Re: Inefficiency in parallel pg_restore with many tables

Pierre Ducroquet <p.psql@pinaraf.info>

From: Pierre Ducroquet <p.psql@pinaraf.info>
To: pgsql-hackers@lists.postgresql.org
Date: 2023-07-24T17:27:36Z
Lists: pgsql-hackers
On Saturday, July 15, 2023 7:47:12 PM CEST Tom Lane wrote:
> I'm not sure how big a deal this is in practice: in most situations
> the individual jobs are larger than they are in this toy example,
> plus the initial non-parallelizable part of the restore is a bigger
> bottleneck anyway with this many tables.  Still, we do have one
> real-world complaint, so maybe we should look into improving it.

Hi

For what it's worth, at my current job it's kind of a big deal. I was going to 
start looking at the bad performance I got on pg_restore for some databases 
with over 50k tables (in 200 namespaces) when I found this thread. The dump 
weights in about 2,8GB, the toc.dat file is 230MB, 50 120 tables, 142 069 
constraints and 73 669 indexes.

HEAD pg_restore duration: 30 minutes
pg_restore with latest patch from Nathan Bossart: 23 minutes

This is indeed better, but there is still a lot of room for improvements. With 
such usecases, I was able to go much faster using the patched pg_restore with 
a script that parallelize on each schema instead of relying on the choices 
made by pg_restore. It seems the choice of parallelizing only the data loading 
is losing nice speedup opportunities with a huge number of objects.

patched pg_restore + parallel restore of schemas: 10 minutes

Anyway, the patch works really fine as is, and I will certainly keep trying 
future iterations.

Regards

 Pierre






Commits

  1. Remove open-coded binary heap in pg_dump_sort.c.

  2. Convert pg_restore's ready_list to a priority queue.

  3. Add function for removing arbitrary nodes in binaryheap.

  4. Make binaryheap available to frontend code.