Sparse matrices in Julia are to my understanding stored as compressed sparse columns. So it is very easy to get the nonzero elements for a given column, but not so easy for rows.
To get the indices of nonzeros rows for column 'c' in sparse matrix M, one can use (at least in the current implementation): M.rowval[a.colptr[col] : M.colptr[col+1]-1] To do the same by rows would be more complicated (a quick-and-dirty solution would of course be to transpose your matrix first). I am however not a Julia expert, so perhaps there's a solution I am not aware of.
