What kind of VM is this? What is the host platform? How many CPU cores? Is
VM using all the cores? The only thing I can think of is the GIL and the
fact that multithreaded code in python gets slower and slower the more
cores I have. On my laptop, with two cores, I do not see any slow down.
Rocket preallocate a thread pool. The rationale is that it decreases the
latency time. Perhaps you can also try rocket in this way:
web2py.py --minthreads=1 --maxthreads=1
This will reduce the number of worker threads to 1. Rocket also runs a
background non-worker thread that monitors worker threads and kills them if
they get stuck.
On Sunday, 16 March 2014 20:22:45 UTC-5, horridohobbyist wrote:
>
> Using gunicorn (Thanks, Massimo), I ran the full web2py Welcome code:
>
> Welcome: elapsed time: 0.0511929988861
> Welcome: elapsed time: 0.0024790763855
> Welcome: elapsed time: 0.00262713432312
> Welcome: elapsed time: 0.00224614143372
> Welcome: elapsed time: 0.00218415260315
> Welcome: elapsed time: 0.00213503837585
>
> Oddly enough, it's slightly faster! But still 37% slower than the command
> line execution.
>
> I'd really, really, **really** like to know why the shipping code is 10x
> slower...
>
>
> On Sunday, 16 March 2014 21:13:56 UTC-4, horridohobbyist wrote:
>>
>> Okay, I did the calculations test in my Linux VM using command line
>> (fred0), Flask (hello0), and web2py (Welcome).
>>
>> fred0: elapsed time: 0.00159001350403
>>
>> fred0: elapsed time: 0.0015709400177
>>
>> fred0: elapsed time: 0.00156021118164
>>
>> fred0: elapsed time: 0.0015971660614
>>
>> fred0: elapsed time: 0.00315999984741
>>
>> hello0: elapsed time: 0.00271105766296
>>
>> hello0: elapsed time: 0.00213503837585
>>
>> hello0: elapsed time: 0.00195693969727
>>
>> hello0: elapsed time: 0.00224900245667
>>
>> hello0: elapsed time: 0.00205492973328
>> Welcome: elapsed time: 0.0484869480133
>>
>> Welcome: elapsed time: 0.00296783447266
>>
>> Welcome: elapsed time: 0.00293898582458
>>
>> Welcome: elapsed time: 0.00300216674805
>>
>> Welcome: elapsed time: 0.00312614440918
>>
>> The Welcome discrepancy is just under 2x, not nearly as bad as 10x in my
>> shipping code.
>>
>>
>> On Sunday, 16 March 2014 17:52:00 UTC-4, Massimo Di Pierro wrote:
>>>
>>> In order to isolate the problem one must take it in steps. This is a
>>> good test but you must first perform this test with the code you proposed
>>> before:
>>>
>>> def test():
>>> t = time.time
>>> start = t()
>>> x = 0.0
>>> for i in range(1,5000):
>>> x += (float(i+10)*(i+25)+175.0)/3.14
>>> debug("elapsed time: "+str(t()-start))
>>> return
>>>
>>> I would like to know the results about this test code first.
>>>
>>> The other code you are using performs an import:
>>>
>>> from shippackage import Package
>>>
>>>
>>> Now that is something that is very different in web2py and flask for
>>> example. In web2py the import is executed at every request (although it
>>> should be cached by Python) while in flask it is executed only once. This
>>> should also not cause a performance difference but it is a different test
>>> than the one above.
>>>
>>> TLTR: we should test separately python code execution (which may be
>>> affected by threading) and import statements (which may be affected by
>>> web2py custom_import and/or module weird behavior).
>>>
>>>
>>>
>>> On Sunday, 16 March 2014 08:47:13 UTC-5, horridohobbyist wrote:
>>>>
>>>> I've conducted a test with Flask.
>>>>
>>>> fred.py is the command line program.
>>>> hello.py is the Flask program.
>>>> default.py is the Welcome controller.
>>>> testdata.txt is the test data.
>>>> shippackage.py is a required module.
>>>>
>>>> fred.py:
>>>> 0.024 second
>>>> 0.067 second
>>>>
>>>> hello.py:
>>>> 0.029 second
>>>> 0.073 second
>>>>
>>>> default.py:
>>>> 0.27 second
>>>> 0.78 second
>>>>
>>>> The Flask program is slightly slower than the command line. However,
>>>> the Welcome app is about 10x slower!
>>>>
>>>> *Web2py is much, much slower than Flask.*
>>>>
>>>> I conducted the test in a Parallels VM running Ubuntu Server 12.04 (1GB
>>>> memory allocated). I have a 2.5GHz dual-core Mac mini with 8GB.
>>>>
>>>>
>>>> I can't quite figure out how to use gunicom.
>>>>
>>>>
>>>> On Saturday, 15 March 2014 23:41:49 UTC-4, horridohobbyist wrote:
>>>>>
>>>>> I'll see what I can do. It will take time for me to learn how to use
>>>>> another framework.
>>>>>
>>>>> As for trying a different web server, my (production) Linux server is
>>>>> intimately reliant on Apache. I'd have to learn how to use another web
>>>>> server, and then try it in my Linux VM.
>>>>>
>>>>>
>>>>> On Saturday, 15 March 2014 22:45:27 UTC-4, Anthony wrote:
>>>>>>
>>>>>> Are you able to replicate the exact task in another web framework,
>>>>>> such as Flask (with the same server setup)?
>>>>>>
>>>>>> On Saturday, March 15, 2014 10:34:56 PM UTC-4, horridohobbyist wrote:
>>>>>>>
>>>>>>> Well, putting back all my apps hasn't widened the discrepancy. So I
>>>>>>> don't know why my previous web2py installation was so slow.
>>>>>>>
>>>>>>> While the Welcome app with the calculations test shows a 2x
>>>>>>> discrepancy, the original app that initiated this thread now shows a
>>>>>>> 13x
>>>>>>> discrepancy instead of 100x. That's certainly an improvement, but it's
>>>>>>> still too slow.
>>>>>>>
>>>>>>> The size of the discrepancy depends on the code that is executed.
>>>>>>> Clearly, what I'm doing in the original app (performing permutations)
>>>>>>> is
>>>>>>> more demanding than mere arithmetical operations. Hence, 13x vs 2x.
>>>>>>>
>>>>>>> I anxiously await any resolution to this performance issue, whether
>>>>>>> it be in WSGI or in web2py. I'll check in on this thread periodically...
>>>>>>>
>>>>>>>
>>>>>>> On Saturday, 15 March 2014 16:19:12 UTC-4, horridohobbyist wrote:
>>>>>>>>
>>>>>>>> Interestingly, now that I've got a fresh install of web2py with
>>>>>>>> only the Welcome app, my Welcome vs command line test shows a
>>>>>>>> consistent 2x
>>>>>>>> discrepancy, just as you had observed.
>>>>>>>>
>>>>>>>> My next step is to gradually add back all the other apps I had in
>>>>>>>> web2py (I had 8 of them!) and see whether the discrepancy grows with
>>>>>>>> the
>>>>>>>> number of apps. That's the theory I'm working on.
>>>>>>>>
>>>>>>>> Yes, yes, I know, according to the Book, I shouldn't have so many
>>>>>>>> apps installed in web2py. This apparently affects performance. But the
>>>>>>>> truth is, most of those apps are hardly ever executed, so their
>>>>>>>> existence
>>>>>>>> merely represents a static overhead in web2py. In my mind, this
>>>>>>>> shouldn't
>>>>>>>> widen the discrepancy, but you never know.
>>>>>>>>
>>>>>>>>
>>>>>>>> On Saturday, 15 March 2014 11:19:06 UTC-4, Niphlod wrote:
>>>>>>>>>
>>>>>>>>> @mcm: you got me worried. Your test function was clocking a hell
>>>>>>>>> lower than the original script. But then I found out why; one order
>>>>>>>>> of
>>>>>>>>> magnitude less (5000 vs 50000). Once that was corrected, you got the
>>>>>>>>> exact
>>>>>>>>> same clock times as "my app" (i.e. function directly in the
>>>>>>>>> controller). I
>>>>>>>>> also stripped out the logging part making the app just return the
>>>>>>>>> result
>>>>>>>>> and no visible changes to the timings happened.
>>>>>>>>>
>>>>>>>>> @hh: glad at least we got some grounds to hold on.
>>>>>>>>> @mariano: compiled or not, it doesn't seem to "change" the mean. a
>>>>>>>>> compiled app has just lower variance.
>>>>>>>>>
>>>>>>>>> @all: jlundell definitively hit something. Times are much more
>>>>>>>>> lower when threads are 1.
>>>>>>>>>
>>>>>>>>> BTW: if I change "originalscript.py" to
>>>>>>>>>
>>>>>>>>> # -*- coding: utf-8 -*-
>>>>>>>>> import time
>>>>>>>>> import threading
>>>>>>>>>
>>>>>>>>> def test():
>>>>>>>>> start = time.time()
>>>>>>>>> x = 0.0
>>>>>>>>> for i in range(1,50000):
>>>>>>>>> x += (float(i+10)*(i+25)+175.0)/3.14
>>>>>>>>> res = str(time.time()-start)
>>>>>>>>> print "elapsed time: "+ res + '\n'
>>>>>>>>>
>>>>>>>>> if __name__ == '__main__':
>>>>>>>>> t = threading.Thread(target=test)
>>>>>>>>> t.start()
>>>>>>>>> t.join()
>>>>>>>>>
>>>>>>>>> I'm getting really close timings to "wsgi environment, 1 thread
>>>>>>>>> only" tests, i.e.
>>>>>>>>> 0.23 min, 0.26 max, ~0.24 mean
>>>>>>>>>
>>>>>>>>>
--
Resources:
- http://web2py.com
- http://web2py.com/book (Documentation)
- http://github.com/web2py/web2py (Source code)
- https://code.google.com/p/web2py/issues/list (Report Issues)
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