benwtrent opened a new pull request, #12582:
URL: https://github.com/apache/lucene/pull/12582
As with most codec changes, this is an eye popping number of LoC and the
design isn't finished yet.
I am opening this as draft to be open about the work and to discuss further
direction.
Initial benchmarking (utilizing non-normalized cohere embeddings + max-inner
product, which is a particularly difficult case for naive quantization), I get
10-20% faster search, 2x faster index building, and ~4x smaller storage used
for the search (I am keeping the raw vectors around...we can debate if we want
to do that).
Recall@10 with 100 fanout = 0.804
Recall@100 with 200 fanout = 0.9.
I am reaching the point where the design needs to be finalized and I wanted
to reachout for feedback.
Some design discussion points that I am unsure about are:
- Do we want to have a new "flat" vector codec that HNSW (or other
complicated vector indexing methods), can use? Detractor here is that now HNSW
codec relies on another pluggable thing that is a "flat" vector index (just
provides mechanisms for reading, writing, merging vectors in a flat index).
- Should "quantization" just be a thing that is provided to vector codecs?
The main detractor here is future scalar quantization could easily be added
(like int4 or even binary).
- Should the "quantizer" keep the raw vectors around itself? Or rely on
some external party to provide them (in this case, I an relying on the HNSW
codec)?
Again, this is draft, I have a ton of comments to fix up, etc. But wanted
early feedback and what we want to integrate into Lucene.
As a side note, it really seems some of these classes
(OffHeap...vectorReader...) should be common between all the vector codecs
instead of copied around, its a ton of code that gets copied with almost no
change between codecs :/
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