[Solved] Advanced query running slowly

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:

  1. Description of the steps you can take to speed up the query.
  2. The optimal indexes for this query, which you can copy and create in your database.
  3. An automatically re-written query you can copy and execute in your database.
The optimization process and recommendations:
  1. Avoid Calling Functions With Indexed Columns (query line: 14): 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 `time` is indexed, the index won’t be used as it’s wrapped with the function `UNIX_TIMESTAMP`. 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.
  2. Avoid Calling Functions With Indexed Columns (query line: 27): 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 `time` is indexed, the index won’t be used as it’s wrapped with the function `UNIX_TIMESTAMP`. 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.
  3. Avoid Correlated Subqueries (query line: 17): A correlated subquery is a subquery that contains a reference (column: id) 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.
  4. 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 `war` ADD INDEX `war_idx_started_guild1_winner` (`started`,`guild1`,`winner`);
ALTER TABLE `war` ADD INDEX `war_idx_started_guild2_winner` (`started`,`guild2`,`winner`);
The optimized query:
SELECT
        g.name,
        g.id,
        (SELECT
            COALESCE(SUM(gwr.result2 / gwr.result1) * (SUM(IF(gwr.result2 != 0,
            1,
            0)) * 0.1),
            0) AS res 
        FROM
            gump.war gwr 
        WHERE
            gwr.started = 1 
            AND (
                UNIX_TIMESTAMP(gwr.time) + 7 * 24 * 60 * 60
            ) > UNIX_TIMESTAMP() 
            AND gwr.guild1 = g.id 
            AND gwr.winner = g.id) + (SELECT
            COALESCE(SUM(gwr.result1 / gwr.result2) * (SUM(IF(gwr.result1 != 0,
            1,
            0)) * 0.1),
            0) AS res1 
        FROM
            gumb.war gwr 
        WHERE
            gwr.started = 1 
            AND (
                UNIX_TIMESTAMP(gwr.time) + 7 * 24 * 60 * 60
            ) > UNIX_TIMESTAMP() 
            AND gwr.guild2 = g.id 
            AND gwr.winner = g.id) AS avg 
    FROM
        gumb.guild g 
    ORDER BY
        avg DESC,
        g.point DESC,
        g.experience DESC LIMIT 10

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* original question posted on StackOverflow here.