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 Calling Functions With Indexed Columns (query line: 15): When a function is used directly on an indexed column, the database's optimizer won’t be able to use the index. For example, if the column `seconds` is indexed, the index won’t be used as it’s wrapped with the function `abs`. If you can’t find an alternative condition that won’t use a function call, a possible solution is to store the required value in a new indexed column.
Avoid Correlated Subqueries (query line: 9): A correlated subquery is a subquery that contains a reference (column: seconds) to a table that also appears in the outer query. Usually correlated queries can be rewritten with a join clause, which is the best practice. The database optimizer handles joins much better than correlated subqueries. Therefore, rephrasing the query with a join will allow the optimizer to use the most efficient execution plan for the query.
Avoid Selecting Unnecessary Columns (query line: 2): Avoid selecting all columns with the '*' wildcard, unless you intend to use them all. Selecting redundant columns may result in unnecessary performance degradation.
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.
Optimal indexes for this query:
ALTER TABLE `entries` ADD INDEX `entries_idx_status` (`status`);
The optimized query:
e0.status = 1
OR e0.status = 0
AND 0 < (
e1.status = 1
AND abs(e1.seconds - e0.seconds) < 10