Also read about hot updates and the storage parameter named "fill_factor", so, data blocks can be recycled instead of creating new ones if the updated fields don't update also indexes.
Am Mi., 5. Dez. 2018 um 09:39 Uhr schrieb Alexey Bashtanov <bashtanov@xxxxxxx>:
>
> The table has around 1.5M rows which have been updated/inserted around
> 121M times, the distribution of updates to row in alerts_alert will be
> quite uneven, from 1 insert up to 1 insert and 0.5M updates.
>
> Under high load (200-300 inserts/updates per second) we see occasional
> (~10 per hour) updates taking excessively long times (2-10s). These
> updates are always of the form:
>
> UPDATE "alerts_alert" SET ...bunch of fields... WHERE
> "alerts_alert"."id" = '...sha1 hash...';
>
> Here's a sample explain:
>
> https://explain.depesz.com/s/Fjq8
>
> What could be causing this? What could we do to debug? What config
> changes could we make to alleviate this?
>
Hello Chris,
One of the reasons could be the row already locked by another backend,
doing the same kind of an update or something different.
Are these updates performed in a longer transactions?
Can they hit the same row from two clients at the same time?
Is there any other write or select-for-update/share load on the table?
Have you tried periodical logging of the non-granted locks?
Try querying pg_stat_activity and pg_locks (possibly joined and maybe
repeatedly self-joined, google for it)
to get the backends that wait one for another while competing for to
lock the same row or object.
Best,
Alex
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