Differentiating UNION, MINUS, and INTERSECT: A Deep Dive

In the realm of SQL, UNION, MINUS, and INTERSECT are powerful set operators that allow you to combine or compare result sets from multiple queries. Understanding the nuances of these operators is crucial for efficient data manipulation and analysis.

UNION

Purpose: Combines the result sets of two or more SELECT statements, eliminating duplicate rows.

Syntax:

SELECT column1, column2, ...
FROM table1
UNION
SELECT column1, column2, ...
FROM table2;

Example:

Consider two tables: Customers_A and Customers_B.

SELECT CustomerID FROM Customers_A
UNION
SELECT CustomerID FROM Customers_B;

This query will return a list of unique customer IDs from both tables, eliminating any duplicates.

MINUS

Purpose: Returns rows from the first SELECT statement that are not present in the second SELECT statement.

Syntax:

SELECT column1, column2, ...
FROM table1
MINUS
SELECT column1, column2, ...
FROM table2;

Example:

SELECT CustomerID FROM Customers_A
MINUS
SELECT CustomerID FROM Customers_B;

This query will return a list of customer IDs that are present in Customers_A but not in Customers_B.

INTERSECT

Purpose: Returns rows that are present in both SELECT statements.

Syntax:

SELECT column1, column2, ...
FROM table1
INTERSECT
SELECT column1, column2, ...
FROM table2;

Example:

SELECT CustomerID FROM Customers_A
INTERSECT
SELECT CustomerID FROM Customers_B;

This query will return a list of customer IDs that are present in both Customers_A and Customers_B.

Key Points to Remember:

• The number and data types of columns in the SELECT statements must be compatible for UNION, MINUS, and INTERSECT operations.
• To preserve duplicate rows in the result set of a UNION operation, use UNION ALL.
• When using MINUS and INTERSECT, the order of rows in the result set is not guaranteed.
• It's essential to optimize your queries by considering the size of the result sets and the indexes on the tables involved.

By mastering these set operators, you can efficiently manipulate and analyze data, gaining valuable insights from your database.