Re: CUBE_MAX_DIM

The problem with higher dimension cubes is that starting with dimensionality of ~52 the "distance" metrics in 64-bit float have less than a single bit per dimension in mantissa, making cubes indistinguishable. Developers for facial recognition software had a chat about that on russian postgres telegram group https://t.me/pgsql. Their problem was that they had 128-dimensional points, recompiled postgres - distances weren't helpful, and GIST KNN severely degraded to almost full scans. They had to change the number of facial features to smaller in order to make KNN search work.

Floating point overflow isn't that much of a risk per se, worst case scenario it becomes an Infinity or 0 which are usually acceptable in those contexts.

While mathematically possible, there are implementation issues with higher dimension cubes. I'm ok with raising the limit if such nuances get a mention in docs.