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:
- Avoid Correlated Subqueries In Select Clause (modified query below): The aggregation function located in a subquery inside the SELECT clause, is executed once for every matched row. Extracting this subquery to a temporary table will improve performance significantly.
- Avoid Subqueries (query line: 6): We advise against using subqueries as they are not optimized well by the optimizer. Therefore, it's recommended to join a newly created temporary table that holds the data, which also includes the relevant search index.
- 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'.
The optimized query:
GROUP_CONCAT(totalPerStatus) AS status,
COUNT(*)) AS totalPerStatus
ON es_temp1.name = t.name