[SPARK-59521][ML] Store word vectors directly in Word2VecModel - #58811
Draft
zhengruifeng wants to merge 3 commits into
Draft
zhengruifeng wants to merge 3 commits into
zhengruifeng wants to merge 3 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
1 participant
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Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be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.
What changes were proposed in this pull request?
This PR changes
org.apache.spark.ml.feature.Word2VecModelto store its word index andflattened word vectors directly instead of wrapping an
org.apache.spark.mllib.feature.Word2VecModel.It also moves the synonym-search implementation into the ML
Word2VecModelcompanion object,reuses it from both the ML and MLlib models, and updates model fitting, copying, size estimation,
transformation, and persistence to use the directly stored data.
Why are the changes needed?
The ML model only needs the word index and vector array from the legacy MLlib model.
Storing those values directly removes the unnecessary model wrapper and keeps the ML model's
implementation and synonym-search logic self-contained.
Does this PR introduce any user-facing change?
No.
How was this patch tested?
The following focused suites pass with 17 tests:
Was this patch authored or co-authored using generative AI tooling?
Generated-by: Codex (GPT-5)