The fastest way to sort the elements in each row of a matrix?

Question

I have a matrix with a couple million rows and about 40 columns.

I want to sort the elements in each row in decreasing order. Thus, the element with the highest value of each row should be in the first column.

To do this I can use the apply function:

set.seed(1)
mm <- replicate(10, rnorm(20)) #random matrix with 20 rows and 10 columns
mm.sorted <- apply(mm,1,sort,decreasing=T)

But for a very large matrix this approach takes a very long time.

Are there different approaches to speed up the sorting of elements in rows?

Answer 1

You could use package data.table:

set.seed(1)
mm <- matrix(rnorm(1000000*40,0,10),ncol=40) 
library(data.table)
system.time({
  d <- as.data.table(mm)
  d[, row := .I]
  d <- melt(d, id.vars = "row") #wide to long format
  setkey(d, row, value) #sort
  d[, variable := paste0("V", ncol(mm):1)] #decreasing order

  #back to wide format and coerce to matrix
  msorted <- as.matrix(dcast(d, row ~ variable)[, row := NULL]) 
})
#user  system elapsed 
#4.96    0.59    5.62 

If you could keep it as a long-format data.table (i.e., skip the last step), it would take about 2 seconds on my machine.

For comparison, timings of @qjgods' answer on my machine:

#user  system elapsed 
#3.71    2.08    8.81

Note that using apply (or parallel versions of it) transposes the matrix.