Re: optimizing number of workers

Having just received a shiny new dual CPU machine to use as a postgresql

server, I'm trying to do some reasonable efforts to configure it correctly. The hard

ware has 128 cores, and I am running a VM with Redhat 9 and Postgresql  16.9.

In postgresql.conf I have:

max_worker_processes = 90               # (change requires restart)

max_parallel_workers_per_gather = 72    # gsh 26 oct 2022

max_parallel_maintenance_workers = 72   # gsh 12 jun 2025

max_parallel_workers =  72              # gsh 12 jun 2025

max_logical_replication_workers = 72    # gsh 12 jun 2025

max_sync_workers_per_subscription = 72   # gsh 12 jun 2025

autovacuum_max_workers = 12             # max number of autovacuum subprocesses

When I do a simple count of a large (large being 1.8 Billion entries), I get

about 10 workers used.

prod_v1_0_0_rc1=# explain (analyze, buffers) select count(*) from gaiadr3.gaia_source;

                                                                                         QUERY PLAN

--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

 Finalize Aggregate  (cost=14379796.81..14379796.82 rows=1 width=8) (actual time=16702.806..16705.479 rows=1 loops=1)

   Buffers: shared hit=2507481

   ->  Gather  (cost=14379795.78..14379796.79 rows=10 width=8) (actual time=16702.513..16705.470 rows=11 loops=1)

         Workers Planned: 10

         Workers Launched: 10

         Buffers: shared hit=2507481

         ->  Partial Aggregate  (cost=14379785.78..14379785.79 rows=1 width=8) (actual time=16691.820..16691.821 rows=1 loops=11)

               Buffers: shared hit=2507481

               ->  Parallel Index Only Scan using gaia_source_nest128 on gaia_source  (cost=0.58..13926632.85 rows=181261171 width=0) (actual time=0.025..9559.644 rows=164700888 loops=11)

                     Heap Fetches: 0

                     Buffers: shared hit=2507481

 Planning:

   Buffers: shared hit=163

 Planning Time: 14.898 ms

 Execution Time: 16705.592 ms

Postgres has chosen to use only a small fraction of the CPU's I have on

my machine. Given the query returns an answer in about 8 seconds, it may be

that Postgresql has allocated the proper number of works. But if I wanted

to try to tweak some config parameters to see if using more workers

would give me an answer faster, I don't seem to see any obvious knobs

to turn. Are there parameters that I can adjust to see if I can increase

throughput? Would adjusting parallel_setup_cost or parallel_tuple_cost

likely to be of help?