Performance improvement in `SimHashIterator`

The current `SimHashIterator` works by finding the most significant active bit, and then calculating the number of `SimHash` buckets that will exist from that bit to the end of the filter. This means we are iterating `(most_significant_bit / SIM_BUCKET_SIZE) + SIM_BUCKETS` buckets.

The problem here is that in the higher order bits the sparsity is very high, meaning that there will potentially be many buckets where the values we're mixing into our `SimHash`es will just be zeros, and given any value XOR `0` is just that value this is wasted computation.

We could move to use the `BitChunks` iterators which batch up our chunks into a `u64` and an index of that block of bits, skipping ranges full of zeros. This will introduce issues where if our `SimHash` bucket straddles multiple `BitChunks`, which can be solved by peeking the next chunk, making sure that the index is contiguous with our current chunk.

Right now `SIM_BUCKET_SIZE` is always `6` bits but if we allowed fully arbitrary `SimHash` bucket sizes this could get slightly gnarly because we'd need to be able to peek an arbitrary number of `BitChunk`s ahead of the current position.

The following is a line chart plot of the proportion of empty `bit_range`s mixed into the SimHashes using pseudorandomly generated geofilters with `0..100_000` items added to them.

The ratio reduces very sharply after a couple of inserts but remains relatively high since newly added items have some chance of landing in a very significant bucket which introduces a load of zero gaps before the next one bit.

Bắt đầu bằng cách xác định SimHashIterator, BitChunks và SIM_BUCKET_SIZE trong repository, sau đó đọc cách các bucket hiện đang được hình thành. Điều tra cách BitChunks có thể bỏ qua các dải bằng 0 và cách xử lý một bucket trải dài qua nhiều chunk. Được xem là hoàn thành khi giảm được việc trộn các dải rỗng mà không thay đổi kết quả của các bucket SimHash.

Do mô hình lập chỉ mục viết ra từ nội dung của issue.