Re: Understanding query planner cpu usage - Mailing list pgsql-general
| From | Lucas Fairchild-Madar |
|---|---|
| Subject | Re: Understanding query planner cpu usage |
| Date | |
| Msg-id | CAJmoq7NtboWu13rKznLgjSkud-soQwvth3XVgxyG2-psg5Mx-g@mail.gmail.com Whole thread Raw |
| In response to | Re: Understanding query planner cpu usage (Tom Lane <tgl@sss.pgh.pa.us>) |
| Responses |
Re: Understanding query planner cpu usage
|
| List | pgsql-general |
On Wed, Feb 21, 2018 at 4:14 PM, Tom Lane <tgl@sss.pgh.pa.us> wrote:
Lucas Fairchild-Madar <lucas.madar@gmail.com> writes:
> I'm having an perplexing issue in PG 10.1 wherein deleting a large amount
> of rows from a table causes query planning time to spike dramatically for a
> while. This happens with or without autovacuums so vacuuming isn't the
> issue.
Would the deleted rows happen to be the extremal values of some indexed
column that is a join key in the slowly-planned queries?
Yes. Basically, this is sort of a moving set of several weeks of data. We have a job that goes through (currently, every 3 hours) and periodically wipes out data from the very beginning. At the same time, more data is continually being appended to the table. All of these rows are immutable. The vast majority of the work happening in the database happens in the last two or three million rows of these tables; the rest is just there for auditing and analytics.
If so, this might be some manifestation of a problem we've seen before:
the planner tries to find out the current live max value of the column
by scanning the index, and that's really slow if there are a lot of
recently-dead entries at the index end, because each of them has to be
inspected and then hinted dead. You'd pay that overhead at some point
anyway, of course. The cases where it becomes a problem are where the
planner inspects these values but *can't* hint them dead, such as when
the deletion hasn't committed yet, or they're newly inserted rows that
likewise aren't committed. Then each incoming query does the work
over again until the transient state is resolved.
We've done various things to ameliorate this, but maybe you've found
some new way to cause it to be a pain point. Is there anything special
about the way you're deleting the rows? Maybe there's a long-running
transaction in the background that can still see the deleted rows?
This sounds like the trigger here. We have a long-running (~20 minute) transaction that's doing analytical rollups on these sets of tables. It's doing them only on very recent data, but I assume having an open transaction means the tuples can't be marked as dead yet because the queries within that transaction could still potentially access them.
I took a look further in this direction and found that our cleanup process and this analytical rollup both happened to run very close to each other twice a day. I moved the cleanup process to run at a time when it should never collide with analytical rollups and we'll see if the load spike happens again. When this happens, the long-running query takes almost an hour so the problem compounds.
It would be helpful to have a way to introspect in to what the query planner is doing. For instance, if I could explain (analyze, verbose, queryplan) the query and the queryplan told me that it spent 5000ms skipping over dead tuples in the index, knowing that would arm me with more information to tune the system better.
Perhaps this is a stupid question, but would creating the index in descending order solve this problem (as a unique index, not a primary key)? What is the planner doing when trying to find the current live max value of the column?
Thanks,
Lucas
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