[SPARK-58964][ML] Consolidate vector and matrix UDT column conversion

[zhengruifeng]

What changes were proposed in this pull request?

This PR consolidates UDT column selection in these MLUtils conversion helpers:

• MLUtils.convertVectorColumnsToML
• MLUtils.convertVectorColumnsFromML
• MLUtils.convertMatrixColumnsToML
• MLUtils.convertMatrixColumnsFromML

When columns are not explicitly specified, each helper preserves the previous automatic selection
behavior: ToML helpers select only old mllib UDT columns, and FromML helpers select only new
ml UDT columns. For explicit columns, the helpers validate that the named columns exist and rely
on the existing wrap_udt(unwrap_udt(...)) expression analysis to reject non-UDT inputs.
Converted columns are replaced with the metadata-preserving withColumns overload instead of
rebuilding the whole projection manually.

Why are the changes needed?

After vector and matrix conversion moved to wrap_udt / unwrap_udt, the explicit-column paths no
longer need separate source-type and target-type branches when deciding whether a column can be
converted.

Does this PR introduce any user-facing change?

No.

How was this patch tested?

Ran:

JAVA_HOME=/usr/lib/jvm/java-17-openjdk-amd64 build/sbt 'mllib/testOnly org.apache.spark.mllib.util.MLUtilsSuite -- -z "convertVectorColumnsToML" -z "convertVectorColumnsFromML" -z "convert nullable vector columns" -z "convertMatrixColumnsToML" -z "convertMatrixColumnsFromML" -z "convert nullable matrix columns"'

Also ran:

• git diff --check
• line-length scan for the changed Scala files
• non-ASCII scan for the changed Scala files

Was this patch authored or co-authored using generative AI tooling?

Generated-by: OpenAI Codex