SQL Query Optimization: Combining Multiple Joins for Improved Performance

[Vandiun]

I'm working on an SQL query for a complex reporting system that involves multiple tables and joins. However, the query's performance is not meeting my expectations, and I suspect that the way I've structured my joins might be inefficient.

Here's a simplified version of my query:

SELECT
    orders.order_id,
    customers.customer_name,
    products.product_name,
    order_details.quantity,
    order_details.unit_price
FROM
    orders
JOIN
    customers ON orders.customer_id = customers.customer_id
JOIN
    order_details ON orders.order_id = order_details.order_id
JOIN
    products ON order_details.product_id = products.product_id
WHERE
    orders.order_date BETWEEN '2023-01-01' AND '2023-12-31';

While this query returns the correct results, it's taking a significant amount of time to execute, especially when dealing with a large dataset.

I'd like to optimize this query for better performance. Could someone review my SQL code and suggest improvements or alternative approaches to achieve the same result more efficiently? Additionally, are there any indexing strategies or database design considerations that might help enhance the query's speed? Any insights or code optimizations would be greatly appreciated. Thank you!

[Dani]

Hello!

I would create an INDEX on the orders table in this order: order_date, customer_id, order_id, product_id

I would also create an INDEX on the customers table for customer_id, the order_details table for order_id, and the products table for product_id.

I don't see any inefficiency in your query itself, but I would definitely create those indexes.

Let me know if this works :)

[Dani]

I would also create an INDEX on the customers table for customer_id, the order_details table for order_id, and the products table for product_id.

Just to add, this is only if those columns aren’t already primary ids, or indexes already exist in which they are listed first.

[pritaeas]

You're querying over an entire year. If this is the point of your query, I would add an extra indexed column to my orders table called year INT and filter on that. Should be much quicker than using a BETWEEN on a date column.

[DGPickett]

Generally any column named id is an artificial, auto-incremented, indexed key. Are your id's also primary keys, and so indexed? If a btree index, maybe make a hash index?

A order date index btree not hash allows a range selection.