zhengruifeng opened a new pull request, #57955: URL: https://github.com/apache/spark/pull/57955
### What changes were proposed in this pull request? Update ML Normalizer to calculate the norm with ML vectors directly. Clone the dense or sparse value array and scale the cloned output with BLAS.scal, while reusing sparse indices. The implementation follows the existing MLlib Normalizer structure. ### Why are the changes needed? ML Normalizer currently converts every input vector from ML to MLlib and converts the normalized result back to ML. Avoiding those conversions reduces allocation and transform overhead. ### Does this PR introduce _any_ user-facing change? No. ### How was this patch tested? The existing NormalizerSuite covers dense, sparse, zero-vector, and parameterized normalization behavior. build/sbt 'mllib/testOnly org.apache.spark.ml.feature.NormalizerSuite' ### Was this patch authored or co-authored using generative AI tooling? Generated-by: Codex (GPT-5) -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
