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:
- Description of the steps you can take to speed up the query.
- The optimal indexes for this query, which you can copy and create in your database.
- An automatically re-written query you can copy and execute in your database.
The optimization process and recommendations:
- 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.
- Explicitly ORDER BY After GROUP BY (modified query below): By default, the database sorts all 'GROUP BY col1, col2, ...' queries as if you specified 'ORDER BY col1, col2, ...' in the query as well. If a query includes a GROUP BY clause but you want to avoid the overhead of sorting the result, you can suppress sorting by specifying 'ORDER BY NULL'.
- Replace Left Join With Subquery (modified query below): The pattern of inflating the amount of data (using joins) and deflating (using GROUP BY) usually slows down queries. In this case, it can be avoided by moving some of the logic to the SELECT clause, and therefore removing some of the LEFT JOINs. In some cases, this transformation can lead to an obsolete GROUP BY clause, which can also be removed.
Optimal indexes for this query:
ALTER TABLE `categories` ADD INDEX `categories_idx_id` (`id`);
ALTER TABLE `places` ADD INDEX `places_idx_id` (`id`);
ALTER TABLE `places_categories_rel` ADD INDEX `places_rel_idx_place_id` (`place_id`);
The optimized query:
GROUP_CONCAT(DISTINCT cat.name SEPARATOR ',') AS categories
cat.id = rel.category_id LIMIT 1) AS categories
ON p.id = rel.place_id