Github user mengxr commented on a diff in the pull request:

    https://github.com/apache/spark/pull/21195#discussion_r185984527
  
    --- Diff: 
mllib/src/test/scala/org/apache/spark/ml/clustering/GaussianMixtureSuite.scala 
---
    @@ -256,6 +258,42 @@ class GaussianMixtureSuite extends SparkFunSuite with 
MLlibTestSparkContext
         val expectedMatrix = GaussianMixture.unpackUpperTriangularMatrix(4, 
triangularValues)
         assert(symmetricMatrix === expectedMatrix)
       }
    +
    +  test("GaussianMixture with Array input") {
    +    val featuresColNameD = "array_double_features"
    +    val featuresColNameF = "array_float_features"
    +    val doubleUDF = udf { (features: Vector) =>
    +      val featureArray = Array.fill[Double](features.size)(0.0)
    +      features.foreachActive((idx, value) => featureArray(idx) = 
value.toFloat)
    +      featureArray
    +    }
    +    val floatUDF = udf { (features: Vector) =>
    +      val featureArray = Array.fill[Float](features.size)(0.0f)
    +      features.foreachActive((idx, value) => featureArray(idx) = 
value.toFloat)
    +      featureArray
    +    }
    +    val newdatasetD = dataset.withColumn(featuresColNameD, 
doubleUDF(col("features")))
    +      .drop("features")
    +    val newdatasetF = dataset.withColumn(featuresColNameF, 
floatUDF(col("features")))
    +      .drop("features")
    +    assert(newdatasetD.schema(featuresColNameD).dataType.equals(new 
ArrayType(DoubleType, false)))
    +    assert(newdatasetF.schema(featuresColNameF).dataType.equals(new 
ArrayType(FloatType, false)))
    +
    +    val gmD = new GaussianMixture().setK(k).setMaxIter(1)
    +      .setFeaturesCol(featuresColNameD).setSeed(1)
    +    val gmF = new GaussianMixture().setK(k).setMaxIter(1)
    +      .setFeaturesCol(featuresColNameF).setSeed(1)
    +    val modelD = gmD.fit(newdatasetD)
    +    val modelF = gmF.fit(newdatasetF)
    +    val transformedD = modelD.transform(newdatasetD)
    +    val transformedF = modelF.transform(newdatasetF)
    +    val predictDifference = transformedD.select("prediction")
    +      .except(transformedF.select("prediction"))
    +    assert(predictDifference.count() == 0)
    +    val probabilityDifference = transformedD.select("probability")
    +      .except(transformedF.select("probability"))
    +    assert(probabilityDifference.count() == 0)
    --- End diff --
    
    ditto


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