SQL Course - QA

What is SQL?

 SQL stands for Structured Query Language
 SQL lets you access and manipulate databases
 SQL is an ANSI Standard

ANSI: American National Standards Institute

Why we use SQL?
 SQL can execute queries against a database
 SQL can retrieve data from a database
 SQL can insert records in a database
 SQL can update records in a database
 SQL can delete records from a database
 SQL can create new databases
 SQL can create new tables in a database
 SQL can create stored procedures in a database
 SQL can create views in a database
 SQL can set permissions on tables, procedures, and views

What is RDBMS?
RDBMS: Relational Database Management System
*Software that stores and manipulates data arranged in relational database tables.

Common RDBMS that use SQL are:

 Oracle
 Sybase
 Microsoft SQL Server
 Access

DDL
Data Definition Language (DDL) statements are
used to define the database structure or schema.

 CREATE - To create objects in the database
 ALTER - Alters the structure of the database
 DROP - Delete objects from the database
 TRUNCATE - Remove all records from a table,
including all spaces allocated for the records
are removed

DML
Data Manipulation Language (DML) statements
are used for managing data within schema
objects.

 SELECT - retrieve data from the a database
 INSERT - insert data into a table
 UPDATE - updates existing data within a table
 DELETE - deletes all records from a table, the
space for the records remain

SQL Arithmetic Operators
Operator Description Example
+ Addition - Adds values on either side a+b
of the operator
- Subtraction - Subtracts right hand a–b
operand from left hand operand

* Multiplication - Multiplies values on a*b
either side of the operator

/ Division - Divides left hand operand by b / a
right hand operand

% Modulus - Divides left hand operand b%a
by right hand operand and returns
remainder

SQL Comparison Operators
Operator Description Example

= Checks if the value of two operands are equal or not, if yes then (a = b) is not true.
condition becomes true.

!= Checks if the value of two operands are equal or not, if values are not (a != b) is true.
equal then condition becomes true.

<> Checks if the value of two operands are equal or not, if values are not (a <> b) is true.
equal then condition becomes true.

> Checks if the value of left operand is greater than the value of right (a > b) is not true.
operand, if yes then condition becomes true.

< Checks if the value of left operand is less than the value of right (a < b) is true.

>= Checks if the value of left operand is greater than or equal to the value (a >= b) is not true.
of right operand, if yes then condition becomes true.

<= Checks if the value of left operand is less than or equal to the value of (a <= b) is true.
right operand, if yes then condition becomes true.

!< Checks if the value of left operand is not less than the value of right (a !< b) is false.

!> Checks if the value of left operand is not greater than the value of right (a !> b) is true.

SQL Logical Operators
Operator Description
AND The AND operator allows the existence of multiple conditions in an SQL
statement's WHERE clause.
BETWEEN The BETWEEN operator is used to search for values that are within a set
of values, given the minimum value and the maximum value.
IN The IN operator is used to compare a value to a list of literal values that
have been specified.
LIKE The LIKE operator is used to compare a value to similar values using
wildcard operators.
NOT The NOT operator reverses the meaning of the logical operator with
which it is used. Eg. NOT EXISTS, NOT BETWEEN, NOT IN etc. This is
negate operator.
OR The OR operator is used to combine multiple conditions in an SQL
statement's WHERE clause.
IS NULL The NULL operator is used to retrieve NULL values

What is a Table?
Table – A set of data arranged in columns and rows. The columns represent
characteristics of stored data and the rows represent actual data entries.

In the below table called “employee_table” we see that the columns are:
First_Name, Last_Name, Email, DOB and Phone and rows are the data.

employee_table

First_Name Last_Name Email DOB Phone
John Smith John.Smith@yahoo.com 2/4/1968 222 222-2222
Steven Goldfish goldfish@gmail.com 4/4/1974 999 455-4545
Paula Brown pb@hotmail.com 5/24/1978 777 323-3232
James Smith jim@ymail.com 20/10/1980 666 323-8888

Select Statement

 Select * from employee_table
- All the columns in the employee_table are retrieved.

 Select First_Name, Last_Name from employee_table
- Only First_Name and Last_Name columns in the employee_table are retrieved.

Distinct Statement

 Select Distinct Last_Name from employee_table
LastName
Smith
Goldfish
Brown

Where Statement

 Select * from employee_table
where Last_Name= “Smith”
John.Smith@yahoo.co
John Smith 2/4/1968 222 222-2222
m

Where Statement Examples:
<>, >, >=, <, =<, Like, Wildcard and Between
SELECT * SELECT *
FROM employee_table FROM employee_table
WHERE Last_Name <> 'Smith' WHERE DOB =< ‘20/10/1980'
SELECT * SELECT *
WHERE DOB > ‘20/10/1980' WHERE Phone LIKE ’777%’

SELECT * SELECT *
WHERE DOB >= ‘20/10/1980' WHERE DOB BETWEEN ‘20/10/1980' AND
‘20/10/1990'
SELECT *
FROM employee_table
WHERE DOB < ‘20/10/1980'

Update Statement

 UPDATE employee_table
SET DOB = '5/10/1974'
WHERE Last_Name = 'Goldfish' AND First_Name = 'Steven’

 UPDATE employee_table
SET Phone = '626 555-5555'
WHERE Last_Name = 'Smith'

Delete Statement

 DELETE FROM employee_table

 DELETE FROM employee_table
WHERE Last_Name = 'Smith'

IN Statement

 SELECT * FROM Employee_Hours
WHERE Date IN ('5/6/2004', '5/7/2004')

WHERE Hours IN (‘9’, ’10’)

Not IN Statement

WHERE Date NOT IN ('5/6/2004', '5/7/2004')

WHERE Hours NOT IN (‘9’, ’10’)

AND/ OR Operator

 SELECT * FROM Employee_table
WHERE First_Name = ‘’John ’’ and Last_Name = ‘’ Smith’’

 SELECT * FROM Employee_table
WHERE First_Name= ‘’Paula’’ or First_Name= ‘’James’’

TOP Statement

 SELECT TOP 10 * FROM Employee_table

 SELECT TOP 200 * FROM Employee_table

Insert Into Statement
 INSERT INTO employee_table (FirstName, LastName, Email, DOB, Phone)
VALUES ('Peter', 'Hunt', 'peter.hunt@gmail.com', '1/1/1974', '626 888-8888’)

Peter Hunt Peter.hunt@gmail.com 1/1/1974 626 888-8888

 INSERT INTO employee_table
VALUES ('Peter', 'Hunt', 'peter.hunt@gmail.com', '1/1/1974', '626 888-8888')
 INSERT INTO employee_table (FirstName, LastName)
VALUES ('Peter', 'Hunt')

Select Into Statement
 SELECT FirstName, LastName
INTO employee_table_name_backup
FROM employee_table

 SELECT *
INTO employee_table_copy
FROM employee_table

Count Statement

 SELECT COUNT(*)
FROM employee_table

 SELECT COUNT (First_Name)
FROM employee_table

As Statement

 SELECT Last_Name AS “EMP_LNAME”, Phone AS “Emergency_Contact”
FROM employee_table

 SELECT COUNT (First_Name) AS “Number_of_employees”
FROM employee_table

Order By Statement
Peter Hunt peter.hunt@gmail.com 1/1/1974 626 888-8888

 SELECT * FROM employee_table
ORDER BY DOB
ORDER BY DOB DESC
ORDER BY DOB ASC
ORDER BY DOB, Last_Name

MAX Function

 SELECT MAX(SaleAmount) As MAX_Sales
FROM Sales

MIN Function

 SELECT Min(SaleAmount) As MIN_Sales
FROM Sales

AVG Function

 SELECT AVG(SaleAmount) As AVG_Sales
FROM Sales

SUM Function

 SELECT SUM(SaleAmount) As Total_Sales
FROM Sales

Group By Statement

 Select Employee, SUM(Hours) As Total_Hours
from Time_Table
Group By Employee

Having Statement

 Select Employee, SUM(Hours) As Total_Hours
from Time_Table
Group By Employee
Having SUM(Hours) >24

SQL Alias
CustomerID First_Name Email DOB Phone
1 Smith John.Smith@yahoo.com 2/4/1968 222 222-2222
2 Goldfish goldfish@gmail.com 4/4/1974 999 455-4545
3 Brown pb@hotmail.com 5/24/1978 777 323-3232
4 Kapil jim@ymail.com 20/10/1980 666 323-8888
5 Hunt Peter.hunt@gmail.com 1/1/1974 626 888-8888

SQL Alias (Contd.)

 Select a.First_Name, b.SaleAmount
From Customer a, Sales b
Where a.CustomerID=b.CustomerID

 Select a.Email, a.DOB, a.Phone, b.Date, b.SaleAmount

 Select a.First_Name, SUM(b.SaleAmount) AS TOTALSALES
Group By a.First_Name

SQL Constraints

 NOT NULL
 UNIQUE
 PRIMARY KEY
 FOREIGN KEY
 CHECK
 DEFAULT

PK & UK Differences
Primary Key:
1. It will not accept null values. 2. There will be only one primary key in a
table. 3. Clustered index is created in Primary key. 4. Primary key allows each
row in a table to be uniquely identified and ensures that no duplicate rows
exist.

Unique Key: 1. Null values are accepted. 2. More than one unique key will
be there in a table. 3. Non-Clustered index is created in unique key. 4. Unique
key constraint is used to prevent the duplication of key values within the rows of
a table and allow null values.

FULL OUTER JOIN
Table A Table B

FULL OUTER JOIN - Case
Table A Table B

LEFT OUTER JOIN
Table A Table B

LEFT OUTER JOIN - Case
Table A Table B

CROSS JOIN/ Cartesian Product
Table A Table B

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