On Aug 9, 2011, at 11:38 PM, Chris Howden wrote:
Hi,
I’m trying to do a hierarchical cluster analysis in R with a Big
Data set.
I’m running into problems using the dist() function.
I’ve been looking at a few threads about R’s memory and have read the
memory limits section in R help. However I’m no computer expert so I’m
hoping I’ve misunderstood something and R can handle my Big Data set,
somehow. Although at the moment I think my dataset is simply too big
and
there is no way around it, but I’d like to be proved wrong!
My data set has 90523 rows of data and 24 columns.
My understanding is that this means the distance matrix has a min of
90523^2 elements which is 8194413529. Which roughly translates as
8GB of
memory being required (if I assume each entry requires 1 bit). I
only have
4GB on a 32bit build of windows and R. So there is no way that’s
going to
work.
So then I thought of getting access to a more powerful computer, and
maybe
using cloud computing.
However the R memory limit help mentions “On all builds of R, the
maximum
length (number of elements) of a vector is 2^31 - 1 ~ 2*10^9”. Now
as the
distance matrix I require has more elements than this does this mean
it’s
too big for R no matter what I do?
Yes. Vector indexing is done with 4 byte integers.
--
David Winsemius, MD
West Hartford, CT
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