As a more complete test I did 3 things...

1) replicated what my function through web2py was doing in a separate 
script and ran that thousands of times on the same server.  This did not 
severely impact memory usage.  

2) set up a web2py function in my controller to simply return a json 
obect.  I am using the protocol: *domain/app/controller/func.json*  No 
processing, just a return statement.  I then ran this script from a 
separate host.  Calling it 1000 times on multiple processors.  The memory 
shot up right away.  

3) reran, from the separate host the same script only this time not 
requesting a json object response.  *domain/app/controller/func*  This also 
made the memory peak to a point of crashing the machine.

is this a leak or do I need to specify some sort of cache for web2py?

On Monday, February 4, 2013 12:19:37 PM UTC-8, pumplerod wrote:
>
> To further elaborate.  I am running my web2py instance on a VPS at 
> dreamhost.com with a memory allocation of 4Gig.  It is running under 
> passenger.
>
>
>
> On Monday, February 4, 2013 12:16:38 PM UTC-8, pumplerod wrote:
>>
>> I had been having critical memory overflow problems and finally saw a 
>> post about a memory leak in the version I was using (2.1.x) so I have 
>> updated to the latest stable version (2.3.2), however I am still seeing my 
>> memory climb until the machine crashes.
>>
>> I'm using web2py as my interface which is accepting data, parsing it, and 
>> then appending to a neo4j database.  I thought, for a while, that neo4j was 
>> the culprit, however, after writing a script to emulate what web2py was 
>> doing and running it on a separate host I saw no memory jump.  It only 
>> happens while running web2py, and only when I'm receiving many hundreds of 
>> requests per min.  There is nothing else running on the machine, other than 
>> system tools.  
>>
>> Within 5min I'm able to watch the memory go from a reasonable 730MB to 
>> over 2500MB.
>>
>> I'm using the default SQLite database and am only making 1 or 2 calls to 
>> the db upon each request.
>>
>> How can I track this down?  Should I be looking for something 
>> specifically in the logs?  Use particular parameters for the logger?
>>
>

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