[Solved] Querying Large Dataset on Join (15+ million rows)

How to optimize this SQL query?

In case you have your own slow SQL query, you can optimize it automatically here.

For the query above, the following recommendations will be helpful as part of the SQL tuning process.
You'll find 3 sections below:

  1. Description of the steps you can take to speed up the query.
  2. The optimal indexes for this query, which you can copy and create in your database.
  3. An automatically re-written query you can copy and execute in your database.
The optimization process and recommendations:
  1. Create Optimal Indexes (modified query below): The recommended indexes are an integral part of this optimization effort and should be created before testing the execution duration of the optimized query.
  2. Mixed Order By Directions Prevents Index Use (query line: 11): The database will not use a sorting index (if exists) in cases where the query mixes ASC (the default if not specified) and DESC order. To avoid filesort, you may consider using the same order type for all columns. Another option that will allow you to switch one direction to another is to create a new reversed "sort" column (max_sort - sort) and index it instead.
  3. Prefer Direct Join Over Joined Subquery (query line: 7): We advise against using subqueries as they are not optimized well by the optimizer. Therefore, we recommend to replace subqueries with JOIN clauses.
Optimal indexes for this query:
ALTER TABLE `products` ADD INDEX `products_idx_id` (`id`);
ALTER TABLE `products_markets` ADD INDEX `products_markets_idx_country_id` (`country_code_id`);
The optimized query:
        products p 
            ON p.id = products_markets.product_id 
        products_markets.country_code_id = 121 
        p.`popularity` DESC,
        `p`.`id` ASC LIMIT 50

Related Articles

* original question posted on StackOverflow here.