Hi,
I have a 900,000,000*9,000 matrix where I need to calculate the correlation
between all entries along the smaller dimension, thus creating a 9k*9k
correlation matrix. This matrix is too big to be uploaded in R, and is saved
as a binary file. To access the data in the file I use mmap and some
api-functions (to get all values in one row, one column, or one particular
value). I'm looking for some advice in how to calculate the correlation
matrix. Right now my approach is to do something similar to this (toy code):
corr.matrix<-matrix('numeric',ncol=9000,nrow=9000)
for (i in 1:9000) {
for (j in (i+1):9000) {
# i1=... getting the index of item (i) in a second file
# i2=....getting the index of item (j)
g1=api$getCol(i1)
g2=api$getCol(i2)
cor.matrix[i,j]=cor(g1,g2)
}}
This will work, but will take forever. Any advice for how this can be done
more efficiently? I'm running on a 2.6.18 linux system, with R version
R-2.11.1.
Thanks!
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