How to most efficiently use QR-decomposition in Julia?

Avoiding array allocations is good for performance. However, I have yet to understand what is the most possible efficient way one can perform a QR decomposition of a matrix A. (note: both Q and R matrices are needed)

Simply using Q, R = qr(A) is probably not the best idea, since it allocates both Q and R, where both could be re-allocated.

The function qrfact allows one to store factorization in a packed format. However, I would still write afterwards: F = qrfact(A); Q = F[:Q]; R = F[:R] once again allocating new arrays for Q and R. Finally, the documentation also suggests the qrfact! function, which saves space by overwriting the input A, instead of creating a copy. However, if one uses F = qrfact!(A) the over-written A is not useful in the sense that it is not either Q or R, which one (specifically, I) would need.

So my two questions are:

1. What is the best/most efficient way to perform a QR decomposition if you only care about the matrices Q and R and you have no problem re-allocating them.

2. What is actually written in the matrix A when one calls qrfact!(A) ?