How should I count the number of unique rows in a 'binary' matrix?

Question

Suppose I have a matrix whose entries are only 0 and 1, e.g.

set.seed(123)
m <- matrix( sample(0:1, 10, TRUE), nrow=5 )
<         


        

Answer 1

I was curious how a pure R solution would perform:

set.seed(123)
m <- matrix( sample(0:1, 1E5, TRUE), ncol=5 )

rowCountsR <- function(x) {
  ## calculate hash
  h <- m %*% matrix(2^(0:(ncol(x)-1)), ncol=1)
  i <- which(!duplicated(h))
  counts <- tabulate(h+1)
  counts[order(h[i])] <- counts
  list(counts=counts, idx=i)
}

library("rbenchmark")
benchmark(rowCounts(m), rowCountsR(m))
#            test replications elapsed relative user.self sys.self user.child sys.child
# 1  rowCounts(m)          100   0.189    1.000     0.188        0          0         0
# 2 rowCountsR(m)          100   0.258    1.365     0.256        0          0         0

Edit: more columns, thanks @Arun for pointing this out.

set.seed(123)
m <- matrix( sample(0:1, 1e7, TRUE), ncol=10)
benchmark(rowCounts(m), rowCountsR(m), replications=100)
#           test replications elapsed relative user.self sys.self user.child sys.child
#1  rowCounts(m)          100  20.659    1.077    20.533    0.024          0         0
#2 rowCountsR(m)          100  19.183    1.000    15.641    3.408          0         0