[WIP][ML] Add vector posexplode function

[zhengruifeng]

What changes were proposed in this pull request?

This PR adds an internal ML-specific vector_posexplode generator expression for MLlib vector
columns.

The new expression explodes org.apache.spark.ml.linalg.VectorUDT and
org.apache.spark.mllib.linalg.VectorUDT columns into (index, value) rows using the shared
four-field VectorUDT SQL representation:

• sparse vectors emit the stored active indices/values pairs
• dense vectors emit all (position, value) pairs

Why are the changes needed?

Spark SQL generator functions such as posexplode only accept arrays and maps. ML vector columns
are UDTs, so users currently need to densify vectors with vector_to_array or manually unwrap the
UDT struct and zip the internal sparse arrays.

This provides Spark ML internals with a direct vector-aware generator that preserves sparse active
elements without densifying first.

Does this PR introduce any user-facing change?

No. The Scala helper is private[ml], and the expression is intended only for Spark ML internals.

How was this patch tested?

Added coverage in FunctionsSuite for both spark.ml and spark.mllib dense and sparse vectors.

build/sbt mllib/Test/compile was started and the new mllib main sources compiled, but the task was
canceled during mllib test compilation so this draft PR could be pushed first.

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

Generated-by: Codex (GPT-5)