On 04/22/2016 06:47 AM, Robert Haas wrote:
On Fri, Apr 22, 2016 at 9:33 AM, Tom Lane <t...@sss.pgh.pa.us> wrote:
Robert Haas <robertmh...@gmail.com> writes:
On Thu, Apr 21, 2016 at 7:20 PM, Tom Lane <t...@sss.pgh.pa.us> wrote:
Is that because max_worker_processes is only 8 by default?  Maybe we
need to raise that, at least for beta purposes?


I'm not really in favor of that.  I mean, almost all of our default
settings are optimized for running PostgreSQL on, for example, a
Raspberry Pi 2, so it would seem odd to suddenly swing the other
direction and assume that there are more than 8 unused CPU cores.

This is the problem right here.

We should be shipping for a reasonable production configuration. It is not reasonable to assume that someone is going to be running on a Rasberry Pi 2. Yes, we can effectively run on that platform that doesn't mean it should be our default target configuration. Consider that a 5.00/mo Digital Ocean VM is going to outperform a Rasberry Pi.


It is much less likely to be true for parallel workers.  The reason
why those processes aren't contending for the CPU at the same time is
generally that most of the connections are in fact idle.  But a
parallel worker is never idle.  It is launched when it is needed to
run a query and exits immediately afterward.  If it's not contending
for the CPU, it will be contending for I/O bandwidth, or a lock.


True, but isn't that also what context switching and (possibly) hyperthreading are for?


So what I'm concerned about for beta purposes is that we have a setup that
can exercise cases like, say, varying orders in which different workers
return tuples, or potential deadlocks between sibling workers.  We'd get
no coverage of that behavioral space at max_parallel_degree=1.  I'm not
really convinced that we'll get adequate coverage at
max_parallel_degree=2.

The right solution to that is for people who have the right hardware
to raise the settings, not to unleash a ridiculous set of defaults on
everyone.  I really hope that some people do serious destruction
testing of parallel query and try to break it.  For example, you could
use the parallel_degree reloption to force 100 parallel workers to
scan the same relation.   That's likely to be dog slow, but it might
well turn up some bugs.

I think your argument sounds more like a production solution, not a Beta solution. We should be pushing it a little bit in Beta.

JD







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