optimizing mysql subquery execution time - mysql

Question

I have a following query:
select
qs.*
from
(
select
tsk.id,
tsk.request_id,
tsk.hash_id
from
user_tasks as usr
inner join unassigned_tasks as tsk on usr.task_id = tsk.id
where
usr.assigned_to = 53
AND tsk.product_id NOT IN (
SELECT
product_id
FROM
product_progresses
WHERE
request_id = tsk.request_id
)
ORDER BY
tsk.id
) as qs <-- this takes about 233ms.
WHERE
qs.id = ( <-- should this subquery execute for every row from outer result-set row?
SELECT
min(qt.id)
FROM
(
select
tsk.id,
tsk.request_id,
tsk.hash_id
from
user_tasks as usr
inner join unassigned_tasks as tsk on usr.task_id = tsk.id
where
usr.assigned_to = 53
AND tsk.product_id NOT IN (
SELECT
product_id
FROM
product_progresses
WHERE
request_id = tsk.request_id
)
ORDER BY
tsk.id
) as qt <-- this takes about 233ms.
WHERE
qt.id > 83934
)
Both qs and qt takes about the same time to execute, i.e. around 233ms.
Also, executing this whole query takes about the same time.
I have a conception that inner query inside where qs.id = (...) executes once for every row in the result-set generated from qs.
In this current case, qs outputs 10 rows.
So I decided to test if the sub-query is executed for each row 10 times.
Here's what I put inside sub-query:
WHERE qs.id = (
SELECT
SLEEP(1)
)
instead of where qs.id = ( select min(qt.id) ... ).
This took about 10.246 s which proves that the inner query is being run for each row.
So with this, shouldn't the initial query take about (qt time) 233 * 10 (rows from qs) = 2330ms?
Is it because select min().. is calculated once only?

Answer 1

In MySQL subqueries within the FROM clause are evaluated before subqueries in the WHERE clause.
Useful article:
https://www.eversql.com/sql-order-of-operations-sql-query-order-of-execution/
In your case, this is causing qs to be fully evaluated before the WHERE clause is factored in. If you want qs to be limited by qt you should be able to achieve that by unnesting qs or moving qt inside qs.
In practice though, rather than use a subquery for the WHERE clause, it would be probably better to use joins.
See SQL select only rows with max value on a column