Every developer has faced slow SQL queries at some point. The reasons can vary: unoptimized indexes, heavy JOIN operations, or the lack of proper caching strategies. In this article, we’ll explore how to properly index databases and speed up SQL queries in PostgreSQL and MySQL.
🔹 Main Types of Indexes
B-Tree Index – A general-purpose index used for most search and sorting operations.
Hash Index – Speeds up exact value searches but is not suitable for sorting.
GIN Index – Ideal for full-text search queries.
BRIN Index – Works efficiently with large tables and ordered datasets.
📌 Optimizing JOIN Queries
Use indexes on columns participating in JOIN.
Replace JOIN with EXISTS if filtering data.
Analyze queries using EXPLAIN ANALYZE to understand their execution.
🏆 Practical Example
Let's take an example of optimizing a JOIN query in PostgreSQL:
SELECT users.id, users.name, orders.amount
FROM users
JOIN orders ON users.id = orders.user_id
WHERE orders.amount > 100;
To speed this up, we add indexes:
CREATE INDEX idx_users_id ON users(id);
CREATE INDEX idx_orders_user_id ON orders(user_id);
By applying these small but effective optimizations, queries can run up to 10x faster! 🚀
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