I have a very large binary matrix, stored as a big.matrix to conserve
memory (it is over 2 gb otherwise - 5 million columns and 100 rows).
r <- 100
c <- 10000
m4 <- matrix(sample(0:1,r*c, replace=TRUE),r,c)
m4 <- cbind(m4, 1)
m4 <- as.big.matrix(m4)
I need to remove every column which has only one unique value (in this
case, only 0s or only 1s). Because of the number of columns, I want to be
able to do this in parallel.
How can I accomplish this while keeping the data compressed as a
big.matrix? I can convert it into a df and loop over the columns looking
for the number of unique values, but this takes too much RAM.
Thanks!
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