56 SQL Queries That Will Destroy Your Database (Part 2 of 56)
This post is part of my ongoing learning notes from a paid SQL performance guide I am studying. In this series, I’m documenting important SQL anti-patterns, why they cause performance issues, and how to fix them in real-world scenarios.

This is Query #2 in the series, and it focuses on a very common performance issue: missing indexes on JOIN columns.
In SQL, JOIN operations are used to combine data from multiple tables. But behind the scenes, the database has to find matching rows between those tables. This matching process becomes slow if the join column is not indexed.
Query #3: Missing Index on a JOIN Column
The dangerous query:
Why is this dangerous
When the database executes a JOIN, it needs to compare rows between the two tables using the join condition:
If orders.customer_id is not indexed, and the database has no fast way to find matching rows. Instead, it may:
Scan the entire
orderstableCompare each row manually
Repeat this process for the matching logic
This is called a sequential scan, and it becomes very slow as the table grows.
In small development datasets, this may not be noticeable. But in production systems with millions of rows, it can cause serious performance degradation and slow query response times.
The fixed version
To solve this, we create an index on the foreign key column:
Then run the same query:
One-line rule
Always index columns used in JOIN conditions, especially foreign keys.
