Re: perf tuning for 28 cores and 252GB RAM

On 18/06/2019 00:45, Jeff Janes wrote:
> On Mon, Jun 17, 2019 at 4:51 PM Michael Curry <curry@cs.umd.edu
> <mailto:curry@cs.umd.edu>> wrote:
>
>     I am using a Postgres instance in an HPC cluster, where they have
>     generously given me an entire node. This means I have 28 cores and
>     252GB RAM. I have to assume that the very conservative default
>     settings for things like buffers and max working memory are too
>     small here.
>
>     We have about 20 billion rows in a single large table.
>
>
> What is that in bytes?  Do you only have that one table?
>
>     The database is not intended to run an application but rather to
>     allow a few individuals to do data analysis, so we can guarantee the
>     number of concurrent queries will be small, and that nothing else
>     will need to use the server. Creating multiple different indices on
>     a few subsets of the columns will be needed to support the kinds of
>     queries we want.
>
>     What settings should be changed to maximize performance?
>
>
> With 28 cores for only a few users, parallelization will probably be
> important.  That feature is fairly new to PostgreSQL and rapidly
> improving from version to version, so you will want to use the last
> version you can (v11).  And then increase the values for
> max_worker_processes, max_parallel_maintenance_workers,
> max_parallel_workers_per_gather, and max_parallel_workers.  With the
> potential for so many parallel workers running at once, you wouldn't
> want to go overboard on work_mem, maybe 2GB.  If you don't think all
> allowed users will be running large queries at the same time (because
> they are mostly thinking what query to run, or thinking about the
> results of the last one they ran, rather than actually running queries),
> then maybe higher than that.
>
> If your entire database can comfortably fit in RAM, I would make
> shared_buffers large enough to hold the entire database.  If not, I
> would set the value small (say, 8GB) and let the OS do the heavy lifting
> of deciding what to keep in cache.


Does the backend mmap() data files when that's possible?


I've heard the "use the page cache" suggestion before, from users and
hackers alike, but I never quite heard a solid argument dismissing
potential overhead-related ill effects of the seek() & read() syscalls
if they're needed, especially on many random page fetches.


Given that shmem-based shared_buffers are bound to be mapped into the
backend's address space anyway, why isn't that considered always
preferable/cheaper?



I'm aware that there are other benefits in counting on the page cache
(eg: staying hot in the face of a backend restart), however I'm
considering performance in steady state here.



TIA



If you go with the first option, you
> probably want to use pg_prewarm after each restart to get the data into
> cache as fast as you can, rather than let it get loaded in naturally as
> you run queries;  Also, you would probably want to set random_page_cost
> and seq_page_cost quite low, like maybe 0.1 and 0.05.
>
> You haven't described what kind of IO capacity and setup you have,
> knowing that could suggest other changes to make.  Also, seeing the
> results of `explain (analyze, buffers)`, especially with track_io_timing
> turned on, for some actual queries could provide good insight for what
> else might need changing.
>
> Cheers,
>
> Jeff





--
Regards

Fabio Ugo Venchiarutti
OSPCFC Network Engineering Dpt.
Ocado Technology

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