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SQL Query Writing and Fundamentals

Reference Guide

Welcome to the SQL Query Writing and Fundamentals Reference Guide. This guide contains all the text content covered in the online course.

For the animated screen Demonstrations, Simulations and Quizzes referred to in this PDF

Guide please visit the online course provided by www.SQLSteps.com

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Table of Contents

Module 1: Database: An Overview .......................................................................... 6

What will you learn in this module? ............................................................................ 6

What is a Database? ............................................................................................... 6

What is a Database Management System? .................................................................. 7

What are the advantages of a DBMS? ......................................................................... 7

What is a Relational Database Management System? .................................................... 8

What is a Table? ..................................................................................................... 8

What are Data Types? ............................................................................................. 9

Describing Relationships ........................................................................................ 10

Listing the Different Types of Relationships ............................................................... 12

Understanding Primary and Foreign Keys .................................................................. 13

What is Normalization? .......................................................................................... 14

Module 2: SQL: An Overview................................................................................ 16

What will you learn in this module? .......................................................................... 16

What is SQL? ....................................................................................................... 16

What is the Role of SQL?........................................................................................ 17

What are the Functions of SQL? .............................................................................. 17

What are the Components of SQL? .......................................................................... 17

Module 3: Getting Started with Microsoft SQL Server ............................................... 20


What is Microsoft SQL Server? ................................................................................ 20

Using the SQLCMD Utility ....................................................................................... 21

Using SQL Server Management Studio for Scripting .................................................... 24

What is the Debug Feature? ................................................................................... 26

Module 4: Using the SELECT Statement ................................................................. 27


Understanding the SELECT Statement....................................................................... 27



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Using the SELECT Statement ................................................................................... 28

Executing a Query Using the SQL Server Management Studio....................................... 28

Retrieving Data from Specific Columns in a Table ....................................................... 29

Filtering Rows with the WHERE Clause ....................................................................... 29

Using Operators to Create Conditions ....................................................................... 30

What is the NULL Keyword?.................................................................................... 33

Sorting the Result Set with the ORDER BY Clause ........................................................ 34

Using the DISTINCT keyword to Suppress Duplicate Rows ............................................ 35

Viewing Top Rows in a Large Result Set .................................................................... 36

Using Wildcards to Retrieve Data ............................................................................. 37

Working with Calculated Columns ............................................................................ 39

Module 5: Working with Multi-table Queries ............................................................ 41


What are Joins? .................................................................................................... 41

Understanding Types of Joins ................................................................................. 42

Creating Joins with the WHERE Clause ....................................................................... 46

Module 6: Using SQL Functions in Queries .............................................................. 48


Understanding SQL Functions ................................................................................. 48

What are Aggregate Functions? ............................................................................... 49

What are Mathematical Functions? ........................................................................... 52

What are Date Functions? ...................................................................................... 55

What are String Functions? .................................................................................... 56

What are Conversion Functions? .............................................................................. 59

Module 7: Grouping Data..................................................................................... 62


Defining Grouping of Data ...................................................................................... 62

Working with the GROUP BY Clause .......................................................................... 62



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Working with the HAVING Clause .............................................................................. 63

Adding Totals and Subtotals to Grouped Data ............................................................ 64

Module 8: Working with Tables ............................................................................. 68


Using the CREATE Statement ................................................................................... 68

Modifying a Table ................................................................................................. 69

Deleting a Table Using the DROP Statement ............................................................... 70

Using the CREATE DATABASE Statement .................................................................... 70

Using the DROP DATABASE Statement ....................................................................... 71

Module 9: Manipulating Data in Tables ................................................................... 72


Using the INSERT INTO Statement ........................................................................... 72

Using the UPDATE INTO Statement ........................................................................... 73

Using the DELETE Statement ................................................................................... 74

Using the TRUNCATE Statement ............................................................................... 74

Module 10: Working with Programming Objects ........................................................ 76


Understanding what is a View ................................................................................. 76

Using the CREATE VIEW Statement ........................................................................... 77

Using the SELECT Statement to Access a view ........................................................... 78

Modifying a View .................................................................................................. 78

Deleting a View .................................................................................................... 79

Renaming a View .................................................................................................. 79

What is an Index? ................................................................................................. 79

What is a Stored Procedure .................................................................................... 80

Using the CREATE PROCEDURE Statement ................................................................... 81

Using the EXECUTE Statement ................................................................................. 83

Using the ALTER PROCEDURE Statement .................................................................... 84



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Using the DROP PROCEDURE statement ...................................................................... 85



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Module 1: Database: An Overview

What will you learn in this module?

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

Describe a Database

Define a Database Management System (DBMS)

List the Advantages of a DBMS

Define a Relational Database Management System (RDBMS)

Describe a Table

Explain Data Types

Describe Relationships

Explain Primary and Foreign Keys

Define Normalization

What is a Database?

A database is a logical collection of data. Data can be easily accessed, managed, and updated using a database. Typically, a database stores related data in a single file.

Before the advent of databases, data was typically stored in separate files. Managing and accessing related information was difficult and time consuming.



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Customer Information

Product Information

Order Information

Sales Database

What is a Database Management System?

A Database Management System (DBMS) is a set of programs used to manage the database. The DBMS manages, processes and retrieves data in the database. While adding, updating, or deleting information, the DBMS maintains the consistency and integrity of the data.

For example, it will not allow a customer‟s details to be deleted if there are pending orders for the customer.

What are the advantages of a DBMS?

These are some of the main DBMS advantages:

Single repository of data. Related data is stored at a single location. For example, customer, product and order details are all stored in a single database.



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Fast and easy data access. Access to related data is quick and easy. For example, you can easily access details of all orders placed by a customer.

Reduced redundancy. Ideally, only one copy of data is stored and this helps in avoiding duplication of data. For example, a particular customer‟s details are stored only once, and not with every order.

Multiple user access: Multiple users can access a single DBMS at once.

Security. A DBMS provides data security by allowing only authorized persons to access the database. The database administrator decides who can view and update the data.

What is a Relational Database Management System?

A Relational Database Management System (RDBMS) is a DBMS in which data is stored in tables according to the relationships between the data elements. In an RDBMS, each table stores data about a particular type of entity.

For example, details of various customers can be stored in a Customers table. Similarly,

details about various products can be stored in the Products table. The Orders table can

store details of the various products in an order and some details of the customer who ordered them.

What is a Table?

A table is a collection of similar data items. For example, a Books table can contain details

about various books.

Tables consist of rows and columns.

Each row represents a unique entity. Within each row, every column holds one detail about the entity. For example, each row in the Books table contains details of a book.

Each individual detail is stored in a separate column. For example, name of the author is stored in the AuthorName column.



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While defining a table, you must specify:

The name of the table

The names of the columns in the table

The data type for each column

What are Data Types?

A data type specifies the type of information that can be stored in a column.

Column Type of Data

ProductName Text

Cost Real numbers

NumberOfItems Integers

DateOfShipping Date

Logo Image file

For example, NumberOfItems should always be whole numbers or integers, while

ProductName will always be text. Similarly, the DateOfShipping must be a valid date.



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By defining the data type for a column, you are limiting the type of data that can be stored in that column. For example, Cost cannot be text.

What are the Data Types Available in Microsoft SQL Server?

Microsoft SQL Server offers a wide range of data types that can be broadly classified as:

Integer Data Types

Numeric Data Types

Data and Time Data Types

Character Data Types

Binary Data Types

Other Data Types

Commonly used data types in Microsoft SQL Server:

Data type Description Example

Int Whole numbers or integer data Number of employees

float Real numbers Salary

datetime Date and time Date and time of login

Char Character data with a fixed length Telephone number

varchar Character data of variable length Notes

image Images Product image

Describing Relationships

What are Entities?

An entity is anything about which data can be stored. The properties of an entity are known as its attributes.

For example, a book is an entity while details such as its author, title etc are its attributes.



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An entity is represented in the form of a table in a database. The column headings in a table represent the attributes of an entity. The data about an entity is represented in the form of rows.

What is a Relationship?

A relationship is an association that links entities. It establishes the connection between entities.

A library owns books. Library and book are entities, while the relationship between them arises from the library owning the books.

A customer buys many products.



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A teacher teaches students.

Listing the Different Types of Relationships

There are three types of relationships:

One-to-one

One-to-many

Many-to-many

What is a One-to-One Relationship?

In a one-to-one relationship, one instance of an entity can relate to only one instance of another entity.

For example, a company can have only one CEO and that CEO can work only for that company.

Company CEO

What is a One-to-Many Relationship?

In a one-to-many relationship, one instance of an entity can relate to more than one instance of another entity.

For example, a company can have many employees.



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Company Employees

What is a Many-to-Many Relationship?

In a many-to-many relationship, more than one instance of an entity is associated with more than one instance of another entity.

For example, in a company, one employee can be assigned many projects, and one project can have many employees.

Project 1 Project 2 Project 3

Understanding Primary and Foreign Keys

What is a Primary Key?

In an RDBMS, each table must have a unique identifier which uniquely identifies individual rows of the table. This identifier helps in accessing and updating each record efficiently.

This unique identifier is known as the primary key.



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For example, an EmployeeID is unique to each employee and so can be the primary key in

the Employee table. We cannot use the employee‟s name as the primary key as there could

potentially be two employees with the same name.

What is a Foreign Key?

To establish a relationship between two tables, there has to be a common element between the two. In an RDBMS, the relationship is established between two tables when the primary key of a table (table A) is also a column in the other table (table B). In the related table (table B), this common column is referred to as the foreign key.

For example, the CustomerID is a primary key in the Customers table. The Orders

table must also indicate the Customer who placed the order. Thus, the Orders table will

have a CustomerID column that will help uniquely identify the customer who placed the

order. In the Orders table, the CustomerID column is a foreign key.

What is Normalization?

Raw data, when received, has a lot of redundancy and the relationship between the entities is not evident.

Normalization is the process that involves organizing data elements into tables such that:

Data redundancy is eliminated.

Relationships are clearly established.



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Normalization ensures that:

Data integrity is maintained.

Results of queries are predictable.

Changes to data have to be made only once.

Amount of storage required by the database is optimal.

Note: A full study of the process of Normalization is outside the scope of this course.



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Module 2: SQL: An Overview



Explain the Role of SQL

List the Functions of SQL

Define SQL Components

What is SQL?

Structured Query Language, or SQL as it is popularly known, is used to access, manipulate and manage data in a relational database.

SQL was originally developed by IBM and was later adopted as an industry standard. The American National Standards Institute (ANSI) defines the standards for SQL. However, many database vendors have developed variations of ANSI SQL. For example, Microsoft SQL Server uses Transact-SQL (T-SQL).



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What is the Role of SQL?

SQL provides users with a way of interacting with and manipulating databases. With SQL you can:

Create, alter and delete the database and objects such as tables.

Add, modify and delete data within the database.

Set permissions for database objects.

The syntax of SQL statements is simple and easy to learn. SQL provides a standard way of accessing data in any relational database.

What are the Functions of SQL?

Although retrieving data is one of the most important functions of SQL, it also performs the following functions:

Data Integrity – SQL ensures valid and correct data in the database. It protects the data from corruption due to certain inconsistencies or system failures.

Data Retrieval – SQL allows a user to retrieve stored data from the database and use it.

Data Manipulation – SQL allows a user to update the database by adding new data, modify existing data, or deleting data.

Data Definition – SQL allows a user to define the structure of a database, organize data, and create logical relationships among the stored data items.

Access Control – SQL allows a user to set permissions for other users to access, add, or modify data in a database. It protects the stored data against unauthorized access.

What are the Components of SQL?

SQL statements can be divided into three major categories:

Data Manipulation Language (DML)



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Data Definition Language (DDL)

Data Control Language (DCL)

What is Data Manipulation Language (DML)?

Data Manipulation Language (DML) is a set of SQL commands that are used to manipulate the data. With DML, you can insert, update or delete data in tables.

The DML statements are:

SELECT – Retrieves data from a database

INSERT – Add rows to a table in a database

UPDATE – Updates existing rows of a table in a database

DELETE – Deletes rows from a table in a database

What is Data Definition Language (DDL)?

Data Definition Language (DDL) is a set of SQL commands used for creating and managing a database and objects within it. DDL includes all the commands that are required to build and modify the structure of tables and other objects in a database.

The commonly used DDL statements are:

CREATE – Creates a new database, table or an index

ALTER – Modifies a table or a database



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DROP – Deletes a table or an index

TRUNCATE – Deletes all data from a table

What is Data Control Language (DCL)?

Data Control Language (DCL) is a set of SQL commands that are used to control access to a database. Using DCL, you can allow or deny access to specified database objects to certain users or roles.

The commonly used DCL statements are:

GRANT – Allows specified users or roles to perform specified tasks on a database object.

REVOKE – Prevents specified users or roles from performing specified tasks on a database object.



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Module 3: Getting Started with Microsoft SQL Server



Understand what is Microsoft SQL Server

Use the SQLCMD utility

Use SQL Server Management Studio for scripting

Explain the Debug feature

What is Microsoft SQL Server?

Microsoft SQL Server is a RDBMS developed by Microsoft. Besides storing and managing relational data, Microsoft SQL Server allows you to use the data effectively through features such as queries, reports and analysis tools. With its high-performance, scalable architecture it is used in businesses large and small.

Listing the Features of Microsoft SQL Server

Some of the notable features of Microsoft SQL Server are:

SQL Server Management Studio: Enables you to access, manage, and develop various components of Microsoft SQL Server from a common environment.

Analysis Services: Design wide-ranging analytics solutions that provide business insights to power your decisions.

Reporting Services: Generate a variety of reports, including interactive web-based reports that deliver information when needed.

Integration Services: Manage data from a wide variety data sources.

Performance Tools: Enhance the performance of your database server with tools such as Database Engine Tuning Advisor and SQL Server Profiler.

Microsoft Sync Framework: Allows applications to work in an offline mode by enabling synchronization of data on connection.



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Security: Protect your data with powerful, customizable security features including robust authentication and access control, powerful encryption and key management capabilities, and enhanced auditing.

Listing the Two Ways to Execute SQL Statements

Microsoft SQL Server provides two ways to execute SQL statements:

SQLCMD – A command-line tool provided by Microsoft for executing SQL statements. In Windows, the command-line is a text based approach for executing various instructions.

SQL Server Management Studio – A popular graphical tool provided by Microsoft for accessing and managing databases.

Both of these approaches will be covered in this module.

Using the SQLCMD Utility

SQLCMD is Microsoft SQL Server‟s command line utility for writing and executing SQL statements from the command prompt. Using the SQLCMD utility, you can also create and run a set of SQL statements as scripts. The results obtained from the executed SQL statements can be displayed on screen or stored in a file.

Starting the SQLCMD Utility

To use the SQLCMD utility, you first need to access the Windows command prompt. At the Command Prompt:

1. Type sqlcmd.

2. Press ENTER.

You are now connected to the SQLCMD utility. The name of the command prompt window changes to SQLCMD. The cursor changes to 1>, indicating that the first command can be typed there.



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Note: This topic includes a demo. To view this demo, please refer to the online course.

By default, the SQLCMD utility connects to the SQL Server using the Windows login and password.

You can also connect to Microsoft SQL Server using the SQL Server login and password using the syntax:

sqlcmd -U [username] -P [password]

Note: Ask the Database Administrator for the SQL Server User Name and Password, if required.

Executing the SQL Statements

After connecting to SQLCMD, to execute a command:

1. At the command prompt, type the SQL statement.

2. Press ENTER.

3. On the new line, type Go.

4. Press ENTER.

The SQL Command is now executed.

Changing a Database in SQLCMD

When you start the SQLCMD utility, it connects to the default instance of Microsoft SQL Server. The default database is selected as the active database.

To change the active database, use the command:

use <Database_Name>

Note: To set the active database while connecting to SQLCMD, use the syntax: sqlcmd –d

northwind.



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Executing Commands Using SQLCMD

In SQLCMD, you can write an SQL statement over multiple lines. To execute the statement, on a new line type Go and press ENTER.

A sample of a SQL SELECT statement specified over multiple lines is shown below:

Executing SQL Statements from a Saved File

You may want to run a particular SQL statement or set of SQL statements often. In such situations, you can save the SQL statements in a text file with the extension .sql. This file will now be called a script.

You can execute a script using the syntax.

sqlcmd –i <Full_Path_of_Script_File_Name>

Executing SQL Statements from a Saved File

Consider the file MyQuery.sql file which contains the following SQL statements.

Use Northwind

Select EmployeeID, FirstName, LastName, Title from Employees

To execute the commands in the script file MyQuery.sql, at the Command Prompt, type:

sqlcmd –i c:\MyQuery.sql.



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The results are displayed on the screen as shown in the image below.

Saving Output to a File

By default, the result of executing an SQL statement is displayed on screen. You can send the output to a file, instead of displaying it on screen, using the syntax:

sqlcmd –o <Full_Path_of_Output_File_Name>

Consider the command:

sqlcmd –o c:\MyQueryResult.txt

All results from SQL statements executed will now be saved in the file c:\MyQueryResult.txt.

Click on Sending Output to a File to view the results.

Using SQL Server Management Studio for Scripting

SQL Server Management Studio is a tool that can be used to access, manage, and develop all components of Microsoft SQL Server. SQL Server Management Studio incorporates a rich set of script and graphical tools, making it easy-to-use across a wide spectrum of users.

With SQL Server Management Studio, you can:

Auto-generate SQL statements

Write SQL statements using the Graphical Query Designer

Use templates to create SQL statements



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Listing the Scripting Features of SQL Server Management Studio

SQL Server Management Studio provides a variety of ways to generate SQL Statements.

Listed below are some features that simplify writing SQL statements in the SQL Server Management Studio:

A rich set of templates that serves as a base for creating a variety of SQL statements. You can also save your queries as templates for future use.

Microsoft IntelliSense displays the syntax as you type the SQL statements.

Dynamic help displays relevant help topics immediately.

Create offline queries or scripts without having to connect to a server.

Create SQLCMD queries and scripts.

Auto-generating SQL Statements

Writing lengthy SQL statements can be tedious and time consuming. With SQL Server Management Studio, you can generate SQL statements using an intuitive, menu-based method.




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Building SQL Queries Using the Query Designer

The Graphical Query Designer is a visual tool that lets you design SQL statements graphically. It is useful for those who are learning how to write SQL as they do not need to remember the syntax for creating complex SQL statements.


Using Templates to Write and Execute SQL Statements

Templates in SQL Server Management Studio are files containing pre-written SQL statements that you can modify and use as required

Templates are organized into various categories and they can be viewed through the Template Explorer window in the SQL Server Management Studio.


What is the Debug Feature?

Checking long multi line SQL statements for errors can be time consuming. To make this task easy, SQL Server Management Studio provides the Debugger function.

The Debugger function helps you find errors in SQL statements by observing their runtime behavior. It helps ensure that the SQL statements are executed in the way that they were intended.



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Module 4: Using the SELECT Statement



Introduce the SELECT statement

Use the SELECT statement

Execute a query in Microsoft SQL Server

Retrieve specific columns in a table

Filter rows with the WHERE clause

Use operators to create conditions

Retrieve unknown values from the database

Sort result sets

Suppress duplicate rows

View top rows in a large result set

Use wildcards to retrieve data

Work with calculated columns

Understanding the SELECT Statement

The SELECT statement enables you to access and retrieve information from the database.

The rows retrieved by the SELECT statement are known as the result set.

Using the SELECT statement, you can retrieve all information from a table or narrow your

search to retrieve only specific information from a table. You can also sort and group data, and perform calculations.

The syntax of the SELECT statement is:

SELECT column_list

[INTO new_table]

FROM table

[WHERE search_condition]

[GROUP BY group_by_expression]



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[HAVING search_condition]

[ORDER BY order_expression [ASC | DESC]]

Note: SQL is not case sensitive.

As you progress through this module, you will learn to use the SELECT statement and its

clauses.

Using the SELECT Statement

In the simplest form, the SELECT statement retrieves all rows and columns from the specified

table.

The syntax of the SELECT statement to retrieve all the data from a table is:

SELECT * FROM <table_name>

Consider the query:

SELECT * FROM Employees

This statement retrieves all rows and columns from the Employees table.

Executing a Query Using the SQL Server Management Studio

You can execute queries using the SQL Server Management Studio.




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Retrieving Data from Specific Columns in a Table

The SELECT statement can also be used to retrieve data from specific columns of a table.

To retrieve data from specific columns of a table, the syntax is:

SELECT <column1,column2,…,columnN> FROM <table_name>

Consider the query:

SELECT TitleOfCourtesy, FirstName, LastName, Title

FROM Employees

This SELECT statement retrieves data from the columns TitleOfCourtesy, FirstName,

LastName, and Title for all rows of the table Employees.

Filtering Rows with the WHERE Clause

You may want to view those rows that meet specific conditions. In such situations, the WHERE clause is used with the SELECT statement.

The syntax of a SELECT query that uses the WHERE clause is:

SELECT <column1,column2,…,columnN>

FROM <table_name>

WHERE <column> <operator> <value1>

Consider the query:

SELECT TitleOfCourtesy, FirstName, LastName, Title



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FROM Employees

WHERE Title='Sales Representative'

This statement retrieves data only from those rows where the Title column has the value

Sales Representative.

Using Operators to Create Conditions

An operator is a character or a reserved word that is used to specify a condition, or combine two or more conditions. The operators are used with the WHERE clause in the SELECT statement to set the filter criteria for data.

There are four types of operators:

1. Comparison Operators

2. List Operators

3. Range Operators

4. Logical Operators

The syntax for using an operator in a query is:


FROM <table_name>

WHERE <expression1> <operator> <expression2>

We shall look at each category of operators in detail in the topics to follow.



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What are Comparison Operators?

The comparison operators shown in the table below are used to compare two expressions.

Comparison Operator Description

= Equal to

> Greater than

< Less than

>= Greater than or equal to

<= Less than or equal to

<> Not equal to

Consider the query:

SELECT ProductName,UnitsInStock,UnitsOnOrder

FROM Products

WHERE UnitsOnOrder >=70

This query retrieves data only from those rows of the Products table where the value of

UnitsInStock is greater than or equal to 70.

What are Logical Operators?

Logical operators are used to test if a specified condition is true or not. They are also used to combine multiple conditions.

Some of the commonly used logical operators are:



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OR Retrieves rows that meet any one of the specified conditions.

AND Retrieves rows that meet both the conditions.

NOT Retrieves rows that do not meet the specified condition.

BETWEEN Retrieves rows where the tested value falls within the specified range.

Consider the following query:

SELECT CompanyName,City

FROM Customers

WHERE City = 'London' OR City = 'Madrid'

This query retrieves data only from those rows of the Products table where the City is

London or Madrid.

What are List Operators?

The IN list operator checks if the result of the expression meets one of the specified values.

The syntax for using a list operator in a query is:


FROM <table_name>



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WHERE <column> IN (‘value1’,‘value2’,…,‘valueN’)

Note: Use NOT IN to retrieve rows that do not meet the specified criteria.

Consider the query:

SELECT CompanyName,City

FROM Customers

WHERE City IN ('London','Madrid','Paris')

This query retrieves data only from those rows of the Products table where the City is

London, Madrid and Paris.

What is the NULL Keyword?

A NULL value in a column means that there is no data in the column. You can retrieve rows

which contain NULL values using the IS NULL keyword with the WHERE clause.

The syntax for retrieving records with NULL values is:


FROM <table_name>

WHERE < column1> IS NULL

Consider the query:

SELECT CompanyName,City,Region,Country



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FROM Customers

WHERE REGION IS NULL

This query retrieves data only from those rows of the Customers table where the Region is NULL.

Sorting the Result Set with the ORDER BY Clause

The ORDER BY clause sorts the retrieved results in the ascending or descending order of the

values in the specified columns. The ASC and DESC keywords specify the sort order. If the

sort order is not specified, the results are sorted in the ascending order.

The syntax for using the ORDER BY clause is:


FROM <table_name>

ORDER BY <column1 [ASC|DESC],column2 [ASC|DESC],…,columnN

[ASC|DESC]>

Sorting Columns with the ORDER BY Clause

Consider the query:

SELECT * FROM [Order Details] ORDER BY Quantity ASC

This query retrieves all the rows and columns from the [Order Details] table and sorts

the rows in the ascending order by the column Quantity.



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Using the DISTINCT keyword to Suppress Duplicate Rows

Queries may return result sets with duplicate rows. The DISTINCT keyword eliminates

redundant rows from a result set.

The syntax for limiting result sets with the DISTINCT keyword is:

SELECT DISTINCT <column1,column2,…,columnN>

FROM <table_name>

Consider the query:

SELECT DISTINCT OrderID,Quantity

FROM [Order Details]

This query retrieves distinct values of the OrderID and the Quantity columns from the

Order Details table.



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Viewing Top Rows in a Large Result Set

When accessing a large database, you can set a limit to the number of records you want to retrieve using the TOP keyword.

The syntax for retrieving the top N (Number) rows is:

SELECT TOP <N> <column1,column2,…,columnN>

FROM <table_name>

You can also specify the percentage of rows to be retrieved. The syntax for retrieving the top N percentage of rows is:

SELECT TOP <N> PERCENT <column1,column2,…,columnN>

FROM <table_name>

Consider the query:

SELECT TOP 30 ProductName FROM Products

This query retrieves the top 30 rows from the Products table.



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Using Wildcards to Retrieve Data

Using the LIKE keyword and patterns

Sometimes we know only a part of the data to be retrieved or are unsure of the exact spelling. For example, we may know that the name begins with Al or that the address contains the word Palm.

To retrieve data based on partially known information, use the LIKE keyword and wildcards.

Wildcards are special characters that can be used as substitutes for one or more unknown characters when searching for a match.

The syntax for retrieving data using wildcards is:


FROM <table_name>

WHERE <expression1> LIKE <Pattern>

Different wildcard characters are described below.

Wildcard Substitutes Example

% Zero or more characters

WHERE Name Like ‘Ja%’ returns

all rows where the column Name has data that starts with the characters Ja. For example, Jade, Jane, Janet, Jake, Jasper, etc.

_ Exactly one character WHERE Name Like ‘Ja_e’ returns

all rows where the column Name has



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Wildcard Substitutes Example

four-letter data that starts with the characters Ja and ends in e. For example, Jade, Jane, Jake, etc.

[] Any single character in the specified list

WHERE Name Like ‘Ja[dn]e’

returns all rows where the column Name has four-letter data that starts with the characters Ja and ends in e and the third character is d or n. That is, rows where the Name is Jade or Jane.

[^] Any single character not in the specified list

WHERE Name Like ‘Ja[^dn]e’

returns all rows where the column Name has four-letter data that starts with the characters Ja and ends in e and the third character is NOT d or n. That is, rows where the Name is Jade or Jane are excluded.

Note: You can use a combination of wildcards.

How to use the LIKE Keyword?

Consider the query:

SELECT CompanyName,Country

FROM Customers

WHERE CompanyName LIKE 'L%'

This query retrieves all the data from the Customers table where the CompanyName starts

with L.



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Working with Calculated Columns

Consider a database table in SQL Server containing two columns, Unit Price and Quantity.

Unit Price Quantity

100 15

150 32

125 18

50 45

If we want to calculate the total cost price of each commodity automatically, we need to multiply Unit Price by Quantity. When we use this formula in a SQL Query, a new column is generated; this is called a calculated column.

By default, the new column is returned with no column name. We can assign a name to this unnamed column. For example, Total Cost.

Unit Price Quantity Total Cost

100 15 1500

150 32 4800

125 18 2250

75 45 3375

Note: Calculated columns are also called computed columns.

Generating Calculated Columns

The syntax for generating calculated columns is below:

SELECT <column1,column2,…,columnN> <CalculatedColumn>

AS <NameforCalculatedColumn>

FROM <table_name>

Consider the query:

SELECT ProductID, Quantity, UnitPrice * Quantity AS TotalPrice




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This query retrieves the ProductID and Quantity from the Order Details table and

creates a new calculated column called TotalPrice.



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Module 5: Working with Multi-table Queries



Understand what are joins

Understand types of joins

Create joins with the WHERE clause

What are Joins?

Often, you may need to extract data from more than one table, based on certain conditions. For example, details of all customers who have an outstanding order.

To extract related data from two tables, you must be able to establish a logical relationship between the two.

For example, in the Customers table, each customer is assigned a CustomerID. In the

Orders table, the customer who placed an order is identified by the CustomerID. So the

CustomerID field can be used to establish a relationship.

In a SQL statement, a join establishes the logical relationship between the tables from which data is to be extracted.



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Joins can be categorized as:

Inner Joins

Outer Joins

Joins can be specified using the WHERE or the FROM clause.

Understanding Types of Joins

What is an Inner Join?

Inner Joins return only those rows that match the join condition.

For example, all employees who are assigned to a project and details of the project. The query will not show details of employees not assigned to a project or a project with no employees assigned to it.

The syntax for an inner join is:

SELECT <columns_from_table_1_and_table_2>

FROM <table_1>

INNER JOIN <table_2>

ON <table_1.column_name>=<table_2.column_name>

Note: If you want to use columns from multiple tables, use the syntax:

<table_name.column_name>

Consider the example:

Employees Projects

Inner Join

Employees who are assigned to a project



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SELECT Customers.CustomerID,Customers.ContactName,

Orders.OrderID, Orders.OrderDate

FROM Customers INNER JOIN Orders

ON Customers.CustomerID = Orders.CustomerID


What is an Outer Join?

Outer Joins return all rows from one table and only those rows from the other table that match the condition specified in the join condition.

For example, all employees whether or not they are assigned to a project and details of the project, where available.

Outer joins have three types:

Left Outer Join

Right Outer Join

Full Outer Join

What is a Left Outer Join?

Every join has a comparison expression that involves fields from the two tables to be joined.

In a left outer join, all rows from the left table are retrieved. For every row in the left table where there is a match available in the right table, details from the right table are also retrieved. When a row in the left table has no matches in the right table, null values are displayed in place of values from the table in the right.

Those rows in the right table which have no matching rows in the table on the left are not retrieved.



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The syntax for a left outer join is:


FROM <table_1> LEFT OUTER JOIN <table_2>


Consider the query:


Orders.OrderID,

Orders.OrderDate FROM Customers

LEFT OUTER JOIN Orders



What is a Right Outer Join?

In a right outer join, all rows from the right table are retrieved. For every row in the right table where there is a match available in the left table, details from the left table are also retrieved. When a row in the right table has no matches in the left table, null values are displayed in place of values from the table in the left.

Those rows in the left table which have no matching rows in the table on the right are not retrieved.

Employees Projects

Left Outer Join All employees and details of

projects where available.



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The syntax for a right outer join is:


FROM <table_1> RIGHT OUTER JOIN <table_2>


Consider the query:


Orders.OrderID,


RIGHT OUTER JOIN Orders



What is a Full Outer Join?

The full outer join retrieves all rows from the left and the right tables, whether there is a corresponding match or not. The joined table contains data from both the tables. However, if a column in one table does not have a match in the corresponding column of the other table, a NULL is displayed in place of the column value.

Employees Projects

Right Outer Join All projects and details of

employees where available.

Full Outer Join



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The syntax for a full outer join is:


FROM <table_1> FULL OUTER JOIN <table_2>


Consider the query:


Orders.OrderID,


FULL OUTER JOIN Orders



Creating Joins with the WHERE Clause

The WHERE clause can be used to specify an inner join, left outer join and right outer join in a

multi-table query.

The syntax for specifying an inner join with the WHERE clause is:


FROM <table_1> INNER JOIN <table_2>

Employees Projects

Full Outer Join

All Employee and Project details



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WHERE <Condition>

The syntax for specifying a left outer join with the WHERE clause is:


FROM <table_1> LEFT OUTER JOIN <table_2>


WHERE <Condition>

The syntax for specifying an right outer join with the WHERE clause is:


FROM <table_1> RIGHT OUTER JOIN <table_2>


WHERE <Condition>




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Module 6: Using SQL Functions in Queries



Use functions in SQL

Use aggregate functions

Use mathematical functions

Use date functions

Use string functions

Use conversion functions

Understanding SQL Functions

Using functions, you can manipulate retrieved data to create useful and relevant information. For example, you can find the total value of all products in stock, rather than just viewing price and quantity details of each product in stock.

Microsoft SQL Server provides a variety of functions for performing different calculations on data. These functions are classified into categories such as:

Aggregate functions

Mathematical functions

Date functions

String functions

Conversion functions

What are Function Arguments and Return Values?

A function argument is the input required by a function. The data that a function needs to process is passed to the function as one or more arguments. Arguments are enclosed in brackets after the function name.

The typical syntax for a function is:

Function_Name(Argument_1, Argument_2,…, Argument_N)

The result of the function calculation is called the return value.



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What are Aggregate Functions?

Aggregate functions process a set of values and return a single value as a result. The aggregate functions in SQL include:

SUM()

AVG()

MAX()

MIN()

COUNT()

All aggregate functions require only one argument, typically the name of the column whose values are to be processed.

If duplicate values are to be ignored, the aggregate function uses the keyword DISTINCT.

To process all values, use the keyword ALL.

Note: The keyword ALL is also the default and can be omitted.

The syntax for an aggregate function is:

Aggregate_Function([ALL|DISTINCT]<column_name>)

Working with the SUM Function

SUM() is one of the most commonly used aggregate functions. This function returns the sum

total of all non-null values in the specified column. The column must contain numerical values.

The syntax of a query using the SUM() function is:

SELECT SUM([ALL|DISTINCT]<column_name>) FROM <table_name>

Consider the query:

SELECT SUM(Quantity) AS 'Total number of units ordered' FROM

[Order Details]

This query returns the sum of the values present in the column Quantity and displays it

under the heading Total number of units ordered.



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Working with the AVG Function

AVG()calculates the average of all non-null data values in the specified column. The column

must contain numerical values.

The syntax of a query using the AVG() function is:

SELECT AVG([ALL |DISTINCT]<column_name>) FROM <table_name>

Consider the query:

SELECT AVG(UnitPrice) AS ‘Average Unit Price’ FROM [Order

Details]

This query returns the average of the values present in the UnitPrice column and displays

it as Average Unit Price.

Working with the MIN Function

MIN() retrieves the smallest non-null data value from the specified table column. The column

can contain numeric, string, or date/time values.

The syntax of a query using the MIN() function is :

SELECT MIN([ALL|DISTINCT]<column_name>) FROM <table_name>



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Consider the query:

SELECT MIN(UnitPrice) AS 'Minimum Unit Price' FROM [Order

Details]

This query returns the minimum value present in the UnitPrice column and displays it as

Minimum Unit Price.

Working with the MAX Function

MAX()retrieves the largest non-null data value in the specified table column. Like MIN(),

this function works for numeric, string, and date/time values.

The syntax of a query using the MAX() function is:

SELECT MAX([ALL|DISTINCT]<column_name>) FROM <table_name>

Consider the query:

SELECT MAX(Discount) AS 'Maximum Discount Given' FROM [Order

Details]

This query returns the maximum value present in the Discount column and displays it as

Maximum Discount Given.

Working with the COUNT Function

COUNT()counts the number of non-null values in the specified table column.



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The syntax of a query using the COUNT() function is:

SELECT COUNT([ALL|DISTINCT]<column_name>) FROM <table_name>

Consider the query:

SELECT COUNT(Quantity) AS 'Number of Products Ordered' FROM

[Order Details]

This query returns the count of all the non-null values present in the Quantity column and

displays it as Number of Products Ordered.

What are Mathematical Functions?

Microsoft SQL Server provides a variety of functions to perform a range of mathematical operations. Some of the mathematical functions are:

ROUND()

CEILING()

FLOOR()

SQUARE()

SQRT()

SIGN()

Working with the ROUND Function

ROUND()rounds off the numerical values to the specified precision.

The syntax of a query using the ROUND() function is:

ROUND(<expression>,<length>)



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If length is a positive number, ROUND() restricts the number of digits after the decimal

point to the number specified by length. If length is a negative number, ROUND()

rounds the digits before the decimal point as specified by length.

Expression Result

SELECT ROUND(487.2378,2) 487.2400

SELECT ROUND(487.2311,2) 487.2300

SELECT ROUND(487.2378,-1) 490.0000

SELECT ROUND(487.2378,-2) 500.0000

SELECT ROUND(487.2378,-3) 0.0000

Working with the CEILING and FLOOR Functions

CEILING() returns the smallest integer greater than or equal to the specified number, while FLOOR()returns the largest integer less than or equal to the specified number.

The syntax of the CEILING() function is:

CEILING(<numeric_expression>)

The syntax of the FLOOR() function is:

FLOOR(<numeric_expression>)

Consider the query:

SELECT CEILING(1875.85)

The result of this query is 1876.



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Consider the query:

SELECT FLOOR(2471.68)

The result of this query is 2471.

Working with the SQUARE and SQRT Functions

SQUARE() and SQRT()return the square and the square root of the specified numerical

value.

The syntax of the SQUARE() function is:

SQUARE(<numeric_expression>)

Consider the query:

SELECT SQUARE(100)

The result is 10000.

The syntax of the SQRT() function is:

SQRT(<numeric_expression>)

Consider the query:

SELECT SQRT(100)

The result is 10.

Working with the SIGN Function

SIGN()returns 1 if the argument value is positive, and -1 if the argument is negative.

The syntax of the SIGN() function is:

SIGN(<numeric_ expression>)

Consider the query:

SELECT SIGN(100)

The result is 1.

Consider the query:

SELECT SIGN(-100)



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The result is -1.

What are Date Functions?

The date functions are used to work with date values. You can retrieve the system date and time as well as extract parts of a date or time value.

The most common date functions are:

GETDATE()

DAY()

MONTH()

YEAR()

Working with the GETDATE Function

GETDATE()returns the system time of the computer on which the SQL Server is running.

The syntax of the GETDATE() function is:

GETDATE()

This query returns the current date and time.

Working with the DAY, MONTH, and YEAR Functions

The DAY(), MONTH() and YEAR() functions return the day, month, and the year

respectively for the specified date.

The syntax of the DAY() function is:

DAY(<date_value>)

The syntax of the MONTH() function is:

MONTH(<date_value>)

The syntax of the YEAR() function is:

YEAR(<date_value>)

Consider the query:



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SELECT GETDATE()AS 'Current Date & Time',

DAY(GETDATE())AS Day,

MONTH(GETDATE())AS Month,

YEAR(GETDATE())AS Year

The result of this query is shown in the screen below.

What are String Functions?

A string consists of a series of characters; alphabets, numbers, spaces, and special characters such as &, #, % etc.

String functions perform actions such as extracting parts of a string, substituting a sequence of characters with another and other such operations.

Typically, strings are enclosed in quotes. For example, „USA‟ or „3456.45‟.

Note: A number enclosed in quotes is treated as a string and not a numerical value.

Some important string functions are:

LEN()

SUBSTRING()

REPLACE()

LTRIM() and RTRIM()

Working with the LEN Function

LEN() returns the number of characters in the specified string expression.

The syntax of the LEN() function is:

LEN(<string_expression>)



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Consider the query:

SELECT ProductName,LEN(ProductName) AS Length FROM Products

The screen below shows the result of the query.

Working with the SUBSTRING Function

SUBSTRING() retrieves a part of the string, starting from the specified character. This

function needs three arguments:

The character string The start point of character string The length of the substring to be returned

The syntax of the SUBSTRING() function is:

SUBSTRING(<value_expression>,<start_expression>,<length_expressio

n>)

Consider the query:

SELECT SUBSTRING('Learn basics of SQL databases',6,14) AS

Substring

The result set of this query is “basics of SQL”.



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Working with the REPLACE Function

REPLACE()replaces a specified set of characters with another string. This function requires

three arguments:

The character string

The characters to be replaced

The new character string

The syntax of the REPLACE() function is:

REPLACE(<string_expression>,<string_pattern>,<string_replacement>

)

Consider the query:

SELECT REPLACE('Queries','ries','stions')AS 'New String'

The result of this query is “Questions”.



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Working with the LTRIM and RTRIM Functions

The LTRIM() and RTRIM()functions return strings after removing blanks from the left and

right of the string respectively.

The syntax of the LTRIM() function is:

LTRIM(<character_expression>)

Consider the query:

SELECT LTRIM(‘ MICROSOFT SQL SERVER’)

The result is ‘MICROSOFT SQL SERVER’.

The syntax of the RTRIM() function is:

RTRIM(<character_expression>)

Consider the query:

SELECT RTRIM(‘SQL MANAGEMENT STUDIO ‘)

The result is ‘SQL MANAGEMENT STUDIO’.

What are Conversion Functions?

Conversion functions are used to convert the data from one data type to another. While some conversions are automatic, many conversions such as numeric to string need special functions.

Some of the conversion functions are:

CAST()

CONVERT()

STR()

Working with the CAST Function

CAST()converts the data from one data type to another specified data type.

The syntax of the CAST() function is:

CAST (<expression> AS <new_data_type> [(length)])

Consider the query:



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SELECT CAST(OrderDate AS VARCHAR(12)) FROM Orders

The query converts the value retrieved from the OrderDate column of the Orders table to

the data type varchar.

Working with the CONVERT Function

CONVERT() is similar to CAST(), except that CONVERT() allows you to specify the format

for date and time conversions.

The syntax for the CONVERT() function is:

CONVERT ( data_type [ ( length ) ] , expression [ , style ] )

The style argument is optional which can be used to specify the format for date-time

values.

Consider the query:

SELECT OrderDate,

CONVERT(VARCHAR(12), OrderDate, 101) AS 'Date Format 1',

CONVERT(VARCHAR(12), OrderDate, 106) AS 'Date Format 2' FROM

Orders

This query displays the value in the OrderDate column of the Orders table as a string in

the format specified by the built-in styles 101 and 106.



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Working with the STR Function

STR() converts numerical data into a string. This function accepts three arguments:

The numerical expression

The overall length of the string

Number of places to the right of the decimal point

The syntax of the STR() function is:

STR ( float_expression [ , length [ , decimal ] ] )

The length argument is optional and can be used to specify the overall length of the

numerical expression to be returned.

Note: If length is less than the number of digits before the decimal point, STR() returns

** as the result.

The decimal argument is also optional and returns the number of places to the right of the

decimal point.

Expression Result

SELECT STR(567.890,7,1) 567.9

SELECT STR(567.890,7,2) 567.89

SELECT STR(567.890,3,1) 568

SELECT STR(567.890,2,1) **



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Module 7: Grouping Data



Define grouping of data

Use the GROUP BY clause

Use the HAVING clause

Add totals and subtotals to grouped data

Defining Grouping of Data

Grouping is the process of summarizing a set of rows into a single row, based on specified criteria. Aggregate functions are used to combine values in one or more columns of the original set of rows into a single value in the summary row.

For example, we can add up orders by customer to find the total value of orders placed by each customer.

Working with the GROUP BY Clause

The GROUP BY clause is used to achieve grouping. This clause is written after the WHERE and

ORDER BY clauses in a SQL statement.

The syntax for the GROUP BY clause is:

SELECT <column1,column2,…,columnN>, <aggregate_function>(column)

FROM <table>

WHERE <condition>

GROUP BY <column1,column2,…,columnN>

Consider the following query that will display the total value of each order.

SELECT OrderID,SUM(Quantity * UnitPrice) AS 'Total Order Value'


GROUP BY OrderID



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Working with the HAVING Clause

Consider a query that uses the GROUP BY clause to calculate and display the total value of

orders placed by each customer. We may want to view only those customers whose order

values exceed a certain amount. In such a case, we will use the HAVING clause.

The HAVING clause is used to filter rows returned by the GROUP BY clause.

When you use the WHERE clause along with the GROUP BY and HAVING clauses, first the

condition in the WHERE clause is used to create a result set of rows that meet the WHERE

condition. Next, the GROUP BY clause is used to create the summary rows. Finally, the

HAVING clause is applied to the summary rows to create the final result set.

If a GROUP BY is not used then the HAVING clause behaves exactly the same way as the

WHERE clause.

The syntax for the HAVING clause is:

SELECT <column1, column2, …, columnN>, <aggregate_function>

(column)

FROM <table_name>

[WHERE <condition>]

GROUP BY <column1, column2, …, columnN>

HAVING <condition>

Consider the query that retrieves orders having total value of each order more than 500.

SELECT OrderID, ProductID, SUM(Quantity * UnitPrice) AS 'Total

Order Value'



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WHERE ProductID BETWEEN 20 AND 35

GROUP BY OrderID, ProductID

HAVING SUM(Quantity * UnitPrice) > 500

Adding Totals and Subtotals to Grouped Data

Describing the ROLLUP and CUBE Operators

Grouping is the process of summarizing a set of rows into a single row, based on specified criteria. You can add totals and subtotals to the summary rows using the following operators:

ROLLUP

CUBE

Using the ROLLUP Operator

The ROLLUP operator calculates the subtotals on the first column specified in the GROUP BY

clause. It calculates the sum of each unique value found in the column and displays the subtotals in new rows.

The syntax of the ROLLUP operator is:



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SELECT <column1, column2, …, columnN>, <aggregate_function>

(column)

FROM <table_name>

GROUP BY ROLLUP (column1, column2, ,…, columnN)

Consider the following example to understand how the ROLLUP operator works:

Original Data SELECT CustID, ProductID,

SUM(Quantity)

FROM MyOrders

GROUP BY CustID, ProductID

SELECT CustID, ProductID,

SUM(Quantity)

FROM MyOrders

GROUP BY ROLLUP (CustID,

ProductID)

CustID

ProductID

Quantity

CustID

ProductID

Quantity

CustID

ProductID

Quantity

C_1 P_1 5 C_1 P_1 13 C_1 P_1 13

C_1 P_1 6 C_1 P_2 8 C_1 P_1 8

C_1 P_2 8 C_2 P_1 5 C_2 P_1 5

C_1 P_1 2 C_2 P_2 11 C_2 P_2 11

C_2 P_1 5 C_1 NULL 21

C_2 P_2 6 C_2 NULL 16

C_2 P_2 5

Consider the following query and its result:

SELECT ProductName,SupplierID,CategoryID,

SUM(UnitPrice * UnitsInStock) AS 'Cost Of Stock'

FROM Products

WHERE ProductName LIKE 'C%'

GROUP BY ROLLUP(ProductName,SupplierID,CategoryID)



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Using the CUBE Operator

The ROLLUP operator creates subtotals only for the first column in the GROUP BY clause. The

CUBE operator creates subtotals for all combinations of columns specified in the GROUP BY

clause. In addition, it creates a grand total that includes all rows.

The syntax of the CUBE operator is:

SELECT <column1, column2, … , columnN>, <aggregate_function>

(column)

FROM <table_name>

GROUP BY CUBE (column1, column2, … , column)

Consider the following example to understand how the CUBE operator works:

Original Data SELECT CustID, ProductID,

SUM(Quantity)

FROM MyOrders

GROUP BY CustID, ProductID

SELECT CustID, ProductID,

SUM(Quantity)

FROM MyOrders

GROUP BY CUBE (CustID,

ProductID)

CustID

ProductID

Quantity

CustID

ProductID

Quantity

CustID

ProductID

Quantity

C_1 P_1 5 C_1 P_1 13 C_1 P_1 13



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C_1 P_1 6 C_1 P_2 8 C_1 P_2 8

C_1 P_2 8 C_2 P_1 5 C_2 P_1 5

C_1 P_1 2 C_2 P_2 11 C_2 P_2 11

C_2 P_1 5 C_1 NULL 21

C_2 P_2 6 C_1 NULL 16

C_2 P_2 5 NULL P_1 18

NULL P_2 19

NULL NULL 37

Consider the following query and its result:

SELECT ProductName,SupplierID,CategoryID,

SUM(UnitPrice * UnitsInStock) AS 'Cost Of Stock'

FROM Products

WHERE ProductName LIKE 'C%'

GROUP BY CUBE(ProductName,SupplierID,CategoryID)



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Module 8: Working with Tables



Create a table

Modify a table

Delete a table

Create a database

Delete an existing database

Using the CREATE Statement

The CREATE statement can be used to create a new table in the current database. You need

to specify the name of the table along with names, data types and constraints of the columns in the table.

Some of the constraints that can be set on a column are:

Primary key

Foreign key

Null values

Remember, a Null value represents an unknown or a missing value. It is important to understand that a null value does not mean a zero of a text string or one or more blank spaces.

As a result, when we allow a column to hold null values, we are saying that data in that column is optional

The syntax of the CREATE statement that is used to create a table is:

CREATE TABLE <table_name>

(

<column_name1> <data_type> PRIMARY KEY,

<column_name2> <data_type> NOT NULL,

…,

<column_nameN> data_type



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)

Consider the example given below, where the CREATE statement will create a table named

Franchise.

CREATE TABLE Franchise

(FranchiseID int PRIMARY KEY,

FranchiseName varchar(255) NOT NULL,

Quantity varchar(255),

ContactName varchar(255)

)


Modifying a Table

The ALTER statement can be used to change the structure of an existing table by:

Adding columns to a table

Modifying the data type of a column

Deleting columns from a table

Adding Columns to a Table Using the ALTER Statement

The ALTER statement can be used to add columns to an existing table.

The syntax of the ALTER statement is below:

ALTER TABLE <table_name>

ADD <column_name> <data type>

Modifying Columns in a Table Using the ALTER Statement

The ALTER TABLE statement can also be used to modify the data type of a column.

The syntax of the ALTER statement as used to modify the data type of a column is:




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ALTER COLUMN <column_name> <new_data type>

Deleting Columns in a Table Using the ALTER Statement

The ALTER TABLE statement can also be used to delete a column using the DROP keyword.

The syntax of the ALTER statement as used to delete a column is:


DROP COLUMN <column_name>


Deleting a Table Using the DROP Statement

The DROP statement can be used to delete a table permanently and completely from the

database. This statement will drop a table if and only if the data in the table is not referenced by any other table or component of the database.

The syntax of the DROP statement as used to delete a table is:

DROP TABLE <table_name>

Using the CREATE DATABASE Statement

So far, we have used an existing database to work with tables. But, If you are starting a completely separate project or want to create a database simply to practice with, you can create a new database.

The CREATE DATABASE statement is used to create a new database.

The syntax to create a database is:

CREATE DATABASE <database_name>

Consider the query:

CREATE DATABASE mydatabase

This query creates a new database called mydatabase.

Note: You can add tables to the new database using the CREATE TABLE statement.




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Using the DROP DATABASE Statement

The DROP DATABASE statement is used to delete an existing database.

The syntax to delete a database is:

DROP DATABASE <database_name>

Consider the query:

DROP DATABASE mydatabase

This query deletes mydatabase.



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Module 9: Manipulating Data in Tables



Add rows to a table

Update rows in a table

Delete rows from a table

Delete all rows from a table

Using the INSERT INTO Statement

The INSERT statement is used to add new rows of data to a table. You can insert data in a

table in two ways:

Insert a new row containing values for all the columns of a table

Insert a new row containing values for only some columns of a table

If you are adding a new row with data for all columns in a table, you do not have to specify the column names. However, you must ensure that the order of the values is the same as that of the columns they are meant for.

The syntax to insert a new row with data for all columns is:

INSERT INTO <table_name>

VALUES (‘value1’, ‘value2’, ‘value3’,…, ‘valueN’)



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You can also add data to only specific columns of a table, by specifying the column names and the associated values.

The syntax to insert a new row with values for specific columns in a table is:

INSERT INTO <table_name> (column1, column2, column3,…,columnN)

VALUES (‘value1’, ‘value2’, ‘value3’,…, ‘valueN’)

If you do not specify a value for a column, SQL uses NULL or the default value for that

column, if any. If the column does not allow NULL and has no default value, then the INSERT

statement fails.


Using the UPDATE INTO Statement

The UPDATE statement is used to modify the existing rows in a table. You can modify just

one row, some rows or all rows in a table.

The syntax to update rows in a table is:

UPDATE <table_name>

SET <column_name1>= ‘<value1>’, <column_name2>=

‘<value2>’,…<column>= ‘<valueN>’

WHERE<condition>

The SET keyword specifies the new values while the WHERE clause identifies the records to

be updated. If you do not specify the WHERE condition, all the records in the table will be

updated.




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Using the DELETE Statement

The DELETE statement is used to delete rows from a table. You can choose which rows to

delete.

The syntax to delete specific rows from a table is:

DELETE FROM <table_name>

WHERE <condition>

The WHERE condition specifies the rows to be deleted in a table. If you do not specify the

WHERE condition, all the rows in the table are deleted.

It is important to note that only the rows of the table are deleted. The table itself remains intact. If you delete all rows, then you have an empty table.


Using the TRUNCATE Statement

The TRUNCATE TABLE statement deletes all the rows of a table. The TRUNCATE TABLE

statement does the same thing as a DELETE statement without the WHERE clause. However,

the TRUNCATE TABLE is faster as compared to the DELETE statement without the WHERE

clause.

Also, the DELETE statement only deletes the rows from a table but does not free the space

used by the table. Whereas, the TRUNCATE TABLE statement deletes all the rows from the

table and also frees the space containing the table.

The syntax to delete all the rows from a table is:

TRUNCATE TABLE <table_name>



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Module 10: Working with Programming Objects



Understand what is a view

Create a view

Access a view

Modify a view

Delete a view

Rename a view

Work with an indexed view

Understand what is a stored procedure

Create a stored procedure

Execute a stored procedure

Modify a stored procedure

Delete a stored procedure

Understanding what is a View

Rewriting complex queries can be time consuming and prone to errors. With views, you can create complex queries, save and reuse them in the future. A view is a virtual table that consists of columns from one or more tables. The tables from which the columns are taken in a view are known as the base or underlying tables. A view is simply stored as a SELECT

statement in the database.

Note: A view does not occupy the physical space in a database as tables do. When the SELECT statement is executed, the view returns a virtual table.

Listing the Advantages of a View

Some advantages of using views:

Restrict access to rows and columns – Users can retrieve or modify only the data that they have been given access to.



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Simplify query execution – Complex queries can be stored in the view and data from the view can be retrieved using simple SQL statements.

Retrieve data from multiple tables as one – Join columns of two tables to retrieve data as one.

Data security – Confidential information can be excluded from a view.

Using the CREATE VIEW Statement

A view is an alternate method to represent data from one or more tables in a database. The

CREATE VIEW statement creates a view in the database in the form of a virtual table.

The syntax for creating a simple view is:

CREATE VIEW <view_name>

AS

<SQL Statements>

For example, you can create a simple view using the syntax:


AS


FROM <table_name>

<WHERE condition>

Note: The SQL statements in the CREATE VIEW statement can be any SELECT, INSERT,

UPDATE, or DELETE statements.

Consider a query that creates a view to retrieve the date on which customers have placed orders and their corresponding date of shipping.

CREATE VIEW CustomerOrders

AS

SELECT OrderID,CustomerID,OrderDate,ShippedDate FROM Orders

WHERE OrderID BETWEEN '10251' AND '10263'




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Using the SELECT Statement to Access a view

The CREATE VIEW statement creates a virtual table based on the result set of the SELECT

statement. A view can be accessed using the SELECT statement.

The syntax for accessing a view is:

SELECT * FROM <view_name>

Note: You cannot rename the columns in a view as the view is only a virtual table in the database.

Modifying a View

The ALTER VIEW statement is used to modify an existing view in a database.

The syntax for the ALTER VIEW statement is:

ALTER VIEW <view_name>

AS

<SQL Statements>

For example, you can modify a view using the syntax:

ALTER VIEW <view_name>

AS


FROM <table_name>

<WHERE condition>

Consider a query that modifies the view CustomerOrders to exclude the order date for

each customer and include the date of shipping, ship name and country.

ALTER VIEW CustomerOrders

AS

SELECT OrderID, ShippedDate, ShipName, ShipCountry FROM Orders

WHERE OrderID > 10254




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Deleting a View

The DROP VIEW statement is used to delete a view from a database.

The syntax of the DROP VIEW statement is:

DROP VIEW <view name>

Renaming a View

An existing view in a database can be renamed without deleting or creating the view again.

The syntax for renaming a view is:

sp_rename <view_name>, <new_view_name>

Consider the query that renames the view CustomerOrders:

sp_rename CustomerOrders, OrdersShippingDetails

After renaming a view, you can access the view using the SELECT statement with the new

view name.

What is an Index?

Due to vast information in tables, it takes a long time to retrieve all information. Hence, indexes are created on columns of existing tables to retrieve data quickly.

You can consider an index in SQL similar to an index that appears at the end of a book which helps to locate information quickly. The same principle applies to indexes in SQL. You can create an index on views that contain a single column or a group of columns from a table. The two types of indexes you can create are clustered and non-clustered indexes.

What is an Indexed View?

A view is stored as a query in the database. In addition, a view can contain joined tables which can significantly reduce the performance as compared to a single table. To improve the performance of a view, you can create an indexed view.

After you create a view, you can create an index on that view. However, you must first create a clustered index on a view. A clustered index sorts the rows in the view. Each table or view can only have one clustered index. Hence, a clustered index is built on columns which contain a high percentage of unique data.

Listing the Rules for Creating an Indexed View

While creating an indexed view, you must keep the following points in mind:



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Create indexed views using the SCHEMABINDING option. The SCHEMABINDING

option locks the tables and prevents any changes that may affect the table structure.

List the column names of a table in the SELECT statement of a view. You

cannot use the asterisk character to retrieve all columns from a table.

Use only inner joins while retrieving data from two tables in a view. Outer joins cannot be included in an indexed view.

Select columns in a view only from the base tables. The tables mentioned in a view must be in the same database as the view.

Creating an Indexed View

The CREATE VIEW statement with the WITH SCHEMABINDING clause is used to create an

indexed view. The steps to create an indexed view are:

1. Create a simple view along with the SCHEMABINDING option.

2. Create a unique clustered index on the view. This index will store data in the view and update it whenever the data in the base table is changed.

The syntax to create a view with the SCHEMABINDING option is:


WITH SCHEMABINDING

AS

<SQL Statements>

The syntax to create a unique clustered index on the view is:

CREATE UNIQUE CLUSTERED INDEX <index_name>

ON <view_name>

(

<Name of the column on which the index is created>

)


What is a Stored Procedure

A stored procedure is a predefined block of SQL statements used to perform a specific task. It is saved in a database and executed as a single unit. Stored procedures are beneficial when groups of SQL statements are reused multiple times.

SQL statements are grouped under one name and saved in the database in the form of a stored procedure.



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Listing the Benefits of a Stored Procedure

The benefits of using a stored procedure are:

Enhance security – Restricts data access to specific users by granting or denying permissions. In this way, only authorized users can execute the stored procedures.

Code reusability – Groups blocks of SQL statements once and use the block again whenever needed. Stored procedures eliminate the task of rewriting the statements again and again.

Reduced network traffic - Reduces the amount of data transmitted over the network. In other words, stored procedures perform tasks within the database without sending unnecessary data on to the network

What are Parameters in a Stored Procedure?

A parameter is a special kind of variable that prompts a user to enter specific information in the form of an input. A stored procedure can have zero, one or more parameters.

A parameter in a stored procedure consists of:

The name of the parameter

Data type of the parameter

Length of the data type

The name of the parameter is always prefixed with the @ sign. If a stored procedure has two or more parameters, each parameter is separated by a comma.

Listing the Types of Parameters in a Stored Procedure

The types of parameters in a stored procedure are:

Input parameter - Accepts data from the user as an input. This parameter is used to execute SQL statements in the stored procedure that produces some result.

Output parameter – Executes and passes the data from the stored procedure back to the user.

Using the CREATE PROCEDURE Statement

The CREATE PROCEDURE statement is used to create a stored procedure.

The syntax for creating a stored procedure with parameters is:

CREATE PROCEDURE <procedure_name>

@parameter1 datatype1, @parameter2 datatype2,…



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AS

<SQL Statements>

The syntax for creating a stored procedure without parameters is :

CREATE PROCEDURE <procedure_name>

AS

<SQL Statements>

Note: You can also write PROCEDURE as PROC while writing the CREATE PROCEDURE

statement.

Consider the query below; it creates a stored procedure in which parameters are not specified.

CREATE PROCEDURE MyCustomerDetails

AS

SELECT CompanyName, ContactName, ContactTitle FROM Customers

WHERE CompanyName LIKE 'C%'

This statement will create a stored procedure named MyCustomerDetails.


Consider the query below; it creates a stored procedure in which parameters are specified.

CREATE PROCEDURE ProductTotalOrders

@ProductID int

AS

SELECT Products.ProductID,Products.ProductName,

SUM(Quantity) AS ‘Total Quantity Ordered’

FROM [Order Details],Products

WHERE Products.ProductID = @ProductID

AND Products.ProductID = [Order Details].ProductID

GROUP BY Products.ProductID,Products.ProductName

This statement creates a stored procedure named ProductTotalOrders with parameters.



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Using the EXECUTE Statement

The EXECUTE PROCEDURE statement is used to execute a stored procedure. A stored

procedure can be executed only in a database in which it is created. When the stored procedure is executed, it produces a result set. The stored procedure also displays output parameters, if specified.

The syntax for creating a stored procedure with parameters is:

EXECUTE <procedure_name>

[variable1, variable2,…,]

Note: Variables denote the input parameters of the stored procedure.

The syntax for executing a stored procedure without any parameters is :

EXECUTE <procedure_name>

Consider the following query and its results:

EXECUTE MyCustomerDetails

This statement executes a stored procedure named MyCustomerDetails which does not

specify any parameters.

This stored procedure displays the details of customers whose company name starts with the letter C.



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Consider the following query and its results:

EXECUTE ProductTotalOrders 19

This query executes a stored procedure named ProductTotalOrders which contains a

parameter @ProductID and an input 19 which is passed to the stored procedure. This

stored procedure retrieves the ProductID and ProductName from the Products table

and the corresponding total quantity ordered from the Order Details table for the

specified ProductID.

Using the ALTER PROCEDURE Statement

The ALTER PROCEDURE statement is used to modify an existing stored procedure.

The syntax for modifying an existing stored procedure with parameters is:

ALTER PROCEDURE <procedure_name>

@parameter1 datatype1, @parameter2 datatype2,…

AS

<SQL Statements>

The syntax to modify an existing stored procedure without parameters is:

ALTER PROCEDURE <procedure_name>

AS

<SQL Statements>



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Using the DROP PROCEDURE statement

The DROP PROCEDURE statement is used to delete a procedure permanently from a

database.

The syntax for deleting a stored procedure is:

DROP PROCEDURE <procedure_name>

Consider the example:

DROP PROCEDURE MyCustomerDetails

This query deletes the MyCustomerDetails procedure

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