SQL ALTER TABLE: A Comprehensive Guide
SQL ALTER TABLE
The ALTER TABLE
statement in SQL is a powerful command that allows you to modify an existing table without the need to recreate it. With this statement, you can add, modify, or delete columns and even update the constraints applied to a table. Additionally, it enables you to rename columns or the table itself. Let’s dive deeper into the various functionalities of the ALTER TABLE
statement.
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Adding Columns Using ALTER TABLE
In real-world scenarios, you may need to add new columns to an existing table to store additional data. The ALTER TABLE
statement with the ADD
keyword makes this process seamless.
Syntax for Adding a Single Column
ALTER TABLE table_name ADD column_name column_definition;
This syntax is used to add a single column to an existing table.
Syntax for Adding Multiple Columns
ALTER TABLE table_name
ADD (
column_name1 column_definition,
column_name2 column_definition,
...
column_nameN column_definition
);
This syntax allows you to add multiple columns in a single query.
Examples
Example 1: Adding a Single Column
Consider a table named Cars
:
Car Name | Car Color | Car Cost |
---|---|---|
Hyundai Creta | White | 10,85,000 |
Hyundai Venue | White | 9,50,000 |
Hyundai i20 | Red | 9,00,000 |
Kia Sonet | White | 10,00,000 |
Kia Seltos | Black | 8,00,000 |
Swift Dezire | Red | 7,95,000 |
To add a new column Car_Model
, use the following query:
ALTER TABLE Cars ADD Car_Model VARCHAR(20);
This adds the Car_Model
column to the Cars
table.
Example 2: Adding Multiple Columns
Consider a table named Employee
:
Emp_Id | Emp_Name | Emp_Salary | Emp_City |
---|---|---|---|
201 | Abhay | 25000 | Goa |
202 | Ankit | 45000 | Delhi |
203 | Bheem | 30000 | Goa |
204 | Ram | 29000 | Goa |
205 | Sumit | 40000 | Delhi |
To add two columns, Emp_ContactNo
and Emp_EmailID
, use this query:
ALTER TABLE Employee ADD (
Emp_ContactNo NUMBER(13),
Emp_EmailID VARCHAR(50)
);
Modifying Columns Using ALTER TABLE
The MODIFY
keyword is used to alter the definition of an existing column, such as changing its data type.
Syntax for Modifying a Single Column
ALTER TABLE table_name MODIFY column_name column_definition;
Syntax for Modifying Multiple Columns
ALTER TABLE table_name
MODIFY (
column_name1 column_definition,
column_name2 column_definition,
...
column_nameN column_definition
);
Examples
Example 1: Modifying a Single Column
To change the data type of the Car_Color
column in the Cars
table:
ALTER TABLE Cars MODIFY Car_Color VARCHAR(50);
Example 2: Modifying Multiple Columns
To update the data types of Emp_ContactNo
and Emp_EmailID
in the Employee
table:
ALTER TABLE Employee MODIFY (
Emp_ContactNo INT,
Emp_EmailID VARCHAR(80)
);
Deleting Columns Using ALTER TABLE
When a column is no longer needed, it can be removed using the DROP
keyword.
Syntax for Deleting a Column
ALTER TABLE table_name DROP COLUMN column_name;
Examples
Example 1: Deleting a Single Column
To delete the Car_Color
column from the Cars
table:
ALTER TABLE Cars DROP COLUMN Car_Color;
This removes the Car_Color
column from the table.
Example 2: Deleting Multiple Columns
To delete the Emp_Salary
and Emp_City
columns from the Employee
table, use two queries:
ALTER TABLE Employee DROP COLUMN Emp_Salary;
ALTER TABLE Employee DROP COLUMN Emp_City;
Renaming Columns Using ALTER TABLE
The RENAME COLUMN
clause is used to rename a column in an existing table.
Syntax for Renaming a Column
ALTER TABLE table_name RENAME COLUMN old_column_name TO new_column_name;
Examples
Example 1: Renaming a Column in the Cars Table
To rename the Car_Color
column to Colors
:
ALTER TABLE Cars RENAME COLUMN Car_Color TO Colors;
Example 2: Renaming a Column in the Employee Table
To rename the Emp_City
column to Emp_Address
:
ALTER TABLE Employee RENAME COLUMN Emp_City TO Emp_Address;
Summary
The ALTER TABLE
statement is a versatile tool for managing and modifying the structure of existing tables in SQL. Whether you need to add new columns, update their definitions, remove unnecessary ones, or rename them for clarity, the ALTER TABLE
statement simplifies these tasks. Mastering this command is essential for efficient database management.
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