
retrieve. SQL statements need to be executed in an environment where, they would
be interpreted and sent to database.

iSQL*Plus Environment

iSQL*Plus introduced in Oracle9i is a browser environment in which SQL statements
are executed. SQL*Plus environment was the default environment in the prior
releases of Oracle. SQL*Plus is still available.

Since the Oracle server understands only SQL worded statements, all Oracle tools
support SQL syntax. Implementation of SQL through SQL*Plus environment or
iSQL*Plus environment meets the ANSI (American National Standard Institute) and
ISO (International Standards Organization) standards.

On issuing an SQL statement, the statement first gets stored in a part of the
memory, which is called the SQL buffer. The SQL statements (stored in the buffer)
are then recognized and submitted to the Oracle database for execution by the
SQL*Plus or the iSQL*Plus environment.

The iSQL*Plus environment helps to perform the following tasks:

 Executing SQL statements to extract, add, change and remove data from
the database

 Formatting and performing calculations on query results so as to produce
more meaningful reports

 Storing SQL statements in files (called script files) so that they could be
used later. These files have .sql file extension.

How to log in to SQL*Plus and iSQL*Plus?

The steps involved in logging into SQL*Plus and iSQL*Plus environments are
different.

Logging in to SQL*Plus Environment

Logging in to SQL*Plus environment depends on the type of operating system you
are working on.


Logging in through a Windows environment:
1.Click Start-> Programs-> Oracle – OraDb10g_home1

2. Select Application Development -> SQL Plus


3. Enter username, password and the connect string.

Logging in through a command-line environment:

 Log on to the DOS prompt
Enter SQL*Plus command as follows:

sqlplus [username[/password[@ ConnectString]]]

Where,username is the database username assigned to each user.

password is the password the user enters to gain access to the database. The
password is visible on entering it at the command line. Therefore, to ensure the
integrity of the password, do not enter it at the command line. Instead enter it at the
password prompt.

@ ConnectString is the alias through which the user has to access the database.

Logging in to iSQL*Plus Environment
The steps to log in to iSQL*Plus environment are as follows:
1. Initiate the browser and enter the URL address of the iSQL*Plus
environment. iSQL*Plus browser window is displayed.


2. Enter the username and password as shown in the following screen.
Click the
Login button.


After you log in to iSQL*Plus, you see the iSQL*Plus window as follows:

Within the windows browser, the key areas of the iSQL*Plus window are the:

Enter Statements field: The area to enter the SQL statements and iSQL*Plus
commands.

Execute button: Click to execute the statements entered in the Enter
Statements field.

Load Script button: Click to access the area for entering the name and
location of a file (containing the contents of the Enter Statements field, which
has been saved) or the URL for the script you want to execute.
Save Script button: Click to save the contents of the Enter Statements field to
a file. It is suggested that you save these files with .sql extension.

Cancel Button: Click to Cancel the query presently entered by the user. A
confirmation is displayed at the end.

Clear Screen button: Click to clear text from the Enter Statement field, output
and stops any script running at that time.

Help icon: Click to access iSQL*Plus help documentation.


iSQL*Plus Commands

iSQL*Plus has a set of commands, which are different from the SQL statements.
These commands need to be entered one line at a time. In order to continue a
command on the next line, end the current line with a hyphen (-).

iSQL*PLUS commands can be abbreviated. For instance, a command CLEAR BUFFER
could be written as CL BUFF. iSQL*Plus commands are not stored in the SQL buffer.

The main categories into which iSQL*Plus commands have been divided are:

 Environment – It affects the behavior of SQL statements for the session.

 Formatting – It formats the query output.

 File manipulation – It saves SQL statements into script files and, loads and
runs them whenever needed.

 Execution – It sends SQL statements from the browser to the Oracle
server.

 Editing – It modifies SQL statements in the Edit window.

 Interaction – It allows you to pass values into the SQL statements and
also print messages to the screen.

SQL Vs iSQL*Plus
SQL is the language used to communicate with the Oracle server from any
tool or application. iSQL*Plus is the Oracle tool, which recognizes and
submits the SQL statements to the Oracle server for execution, and based
on the query result, it produces formatted reports using its own commands.

The following diagram depicts the SQL and iSQL*Plus interaction:


Browser SQL Statements

iSQL*Plus Oracle
Server

iSQL*Plus Commands Query Output

Formatted Report

Features of SQL are:

 It is a non-procedural language of ANSI standard

 It is an English-like language

Features of iSQL*Plus are:

 It is accessible from a browser

 It supports ad hoc entry of statements

 It formats query output into a basic report

 It can access local as well as remote databases

 It controls environmental settings


SQL Statements
The SQL statements can be categorized with regard to their functionality.
They are:

 SELECT statements - used to retrieve data from the database.

 Data Definition Language (DDL)- used to create and maintain the
database structure. The DDL statements are:

 CREATE

 ALTER

 DROP

 RENAME

 TRUNCATE


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