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 Selecting Unnecessary Columns (query line: 11): Avoid selecting all columns with the '*' wildcard, unless you intend to use them all. Selecting redundant columns may result in unnecessary performance degradation.
- Avoid Subqueries (query line: 10): 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.
- 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.
- Prefer Direct Join Over Joined Subquery (query line: 14): 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 `User_Info` ADD INDEX `user_info_idx_action_user_name_url` (`action`,`user_name`,`url`);
The optimized query:
ROW_NUMBER() OVER (ORDER
info.modified_date DESC) rn
Count(*) OVER () AS info_count
info.url LIKE 'url://%'
info.action = 'Action1'
AND info.user_name = 'john'
AND info.modified_date >= '04/01/2014 00:00:00'
AND info.modified_date <= '04/12/2014 23:59:59'
)) info) info
rn >= 1
AND rn <= 100