[FEA] Build CAGRA Graph with RaBitQ Dataset View
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Nobody has claimed this yet.
feature request
- Dominant language
- Cuda
- Stars
- 854
- Forks
- 236
- Avg merge
- 3d 3h
- Merged PRs (30d)
- 62
Description
With the new Dataset API, we should now be able to create dataset implementations that store additional state, such as correction codes for Lucene's BBQ quantizers.
This feature will allow users to build a CAGRA graph directly from BBQ (or RaBitQ) quantized vectors.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reading the new Dataset API and the existing CAGRA graph-building path. Determine how a dataset view can retain BBQ or RaBitQ correction codes and how quantized vectors should be passed into graph construction. Done means users can build a CAGRA graph directly from BBQ or RaBitQ quantized vectors.
Written by the indexing model from the issue text.
Assessment
- Domain
- machine-learning, search
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100