On Fri, Jul 3, 2015 at 9:48 AM, Graeme B. Bell <graeme.bell@xxxxxxxx> wrote: > Hi everyone, > > I've written a new open source tool for easily parallelising SQL scripts in postgres. [obligatory plug: https://github.com/gbb/par_psql ] > > Using it, I'm seeing a problem that I've also seen in other postgres projects involving high degrees of parallelisation in the last 12 months. > > Basically: > > - I have machines here with up to 16 CPU cores and 128GB memory, very fast SSDs and controller etc, carefully configured kernel/postgresql.conf for high performance. > > - Ordinary queries parallelise nearly perfectly (e.g. SELECT some_stuff ...), e.g. almost up to 16x performance improvement. > > - Non-DB stuff like GDAL, python etc. parallelise nearly perfectly. > > - HOWEVER calls to CPU-intensive user-defined pl/pgsql functions (e.g. SELECT myfunction(some_stuff)) do not parallelise well, even when they are independently defined functions, or accessing tables in a read-only way. They hit a limit of 2.5x performance improvement relative to single-CPU performance (pg9.4) and merely 2x performance (pg9.3) regardless of how many CPU cores I throw at them. This is about 6 times slower than I'm expecting. > > I can't see what would be locking. It seems like it's the pl/pgsql environment itself that is somehow locking or incurring some huge frictional costs. Whether I use independently defined functions, independent source tables, independent output tables, makes no difference whatsoever, so it doesn't feel 'lock-related'. It also doesn't seem to be WAL/synchronisation related, as the machines I'm using can hit absurdly high pgbench rates, and I'm using unlogged tables for output. > > Take a quick peek here: https://github.com/gbb/par_psql/blob/master/BENCHMARKS.md > > I'm wondering what I'm missing here. Any ideas? I'm not necessarily seeing your results. via pgbench, mmoncure@mernix2 11:34 AM ~$ ~/pgdev/bin/pgbench -n -T 60 -f b.sql transaction type: Custom query scaling factor: 1 query mode: simple number of clients: 1 number of threads: 1 duration: 60 s number of transactions actually processed: 658833 latency average: 0.091 ms tps = 10980.538470 (including connections establishing) tps = 10980.994547 (excluding connections establishing) mmoncure@mernix2 11:35 AM ~$ ~/pgdev/bin/pgbench -n -T 60 -c4 -j4 -f b.sql transaction type: Custom query scaling factor: 1 query mode: simple number of clients: 4 number of threads: 4 duration: 60 s number of transactions actually processed: 2847631 latency average: 0.084 ms tps = 47460.430447 (including connections establishing) tps = 47463.702074 (excluding connections establishing) b.sql: select f(); f(): create or replace function f() returns int as $$ begin return 1; end; $$ language plpgsql; the results are pretty volatile even with a 60s run, but I'm clearly not capped at 2.5x parallelization (my box is 4 core). It would help if you disclosed the function body you're benchmarking. If the problem is indeed on the sever, the next step I think is to profile the code and look for locking issues. merlin -- Sent via pgsql-performance mailing list (pgsql-performance@xxxxxxxxxxxxxx) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance
