MySQL chooses to execute queries, or not, at whim - mysql

Question

For a reporting output, I used to DROP and recreate a table 'mis.pr_approval_time'. but now I just TRUNCATE it.
After populating the above table with data, I run an UPDATE statement, but I have written that as a SELECT below...
SELECT t.account_id FROM mis.hj_approval_survey h INNER JOIN mis.pr_approval_time t ON h.country = t.country AND t.scheduled_at =
(
SELECT MAX(scheduled_at) FROM mis.pr_approval_time
WHERE country = h.country
AND scheduled_at <= h.created_at
AND TIME_TO_SEC(TIMEDIFF(h.created_at, scheduled_at)) < 91
);
When I run the above statement or even just...
SELECT t.account_id FROM mis.hj_approval_survey h INNER JOIN mis.pr_approval_time t ON h.country = t.country AND t.scheduled_at =
(
SELECT MAX(scheduled_at) FROM mis.pr_approval_time
WHERE country = h.country
);
...it runs forever and does not seem to finish. There are only ~3,400 rows in hj_approval_survey table and 29,000 rows in pr_approval_time. I run this on an Amazon AWS instance with 15+ GB RAM.
Now, if I simply right click on pr_approval_time table and choose ALTER TABLE option, and just close without doing anything, then the above queries run within seconds.
I guess when I trigger the ALTER TABLE option and Workbench populates the table fields, it probably improves its execution plan somehow, but I am not sure why. Has anyone faced anything similar to this? How can I trigger a better execution plan check without right clicking the table and choosing 'ALTER TABLE'
EDIT
It may be noteworthy to mention that my organisation also uses DOMO. Originally, I had this setup as an MySQL Dataflow on DOMO, but the query would not complete on most occassions, but I have observed it finish at times.
This was the reason why I moved this query back to our AWS MySQL RDS. So the problem has not only been observed on our own MySQL RDS, but probably also on DOMO

Answer 1

I suspect this is slow because of the correlated subquery (subquery depends on row values from parent table, meaning it has to execute for each row). I'd try and rework the pr_approval_time table slightly so it's point-in-time and then you can use the JOIN to pick the correct rows without doing a correlated subquery. Something like:
SELECT
hj_approval_survey.country
, hj_approval_survey.created_at
, pr_approval_time.account_id
FROM
#hj_approval_survey AS hj_approval_survey
JOIN (
SELECT
current_row.country
, current_row.scheduled_at AS scheduled_at_start
, COALESCE( MIN( next_row.scheduled_at ), GETDATE() ) AS scheduled_at_end
FROM
#pr_approval_time AS current_row
LEFT OUTER JOIN
#pr_approval_time AS next_row ON (
next_row.country = current_row.country
AND next_row.scheduled_at > current_row.scheduled_at
)
GROUP BY
current_row.country
, current_row.scheduled_at
) AS pr_approval_pit ON (
pr_approval_pit.country = hj_approval_survey.country
AND ( hj_approval_survey.created_at >= pr_approval_pit.scheduled_at_start
AND hj_approval_survey.created_at < pr_approval_pit.scheduled_at_end
)
)
JOIN #pr_approval_time AS pr_approval_time ON (
pr_approval_time.country = pr_approval_pit.country
AND pr_approval_time.scheduled_at = pr_approval_pit.scheduled_at_start
)
WHERE
TIME_TO_SEC( TIMEDIFF( hj_approval_survey.created_at, pr_approval_time.scheduled_at ) ) < 91

Answer 2

Assuming you have proper index on the columns involved in join
You could try refactoring your query using a grouped by subquery and join on country
SELECT t.account_id
FROM mis.hj_approval_survey h
INNER JOIN mis.pr_approval_time t ON h.country = t.country
INNER JOIN (
SELECT country, MAX(scheduled_at) max_sched
FROM mis.pr_approval_time
group by country
) z on z.contry = t.country and t.scheduled_at = z.max_sched