Re: [HACKERS] Parallel Hash take II

On Thu, Nov 16, 2017 at 7:35 AM, Andres Freund <andres(at)anarazel(dot)de> wrote:
> On 2017-11-15 08:37:11 -0500, Robert Haas wrote:
>> I mean, the very first version of this patch that Thomas submitted was
>> benchmarked by Rafia and had phenomenally good performance
>> characteristics. That turned out to be because it wasn't respecting
>> work_mem; you can often do a lot better with more memory, and
>> generally you can't do nearly as well with less. To make comparisons
>> meaningful, they have to be comparisons between algorithms that use
>> the same amount of memory. And it's not just about testing. If we
>> add an algorithm that will run twice as fast with equal memory but
>> only allow it half as much, it will probably never get picked and the
>> whole patch is a waste of time.
>
> But this does bug me, and I think it's what made me pause here to make a
> bad joke. The way that parallelism treats work_mem makes it even more
> useless of a config knob than it was before. Parallelism, especially
> after this patch, shouldn't compete / be benchmarked against a
> single-process run with the same work_mem. To make it "fair" you need to
> compare parallelism against a single threaded run with work_mem *
> max_parallelism.
>
> Thomas argues that this makes hashjoins be treated faily vis-a-vi
> parallel-oblivious hash join etc. And I think he has somewhat of a
> point. But I don't think it's quite right either: In several of these
> cases the planner will not prefer the multi-process plan because it uses
> more work_mem, it's a cost to be paid. Whereas this'll optimize towards
> using work_mem * max_parallel_workers_per_gather amount of memory.
>
> This makes it pretty much impossible to afterwards tune work_mem on a
> server in a reasonable manner. Previously you'd tune it to something
> like free_server_memory - (max_connections * work_mem *
> 80%_most_complex_query). Which you can't really do anymore now, you'd
> also need to multiply by max_parallel_workers_per_gather. Which means
> that you might end up "forcing" paralellism on a bunch of plans that'd
> normally execute in too short a time to make parallelism worth it.

Currently our way of choosing the number of workers is 'rule based':
we use a simple formula that takes relation sizes and some GUCs and
per-relation options as inputs. The comparison against non-parallel
plans is cost based of course, but we won't consider any other number
of workers.

Suppose we had 'cost based' worker number selection instead: simply
try planning with various different worker counts and pick the winner.
Then I think we'd see the moral hazard in this scheme more clearly:
the planner effectively has a free memory printing press. It will
think that it's a good idea to use a huge number of workers to get
more and more work_mem-sized hash tables or in-memory sorts into
memory (whether that's with partition-wise join, Parallel Hash, or
something else).

We could switch to a model where work_mem is divided by the number of
workers. Parallel Hash would be able to use a full work_mem by
combining them, and parallel-oblivious Hash would be able to use only
work_mem / participants. That'd be the other way to give Parallel
Hash a fair amount of memory compared to the competition, but I didn't
propose that because it'd be a change to the already-released
behaviour. Then I'd have been saying "hey, look at this new plan I
wrote, it performs really well if you first tie the other plans' shoe
laces together". It may actually be better though, even without
Parallel Hash in the picture.

--
Thomas Munro
http://www.enterprisedb.com