Introduction to the SELECT Statement

Table of Contents

1. Introduction
2. What is the SELECT Statement?
3. Basic Syntax of SELECT
4. Selecting All Columns with *
5. Selecting Specific Columns
6. Using Aliases with AS
7. Selecting Distinct Records
8. Filtering Results with WHERE
9. Logical Operators: AND, OR, NOT
10. Comparison Operators
11. Working with NULL
12. Sorting Results with ORDER BY
13. Limiting Results with LIMIT
14. Selecting Based on Ranges: BETWEEN
15. Using IN to Match Multiple Values
16. Pattern Matching with LIKE
17. Combining Conditions
18. Real-World Query Examples
19. Best Practices for SELECT Queries
20. Summary and What’s Next

1. Introduction

The SELECT statement is the foundation of SQL. It’s the command used to retrieve data from a database. Whether you’re pulling records from a table, filtering data, or aggregating it for analysis, SELECT is your go-to tool.

In this module, we’ll explore everything you need to know to write your first SELECT queries confidently.

2. What is the SELECT Statement?

The SELECT statement retrieves rows from one or more tables or views. It allows you to specify which columns you want, apply conditions, sort, limit, and more.

3. Basic Syntax of SELECT

SELECT column1, column2
FROM table_name;

Example:

SELECT name, email FROM users;

4. Selecting All Columns with *

The asterisk (*) selects all columns:

SELECT * FROM users;

Useful for quick debugging or exploration, but avoid it in production queries for performance reasons.

5. Selecting Specific Columns

You can specify only the columns you need:

SELECT name, age FROM employees;

This improves performance and makes results easier to understand.

6. Using Aliases with AS

Aliases give columns or tables temporary names:

SELECT name AS full_name, age AS years_old FROM users;

You can also alias tables:

SELECT u.name FROM users AS u;

7. Selecting Distinct Records

To eliminate duplicates:

SELECT DISTINCT city FROM customers;

DISTINCT ensures only unique values are returned.

8. Filtering Results with WHERE

The WHERE clause is used to filter records based on conditions.

SELECT * FROM orders WHERE total > 500;

You can use:

• Comparison operators: =, !=, <, >, <=, >=
• Logical operators: AND, OR, NOT
• Special conditions: IN, BETWEEN, LIKE, IS NULL

9. Logical Operators: AND, OR, NOT

Combine multiple conditions:

sqlCopyEditSELECT * FROM employees 
WHERE department = 'HR' AND age > 30;

sqlCopyEditSELECT * FROM employees 
WHERE department = 'HR' OR department = 'Finance';

sqlCopyEditSELECT * FROM employees 
WHERE NOT age < 18;

10. Comparison Operators

Example:

sqlCopyEditSELECT * FROM products WHERE price <= 1000;

11. Working with NULL

NULL represents missing or unknown data. You cannot use = or != to compare NULL.

Use:

sqlCopyEditSELECT * FROM users WHERE email IS NULL;
SELECT * FROM users WHERE email IS NOT NULL;

12. Sorting Results with ORDER BY

sqlCopyEditSELECT name, age FROM users ORDER BY age;
SELECT name, age FROM users ORDER BY age DESC;

You can sort by one or more columns.

13. Limiting Results with LIMIT

Restrict number of rows:

sqlCopyEditSELECT * FROM users LIMIT 5;

MySQL and PostgreSQL support:

sqlCopyEditSELECT * FROM users LIMIT 5 OFFSET 10;

SQLite also supports this syntax.

14. Selecting Based on Ranges: BETWEEN

Check if a value falls within a range:

sqlCopyEditSELECT * FROM products WHERE price BETWEEN 100 AND 500;

Inclusive: includes both 100 and 500.

15. Using IN to Match Multiple Values

sqlCopyEditSELECT * FROM customers 
WHERE country IN ('India', 'Nepal', 'Bangladesh');

IN is cleaner and more efficient than multiple OR conditions.

16. Pattern Matching with LIKE

Use LIKE for partial matches with % and _.

sqlCopyEditSELECT * FROM users WHERE name LIKE 'A%';  -- Starts with A
SELECT * FROM users WHERE email LIKE '%@gmail.com';  -- Ends with
SELECT * FROM users WHERE name LIKE '_ohn'; -- Matches 4-letter name ending in "ohn"

17. Combining Conditions

sqlCopyEditSELECT * FROM employees
WHERE department = 'Sales' 
  AND (age > 30 OR city = 'Delhi');

Use parentheses to group complex logic for clarity and accuracy.

18. Real-World Query Examples

Find all active users above 25 years of age:

sqlCopyEditSELECT name, email FROM users
WHERE age > 25 AND is_active = TRUE;

Get top 3 highest-paying jobs:

sqlCopyEditSELECT title, salary FROM jobs
ORDER BY salary DESC
LIMIT 3;

Search for customers not in India or Nepal:

sqlCopyEditSELECT * FROM customers
WHERE country NOT IN ('India', 'Nepal');

19. Best Practices for SELECT Queries

• Avoid using SELECT * in production
• Use meaningful aliases for readability
• Filter early with WHERE to improve performance
• Sort data after filtering, not before
• Use indexes wisely for large datasets

20. Summary and What’s Next

The SELECT statement is your entry point to reading and analyzing data. Mastering it will help you query any relational database confidently. We’ve covered syntax, filtering, sorting, and limiting — all crucial to practical SQL use.