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: 2): Avoid selecting all columns with the '*' wildcard, unless you intend to use them all. Selecting redundant columns may result in unnecessary performance degradation.
- Avoid Subselect When Selecting MAX/MIN Per Group (query line: 11): Constant subquery results are usually not cached by the database, especially in non-recent database versions. Therefore, a constant subquery in a WHERE clause will be fully evaluated for every row the WHERE clause will examine, which can significantly impact query performance. Use the method mentioned in the example instead.
- 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:
CREATE INDEX engineer_idx_id_process ON engineer (id,process);
The optimized query:
SELECT
e.*,
r.report_name
FROM
report r
LEFT JOIN
engineer AS engineer1
ON engineer1.id = r.id
LEFT JOIN
engineer AS engineer2
ON (
engineer2.process = r.process
)
AND (
engineer1.id < engineer2.id
)
WHERE
(
1 = 1
)
AND (
engineer2.id IS NULL
)