[GitHub] [spark] WeichenXu123 opened a new pull request #26910: [SPARK-30154][ML] PySpark UDF to convert MLlib vectors to dense arrays

[GitBox <gi...@apache.org>]

WeichenXu123 opened a new pull request #26910: [SPARK-30154][ML] PySpark UDF to convert MLlib vectors to dense arrays
URL: https://github.com/apache/spark/pull/26910
 
 
   ### What changes were proposed in this pull request?
   
   PySpark UDF to convert MLlib vectors to dense arrays.
   Example:
   ```
   from pyspark.ml.functions import vector_to_dense_array
   df.select(vector_to_dense_array(col("features"))
   ```
   
   ### Why are the changes needed?
   If a PySpark user wants to convert MLlib sparse/dense vectors in a DataFrame into dense arrays, an efficient approach is to do that in JVM. However, it requires PySpark user to write Scala code and register it as a UDF. Often this is infeasible for a pure python project.
   
   ### Does this PR introduce any user-facing change?
   No.
   
   ### How was this patch tested?
   UT.
   

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