On Wed, Jul 8, 2015 at 1:27 PM, Andres Freund <andres@xxxxxxxxxxx> wrote:
On 2015-07-08 13:46:53 -0500, Merlin Moncure wrote:
> On Wed, Jul 8, 2015 at 12:48 PM, Craig James <cjames@xxxxxxxxxxxxxx> wrote:
> > On Tue, Jul 7, 2015 at 10:31 PM, Joshua D. Drake <jd@xxxxxxxxxxxxxxxxx>
> >> Using Apache Fast-CGI, you are going to fork a process for each instance
> >> of the function being executed and that in turn will use all CPUs up to the
> >> max available resource.
> >>
> >> With PostgreSQL, that isn't going to happen unless you are running (at
> >> least) 8 functions across 8 connections.
> >
> >
> > Well, right, which is why I mentioned "even with dozens of clients."
> > Shouldn't that scale to at least all of the CPUs in use if the function is
> > CPU intensive (which it is)?
>
> only in the absence of inter-process locking and cache line bouncing.
And addititionally memory bandwidth (shared between everything, even in
the numa case), cross socket/bus bandwidth (absolutely performance
critical in multi-socket configurations), cache capacity (shared between
cores, and sometimes even sockets!).
From my admittedly naive point of view, it's hard to see why any of this matters. I have functions that do purely CPU-intensive mathematical calculations ... you could imagine something like is_prime(N) that determines if N is a prime number. I have eight clients that connect to eight backends. Each client issues an SQL command like, "select is_prime(N)" where N is a simple number.
Are you saying that in order to calculate is_prime(N), all of that stuff (inter-process locking, memory bandwith, bus bandwidth, cache capacity, etc.) is even relevant? And if so, how is it that Postgres is so different from an Apache fast-CGI program that runs the exact same is_prime(N) calculation?
Just curious ... as I said, I've already implemented a different solution.
Craig
