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:
- 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.
- Index Function Calls Using Generated Columns (modified query below): When a function is used directly on an indexed column, the database's optimizer won’t be able to use the index to optimize the search. Creating and indexing a generated column (supported in MySQL 5.7) will allow MySQL to optimize the search.
- Use Numeric Column Types For Numeric Values (query line: 9): Referencing a numeric value (e.g. 30) 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.
Optimal indexes for this query:
ALTER TABLE `bills` ADD INDEX `bills_idx_amt_substring_7` (`amt`,`substring_tdate_1_7`);
The optimized query:
SELECT
count(*),
substring(bills.tdate,
1,
7)
FROM
bills
WHERE
bills.amt = '30'
GROUP BY
bills.substring_tdate_1_7
ORDER BY
substring(bills.tdate,
1,
7) DESC