[Numpy-discussion] How to limit the numpy.memmap's RAM usage?

[David Cournapeau]

2010/10/23 braingateway <braingateway at gmail.com>:
> Hi everyone,
> I noticed the numpy.memmap using RAM to buffer data from memmap files.
> If I get a 100GB array in a memmap file and process it block by block,
> the RAM usage is going to increasing with the process running until
> there is no available space in RAM (4GB), even though the block size is
> only 1MB.
> for example:
> ####
> a = numpy.memmap(‘a.bin’, dtype='float64', mode='r')
> blocklen=1e5
> b=npy.zeros((len(a)/blocklen,))
> for i in range(0,len(a)/blocklen):
> b[i]=npy.mean(a[i*blocklen:(i+1)*blocklen])
> ####
> Is there any way to restrict the memory usage in numpy.memmap?

The whole point of using memmap is to let the OS do the buffering for
you (which is likely to do a better job than you in many cases). Which
OS are you using ? And how do you measure how much memory is taken by
numpy for your array ?

David