Fixed matrix rows joining

[bearophile]

If I have a simple fixed-size matrix and I need to linearize (flatten) it, the 
function join() seems to not not work:


import std.array: join;
void main() {
    int[4][4] table;
    join(table);
}


test.d(4): Error: template std.array.join(RoR,R) if (isInputRange!(RoR) && 
isInputRange!(ElementType!(RoR)) && isForwardRange!(R) && 
is(Unqual!(ElementType!(ElementType!(RoR))) == Unqual!(ElementType!(R)))) does 
not match any function template declaration
test.d(4): Error: template std.array.join(RoR,R) if (isInputRange!(RoR) && 
isInputRange!(ElementType!(RoR)) && isForwardRange!(R) && 
is(Unqual!(ElementType!(ElementType!(RoR))) == Unqual!(ElementType!(R)))) 
cannot deduce template function from argument types !()(int[4u][4u])


This too doesn't work:
join(table[]);



This compiles:
join(map!q{ a[] }(table[]));


But this program shows there is something wrong (I know what's wrong), it 
prints:
[6, 4219787, 4, 6, 4219787, 4]


import std.stdio: writeln;
import std.algorithm: map;
import std.array: join;
void main() {
    int[3][2] table = [[1,2,3],[4,5,6]];
    int[] result = join(map!q{ a[] }(table[]));
    writeln(result);
}



This prints the right output, but it allocates lot of memory:
[1, 2, 3, 4, 5, 6]


import std.stdio: writeln;
import std.algorithm: map;
import std.array: join;
void main() {
    int[3][2] table = [[1,2,3],[4,5,6]];
    int[] result2 = join(map!q{ a.dup }(table[]));
    writeln(result2);
}


Do you have better suggestions?
Is the function join() worth fixing/changing to improve this use case?

Bye,
bearophile