On 10/07/2011 08:50 PM, Maciej Fijalkowski wrote:
On Fri, Oct 7, 2011 at 1:33 PM, Igor Katson<igor.kat...@gmail.com> wrote:
When I first started benchmarking one of my Django sites,
http://trip-travel.ru/ (using postgres driver pypq),
I was disappointed by the results. PyPy was visually much slower than
cPython (I just looked at how the site loads in the browser)
But today I got some incredible results, I finally made PyPy to work faster
than cPython, and found out that it got faster after loading the page
several hundred times with "ab" or "siege"
Here a the results, of mean response time by querying the home page with
apache's "ab" (cPython 2.7.2, Django 1.3, PyPy 1.6.0), served with cherrypy
wsgi server:
After 10 requests (excluding the first request):
cPython - 163.529 ms
PyPy - 460.879 ms
50 request more:
cPython - 168.539
PyPy - 249.850
100 requests more:
cPython - 166.278 ms
PyPy - 131.104
100 requests more:
cPython - 165.820
PyPy - 115.446
300 requests more:
cPython - 165.543
PyPy - 107.636
300 requests more:
cPython - 166.425
PyPy - 103.065
Thanks for doing the benchmarks :)
As we can see, the JIT needs much time to warm up, but when it does, the
result is pretty noticeable.
By the way, with psycopg2, the site responds for 155.766 ms in average (only
10 ms faster), so using PyPy with Django makes much sense for me.
As for now, pypy cannot run with uWSGI, which I use in production, but maybe
i'll switch to PyPy for production deployments if "PyPy + PyPQ + Some pure
python WSGI server" suite will outperform (uWSGI + cPython + psycopg2).
Though, the need to load the page 500 times after each server reload is not
comfortable.
I've heard people using gunicorn. Maybe this is a good try? Loading
the pages is indeed annoying, but you need to load it a couple times
for results not to be noticably slower :) We kind of know that the JIT
warmup time is high, but it's partly a thing to fix and partly an
inherent property of the JIT.
Tried gunicorn, nothing special, the speed is roughly the same.
Unfortunately, I noticed that a single instance takes way to much memory
to bring that to production, where I pay for the actually used memory. 4
uWSGI workers eat 14 megabytes each, and pypy's memory usage increases,
and after a couple thousands or requests a single worker took 250mb,
more than 15 times more.
_______________________________________________
pypy-dev mailing list
pypy-dev@python.org
http://mail.python.org/mailman/listinfo/pypy-dev
