Re: pb with big volumes - Mailing list pgsql-general

From Adam Scott
Subject Re: pb with big volumes
Date
Msg-id CA+s62-P=_NCCm1c=D8bp3vBk4+y+OXYQcvXhUjYkzY_SGiDtQQ@mail.gmail.com
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In response to pb with big volumes  (Marc Millas <marc.millas@mokadb.com>)
Responses Re: pb with big volumes
List pgsql-general
I think your concern is that 20 min + 30 min does not equal 3 hours.

It might be natural to think the contention would, at max, be 50 min x 2 (1 hr 40 min).

So what's going on?

It seems disk I/O  is a primary suspect since you hint for an iostat replacement inside of Postgres.

If it is due to disk I/O the resolution will be to add RAID 0 SSDs at best.

Consider looking at io stats on the container's persistent volumes.

What is the pipe connecting the database server to the disks?  If it's NAS, well that would explain it.

HTH,
Adam



On Thu, Aug 10, 2023 at 2:37 PM Marc Millas <marc.millas@mokadb.com> wrote:
Hi,

I have a 15 TB db on postgres 14 (soon 15).
shared buffers is 32 GB.

It's a db with max 15 users and often less, and currently 1 or 2.
the biggest table have 133 partitions of 150M to 200M+ rows each.
lots of request access explicitly one of those.

When I, alone, run a query "reading" 15M buffers, it takes 20 minutes (+-5minutes). inside the query there are  2 group by on a 200M rows partition, with all the rows in each group by.
When a colleague run the same kind of request (not the same request, but something reading roughly the same volume ) , on a different set of data,   his request is completed in less than half an hour.
If we run our requests simultaneously... my request take hours. around 3 hours.

I am making a supposition that its some kind of "pumping" effect in the cache. 

I cannot have access to the underlying OS. I can, for sure, do some copy xx from program 'some command',  but its a container with very limited possibilities, not even 'ps'.
So I would like to monitor from inside the db (so without iostat and the same)  the volumes of read that postgres do to the OS.
I did activate track_io_timing, but the volumes I get in the explain analyze buffer are roughly the same alone or not alone. (the 15M buffers told )
to my understanding, the volumes that are shown in pg_stat_database are the useful ones ie. even if the db as to read it from disk more than once. true ? or false ?

So.. either my supposition is not correct, and I will read with a lot of interest other ideas
either its correct and I would like to know how to monitor this (in the current context, installing a dedicated extension is not impossible, but is a very boring process)

Thanks for your help :-)

regards,

PS: I know that providing the complete data model and the exact requests can be considered mandatory, but when I change the request I get the very same behaviour...



Marc MILLAS
Senior Architect
+33607850334

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