[GitHub] [spark] mengxr commented on a change in pull request #27522: [SPARK-30762] Add dtype=float32 support to vector_to_array UDF

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

mengxr commented on a change in pull request #27522: [SPARK-30762] Add dtype=float32 support to vector_to_array UDF
URL: https://github.com/apache/spark/pull/27522#discussion_r378435612
 
 

 ##########
 File path: mllib/src/test/scala/org/apache/spark/ml/FunctionsSuite.scala
 ##########
 @@ -61,5 +59,34 @@ class FunctionsSuite extends MLTest {
         "`org.apache.spark.ml.linalg.Vector` or `org.apache.spark.mllib.linalg.Vector`, " +
         s"but got ${valType}"))
     }
+
+    val df3 = Seq(
+      (Vectors.dense(1.0, 2.0, 3.0), OldVectors.dense(10.0, 20.0, 30.0)),
+      (Vectors.sparse(3, Seq((0, 2.0), (2, 3.0))), OldVectors.sparse(3, Seq((0, 20.0), (2, 30.0))))
+    ).toDF("vec", "oldVec")
+    val df_array_float = df3.select(
 
 Review comment:
   use camelCase in scala. the UDF naming is an exception.

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