[Feature] Support batched vector index training with sampling ratio#8350
Draft
jerry-024 wants to merge 5 commits into
Draft
[Feature] Support batched vector index training with sampling ratio#8350jerry-024 wants to merge 5 commits into
jerry-024 wants to merge 5 commits into
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Purpose
This PR updates native vector global index building to train through the
VectorIndexTrainer/VectorIndexTrainingAPI instead of materializing all training vectors in one Javafloat[].Main changes:
paimon-vector-index-javato0.2.0-SNAPSHOTfor the separated trainer/training API.train.sample-ratiofor vector index training, with default1.0so the default path still trains with all non-null vectors.<index-type>.train.sample-ratioandfields.<field-name>.train.sample-ratio; field-level configuration takes precedence.train.sample-ratiois less than1.0, sample training vectors evenly from the temporary vector file and feed them to the native trainer in batches, while still adding all vectors to the final index.Tests