This implements a common B-tree using rbyd's as inner nodes.
Since our rbyds actually map to sorted arrays, this fits together quite
well.
The main caveat/concern is that we can't rely on strict knowledge on the
on-disk size of these things. This first shows up with B-tree insertion,
we can't split in preparation to insert as we descend down the tree.
Normally, this means our B-tree would require recursion in order to keep
track of each parent as we descend down our tree. However, we can
avoid this by not storing our parent, but by looking it up again on each
step of the splitting operation.
This brute-force-ish approach makes our algorithm tail-recursive, so
bounded RAM, but raises our runtime from O(logB(n)) to O(logB(n)^2)
That being said, O(logB(n)^2) is still sublinear, and, thanks to
B-tree's extremely high branching factor, may be insignificant.
Christopher Haster
1709aec95b