Grover's algorithm, M out of N, when M is large The more general version of Grover's algorithm searches for one of $M$ entries that match a criterion, out of $N$ total entries.

I have seen it written that this takes $O(\sqrt{N/M})$ iterations, to find one of the $M$ matching entries, with good probability.
(e.g. on wikipedia )

Is this still valid when $M$ is large, say $M=N/2$ ?  In that case we get $O(1)$ iterations?
When $M=N/2$, you don't need a quantum algorithm; a classical algorithm can find a matching entry in $O(1)$ iterations on average (expected running time), just by randomly guessing an item and checking if it matches.  Grover's algorithm is also randomized, so the quantum computer offers no advantage in asymptotic running time for that case.