Big thank you to all the people that worked on it!
BTW has anyone tried a probabilistic dedup approach using soemthing like a bloom filter so you don't have to store the entire dedup table of hashes verbatim? Collect groups of ~100 block hashes into a bucket each, and store a hyper compressed representation in a bloom filter. On write, lookup the hash of the block to write in the bloom filter, and if a potential dedup hit is detected, walk the 100 blocks in the matching bucket manually to look for any identical hashes. In theory you could do this with layers of bloom filters with different resolutions and dynamically swap out the heavier ones to disk when memory pressure is too high to keep the high resolution ones in RAM. Allowing the accuracy of the bloom filter to be changed as a tunable parameter would let people choose their preference around CPU time/overhead:bytes saved ratio.