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:
- Use Numeric Column Types For Numeric Values (query line: 17): Referencing a numeric value (e.g. 19) as a string in a WHERE clause might result in poor performance. Possible impacts of storing numbers as varchars: more space will be used, you won't be able to perform arithmetic operations, the data won't be self-validated, aggregation functions like SUM won't work, the output may sort incorrectly and more. If the column is numeric, remove the quotes from the constant value, to make sure a numeric comparison is done.
- Use Numeric Column Types For Numeric Values (query line: 21): Referencing a numeric value (e.g. 1) as a string in a WHERE clause might result in poor performance. Possible impacts of storing numbers as varchars: more space will be used, you won't be able to perform arithmetic operations, the data won't be self-validated, aggregation functions like SUM won't work, the output may sort incorrectly and more. If the column is numeric, remove the quotes from the constant value, to make sure a numeric comparison is done.
- Use Numeric Column Types For Numeric Values (query line: 24): Referencing a numeric value (e.g. 1) as a string in a WHERE clause might result in poor performance. Possible impacts of storing numbers as varchars: more space will be used, you won't be able to perform arithmetic operations, the data won't be self-validated, aggregation functions like SUM won't work, the output may sort incorrectly and more. If the column is numeric, remove the quotes from the constant value, to make sure a numeric comparison is done.
The optimized query:
SELECT
`main_table`.`entity_id`,
main_table.`name`,
main_table.`path`,
`main_table`.`is_active`,
`main_table`.`is_anchor`,
`url_rewrite`.`request_path`,
`main_table`.`url_override`,
`main_table`.`display_subcategories`
FROM
`catalog_category_flat_store_19` AS `main_table`
LEFT JOIN
`core_url_rewrite` AS `url_rewrite`
ON url_rewrite.category_id = main_table.entity_id
AND url_rewrite.is_system = 1
AND url_rewrite.product_id IS NULL
AND url_rewrite.store_id = '19'
AND url_rewrite.id_path LIKE 'category/%'
WHERE
(
main_table.is_active = '1'
)
AND (
main_table.include_in_menu = '1'
)
AND (
main_table.path LIKE '1/1877/%'
)
AND (
`level` <= 3
)
ORDER BY
`main_table`.`position` ASC