Slow joins are one of the most common SQL performance bottlenecks. Here's how to fix them:

5 Quick Optimizations

1. Index Your Join Columns

Always create indexes on columns used in JOIN conditions. This is the single biggest performance gain.

CREATE INDEX idx_user_id ON orders(user_id);
CREATE INDEX idx_product_id ON order_items(product_id);

2. Filter Early with WHERE

Apply WHERE conditions before the JOIN to reduce the dataset size:

-- Better: Filter first
SELECT u.name, o.total
FROM users u
JOIN (SELECT * FROM orders WHERE created_at > '2025-01-01') o
  ON u.id = o.user_id;

3. Use the Right Join Type

• INNER JOIN when you need matching records only (fastest)
• LEFT JOIN when you need all records from the left table
• Avoid RIGHT/FULL OUTER joins if possible

4. Join on Matching Data Types

Ensure columns have the same data type. Joining INT to VARCHAR forces type conversion and prevents index usage.

5. Limit Column Selection

Only SELECT the columns you need. Avoid SELECT * in joins—it increases memory and I/O overhead.