MySQL Table Indexing: A Complete Beginner’s Guide
When a database table grows large, searching for data can become slow and inefficient.
Imagine searching for a name in a 1000-page book without an index—you would have to read every page.
👉 Table indexing in MySQL solves this problem by making data searches fast and efficient.
This guide explains what indexing is, why it’s important, how it works, and how to use it correctly, even if you’ve never worked with databases before.
What Is Table Indexing in MySQL?
Simple Definition
A MySQL index is a data structure that improves the speed of data retrieval from a table.
Indexes work like a table of contents in a book.
Without Index
MySQL scans every row
Slower performance
With Index
MySQL finds data quickly
Much faster queries
Why Is Indexing Important?
- Faster
SELECTqueries - Improved search performance
- Efficient filtering (
WHERE,JOIN,ORDER BY) - Better scalability for large tables
⚠️ Important:
Indexes speed up reading data, but they slightly slow down INSERT, UPDATE, DELETE operations.
Real-Life Analogy
| Database Concept | Real-Life Example |
|---|---|
| Table | Book |
| Row | Page |
| Column | Topic |
| Index | Book Index |
👉 Without an index, you read every page.
👉 With an index, you jump directly to the page.
How Indexing Works in MySQL
MySQL creates a sorted structure
Stores column values with pointers to rows
Uses B-Tree (default) for most indexes
Searches become faster because MySQL avoids full table scans
Basic Index Syntax
Creating an Index
CREATE INDEX index_name ON table_name(column_name); Example
CREATE INDEX idx_city
ON customers(city);Speeds up searches on the city column.
Sample Table for Examples
Table: customers
| id | name | city | |
|---|---|---|---|
| 1 | Rahul | Delhi | r@gmail.com |
| 2 | Neha | Mumbai | n@gmail.com |
| 3 | Amit | Delhi | a@gmail.com |
Example 1: Query Without Index
SELECT * FROM customers WHERE city = 'Delhi'; MySQL scans every row to find matching records.
Example 2: Query With Index
CREATE INDEX idx_city ON customers(city); SELECT * FROM customers WHERE city = 'Delhi'; MySQL uses the index to locate rows quickly.
Types of Indexes in MySQL
PRIMARY KEY Index
Automatically created
Unique + Not NULL
One per table
PRIMARY KEY (id) UNIQUE Index
Prevents duplicate values
CREATE UNIQUE INDEX idx_email ON customers(email); ✔ No two customers can have the same email.
NORMAL (NON-UNIQUE) Index
Most common
Allows duplicate values
CREATE INDEX idx_city ON customers(city); COMPOSITE (MULTI-COLUMN) Index
Index on multiple columns
CREATE INDEX idx_city_name ON customers(city, name); ✔ Useful when filtering by both columns together
FULLTEXT Index
Used for text search
Works with
MATCH()andAGAINST()
CREATE FULLTEXT INDEX idx_name ON customers(name);
When Should You Use Indexes?
- Frequently searched columns
- Columns used in
WHEREclause - Columns used in
JOIN Columns used inORDER BYLarge tables
When NOT to Use Indexes
- Very small tables
- Columns with many updates
- Columns with low data variation (e.g., gender)
Indexing and WHERE Clause
SELECT * FROM customers
WHERE email = 'r@gmail.com';
✔ Index on email makes this query extremely fast.
Indexing and JOIN Performance
SELECT orders.id, customers.name
FROM orders
JOIN customers
ON orders.customer_id = customers.id;
✔ Indexes on customer_id and id improve JOIN speed.
Checking Existing Indexes
SHOW INDEX FROM customers;
✔ Displays all indexes on a table.
Removing an Index
DROP INDEX idx_city ON customers;Common Beginner Mistakes
❌ Indexing Every Column
Too many indexes reduce performance
❌ Ignoring Composite Index Order
(city, name) ≠ (name, city) ❌ Forgetting Index Impact on INSERT/UPDATE
Indexes slow down write operations.
Best Practices for Table Indexing
- Index only frequently searched columns
- Use composite indexes wisely
- Use
EXPLAINto analyze queries - Avoid unnecessary indexes
- Regularly review indexes
Using EXPLAIN to See Index Usage
EXPLAIN SELECT * FROM customers WHERE city = ‘Delhi’;
✔ Shows whether MySQL uses an index or not.
Quick Comparison: Indexed vs Non-Indexed Search
| Feature | Without Index | With Index |
|---|---|---|
| Speed | Slow | Fast |
| Table Scan | Full scan | Partial |
| Performance | Low | High |