[SPARK-19953][ML] Random Forest Models use parent UID when being fit

## What changes were proposed in this pull request?

The ML `RandomForestClassificationModel` and `RandomForestRegressionModel` were not using the estimator parent UID when being fit.  This change fixes that so the models can be properly be identified with their parents.

## How was this patch tested?Existing tests.

Added check to verify that model uid matches that of the parent, then renamed `checkCopy` to `checkCopyAndUids` and verified that it was called by one test for each ML algorithm.

Author: Bryan Cutler <cutlerb@gmail.com>

Closes #17296 from BryanCutler/rfmodels-use-parent-uid-SPARK-19953.

41 files changed, 98 insertions, 100 deletions

diff --git a/mllib/src/main/scala/org/apache/spark/ml/classification/RandomForestClassifier.scala b/mllib/src/main/scala/org/apache/spark/ml/classification/RandomForestClassifier.scala
index ce834f1d17..ab4c235209 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/classification/RandomForestClassifier.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/classification/RandomForestClassifier.scala
@@ -140,7 +140,7 @@ class RandomForestClassifier @Since("1.4.0") (
       .map(_.asInstanceOf[DecisionTreeClassificationModel])
 
     val numFeatures = oldDataset.first().features.size
-    val m = new RandomForestClassificationModel(trees, numFeatures, numClasses)
+    val m = new RandomForestClassificationModel(uid, trees, numFeatures, numClasses)
     instr.logSuccess(m)
     m
   }
diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/RandomForestRegressor.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/RandomForestRegressor.scala
index 2f524a8c57..a58da50fad 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/regression/RandomForestRegressor.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/regression/RandomForestRegressor.scala
@@ -131,7 +131,7 @@ class RandomForestRegressor @Since("1.4.0") (@Since("1.4.0") override val uid: S
       .map(_.asInstanceOf[DecisionTreeRegressionModel])
 
     val numFeatures = oldDataset.first().features.size
-    val m = new RandomForestRegressionModel(trees, numFeatures)
+    val m = new RandomForestRegressionModel(uid, trees, numFeatures)
     instr.logSuccess(m)
     m
   }
diff --git a/mllib/src/test/scala/org/apache/spark/ml/PipelineSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/PipelineSuite.scala
index dafc6c200f..4cdbf845ae 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/PipelineSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/PipelineSuite.scala
@@ -79,7 +79,7 @@ class PipelineSuite extends SparkFunSuite with MLlibTestSparkContext with Defaul
       .setStages(Array(estimator0, transformer1, estimator2, transformer3))
     val pipelineModel = pipeline.fit(dataset0)
 
-    MLTestingUtils.checkCopy(pipelineModel)
+    MLTestingUtils.checkCopyAndUids(pipeline, pipelineModel)
 
     assert(pipelineModel.stages.length === 4)
     assert(pipelineModel.stages(0).eq(model0))
diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/DecisionTreeClassifierSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/DecisionTreeClassifierSuite.scala
index 964fcfbdd8..918ab27e27 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/classification/DecisionTreeClassifierSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/classification/DecisionTreeClassifierSuite.scala
@@ -249,8 +249,7 @@ class DecisionTreeClassifierSuite
     val newData: DataFrame = TreeTests.setMetadata(rdd, categoricalFeatures, numClasses)
     val newTree = dt.fit(newData)
 
-    // copied model must have the same parent.
-    MLTestingUtils.checkCopy(newTree)
+    MLTestingUtils.checkCopyAndUids(dt, newTree)
 
     val predictions = newTree.transform(newData)
       .select(newTree.getPredictionCol, newTree.getRawPredictionCol, newTree.getProbabilityCol)
diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/GBTClassifierSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/GBTClassifierSuite.scala
index 0cddb37281..1f79e0d4e6 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/classification/GBTClassifierSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/classification/GBTClassifierSuite.scala
@@ -97,8 +97,7 @@ class GBTClassifierSuite extends SparkFunSuite with MLlibTestSparkContext
     assert(model.getProbabilityCol === "probability")
     assert(model.hasParent)
 
-    // copied model must have the same parent.
-    MLTestingUtils.checkCopy(model)
+    MLTestingUtils.checkCopyAndUids(gbt, model)
   }
 
   test("setThreshold, getThreshold") {
@@ -261,8 +260,7 @@ class GBTClassifierSuite extends SparkFunSuite with MLlibTestSparkContext
       .setSeed(123)
     val model = gbt.fit(df)
 
-    // copied model must have the same parent.
-    MLTestingUtils.checkCopy(model)
+    MLTestingUtils.checkCopyAndUids(gbt, model)
 
     sc.checkpointDir = None
     Utils.deleteRecursively(tempDir)
diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/LinearSVCSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/LinearSVCSuite.scala
index c763a4cef1..2f87afc23f 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/classification/LinearSVCSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/classification/LinearSVCSuite.scala
@@ -124,8 +124,7 @@ class LinearSVCSuite extends SparkFunSuite with MLlibTestSparkContext with Defau
     assert(model.hasParent)
     assert(model.numFeatures === 2)
 
-    // copied model must have the same parent.
-    MLTestingUtils.checkCopy(model)
+    MLTestingUtils.checkCopyAndUids(lsvc, model)
   }
 
   test("linear svc doesn't fit intercept when fitIntercept is off") {
diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala
index f0648d0936..c858b9bbfc 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala
@@ -142,8 +142,7 @@ class LogisticRegressionSuite
     assert(model.intercept !== 0.0)
     assert(model.hasParent)
 
-    // copied model must have the same parent.
-    MLTestingUtils.checkCopy(model)
+    MLTestingUtils.checkCopyAndUids(lr, model)
     assert(model.hasSummary)
     val copiedModel = model.copy(ParamMap.empty)
     assert(copiedModel.hasSummary)
diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/MultilayerPerceptronClassifierSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/MultilayerPerceptronClassifierSuite.scala
index 7700099caa..ce54c3df4f 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/classification/MultilayerPerceptronClassifierSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/classification/MultilayerPerceptronClassifierSuite.scala
@@ -74,8 +74,8 @@ class MultilayerPerceptronClassifierSuite
       .setMaxIter(100)
       .setSolver("l-bfgs")
     val model = trainer.fit(dataset)
-    MLTestingUtils.checkCopy(model)
     val result = model.transform(dataset)
+    MLTestingUtils.checkCopyAndUids(trainer, model)
     val predictionAndLabels = result.select("prediction", "label").collect()
     predictionAndLabels.foreach { case Row(p: Double, l: Double) =>
       assert(p == l)
diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/NaiveBayesSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/NaiveBayesSuite.scala
index d41c5b533d..b56f8e19ca 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/classification/NaiveBayesSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/classification/NaiveBayesSuite.scala
@@ -149,6 +149,7 @@ class NaiveBayesSuite extends SparkFunSuite with MLlibTestSparkContext with Defa
 
     validateModelFit(pi, theta, model)
     assert(model.hasParent)
+    MLTestingUtils.checkCopyAndUids(nb, model)
 
     val validationDataset =
       generateNaiveBayesInput(piArray, thetaArray, nPoints, 17, "multinomial").toDF()
diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/OneVsRestSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/OneVsRestSuite.scala
index aacb7921b8..c02e38ad64 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/classification/OneVsRestSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/classification/OneVsRestSuite.scala
@@ -76,8 +76,7 @@ class OneVsRestSuite extends SparkFunSuite with MLlibTestSparkContext with Defau
     assert(ova.getPredictionCol === "prediction")
     val ovaModel = ova.fit(dataset)
 
-    // copied model must have the same parent.
-    MLTestingUtils.checkCopy(ovaModel)
+    MLTestingUtils.checkCopyAndUids(ova, ovaModel)
 
     assert(ovaModel.models.length === numClasses)
     val transformedDataset = ovaModel.transform(dataset)
diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/RandomForestClassifierSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/RandomForestClassifierSuite.scala
index c3003cec73..ca2954d2f3 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/classification/RandomForestClassifierSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/classification/RandomForestClassifierSuite.scala
@@ -141,8 +141,7 @@ class RandomForestClassifierSuite
     val df: DataFrame = TreeTests.setMetadata(rdd, categoricalFeatures, numClasses)
     val model = rf.fit(df)
 
-    // copied model must have the same parent.
-    MLTestingUtils.checkCopy(model)
+    MLTestingUtils.checkCopyAndUids(rf, model)
 
     val predictions = model.transform(df)
       .select(rf.getPredictionCol, rf.getRawPredictionCol, rf.getProbabilityCol)
diff --git a/mllib/src/test/scala/org/apache/spark/ml/clustering/BisectingKMeansSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/clustering/BisectingKMeansSuite.scala
index 200a892f6c..fa7471fa2d 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/clustering/BisectingKMeansSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/clustering/BisectingKMeansSuite.scala
@@ -47,8 +47,7 @@ class BisectingKMeansSuite
     assert(bkm.getMinDivisibleClusterSize === 1.0)
     val model = bkm.setMaxIter(1).fit(dataset)
 
-    // copied model must have the same parent
-    MLTestingUtils.checkCopy(model)
+    MLTestingUtils.checkCopyAndUids(bkm, model)
     assert(model.hasSummary)
     val copiedModel = model.copy(ParamMap.empty)
     assert(copiedModel.hasSummary)
diff --git a/mllib/src/test/scala/org/apache/spark/ml/clustering/GaussianMixtureSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/clustering/GaussianMixtureSuite.scala
index 61da897b66..08b800b7e4 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/clustering/GaussianMixtureSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/clustering/GaussianMixtureSuite.scala
@@ -77,8 +77,7 @@ class GaussianMixtureSuite extends SparkFunSuite with MLlibTestSparkContext
     assert(gm.getTol === 0.01)
     val model = gm.setMaxIter(1).fit(dataset)
 
-    // copied model must have the same parent
-    MLTestingUtils.checkCopy(model)
+    MLTestingUtils.checkCopyAndUids(gm, model)
     assert(model.hasSummary)
     val copiedModel = model.copy(ParamMap.empty)
     assert(copiedModel.hasSummary)
diff --git a/mllib/src/test/scala/org/apache/spark/ml/clustering/KMeansSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/clustering/KMeansSuite.scala
index ca05b9c389..119fe1dead 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/clustering/KMeansSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/clustering/KMeansSuite.scala
@@ -52,8 +52,7 @@ class KMeansSuite extends SparkFunSuite with MLlibTestSparkContext with DefaultR
     assert(kmeans.getTol === 1e-4)
     val model = kmeans.setMaxIter(1).fit(dataset)
 
-    // copied model must have the same parent
-    MLTestingUtils.checkCopy(model)
+    MLTestingUtils.checkCopyAndUids(kmeans, model)
     assert(model.hasSummary)
     val copiedModel = model.copy(ParamMap.empty)
     assert(copiedModel.hasSummary)
diff --git a/mllib/src/test/scala/org/apache/spark/ml/clustering/LDASuite.scala b/mllib/src/test/scala/org/apache/spark/ml/clustering/LDASuite.scala
index 75aa0be61a..b4fe63a89f 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/clustering/LDASuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/clustering/LDASuite.scala
@@ -176,7 +176,7 @@ class LDASuite extends SparkFunSuite with MLlibTestSparkContext with DefaultRead
     val lda = new LDA().setK(k).setSeed(1).setOptimizer("online").setMaxIter(2)
     val model = lda.fit(dataset)
 
-    MLTestingUtils.checkCopy(model)
+    MLTestingUtils.checkCopyAndUids(lda, model)
 
     assert(model.isInstanceOf[LocalLDAModel])
     assert(model.vocabSize === vocabSize)
@@ -221,7 +221,7 @@ class LDASuite extends SparkFunSuite with MLlibTestSparkContext with DefaultRead
     val lda = new LDA().setK(k).setSeed(1).setOptimizer("em").setMaxIter(2)
     val model_ = lda.fit(dataset)
 
-    MLTestingUtils.checkCopy(model_)
+    MLTestingUtils.checkCopyAndUids(lda, model_)
 
     assert(model_.isInstanceOf[DistributedLDAModel])
     val model = model_.asInstanceOf[DistributedLDAModel]
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/BucketedRandomProjectionLSHSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/BucketedRandomProjectionLSHSuite.scala
index cc81da5c66..7175c721bf 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/BucketedRandomProjectionLSHSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/BucketedRandomProjectionLSHSuite.scala
@@ -94,7 +94,8 @@ class BucketedRandomProjectionLSHSuite
     unitVectors.foreach { v: Vector =>
       assert(Vectors.norm(v, 2.0) ~== 1.0 absTol 1e-14)
     }
-    MLTestingUtils.checkCopy(brpModel)
+
+    MLTestingUtils.checkCopyAndUids(brp, brpModel)
   }
 
   test("BucketedRandomProjectionLSH: test of LSH property") {
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/ChiSqSelectorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/ChiSqSelectorSuite.scala
index d6925da97d..c83909c449 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/ChiSqSelectorSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/ChiSqSelectorSuite.scala
@@ -119,7 +119,8 @@ class ChiSqSelectorSuite extends SparkFunSuite with MLlibTestSparkContext
   test("Test Chi-Square selector: numTopFeatures") {
     val selector = new ChiSqSelector()
       .setOutputCol("filtered").setSelectorType("numTopFeatures").setNumTopFeatures(1)
-    ChiSqSelectorSuite.testSelector(selector, dataset)
+    val model = ChiSqSelectorSuite.testSelector(selector, dataset)
+    MLTestingUtils.checkCopyAndUids(selector, model)
   }
 
   test("Test Chi-Square selector: percentile") {
@@ -166,11 +167,13 @@ class ChiSqSelectorSuite extends SparkFunSuite with MLlibTestSparkContext
 
 object ChiSqSelectorSuite {
 
-  private def testSelector(selector: ChiSqSelector, dataset: Dataset[_]): Unit = {
-    selector.fit(dataset).transform(dataset).select("filtered", "topFeature").collect()
+  private def testSelector(selector: ChiSqSelector, dataset: Dataset[_]): ChiSqSelectorModel = {
+    val selectorModel = selector.fit(dataset)
+    selectorModel.transform(dataset).select("filtered", "topFeature").collect()
       .foreach { case Row(vec1: Vector, vec2: Vector) =>
         assert(vec1 ~== vec2 absTol 1e-1)
       }
+    selectorModel
   }
 
   /**
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/CountVectorizerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/CountVectorizerSuite.scala
index 69d3033bb2..f213145f1b 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/CountVectorizerSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/CountVectorizerSuite.scala
@@ -19,7 +19,7 @@ package org.apache.spark.ml.feature
 import org.apache.spark.SparkFunSuite
 import org.apache.spark.ml.linalg.{Vector, Vectors}
 import org.apache.spark.ml.param.ParamsSuite
-import org.apache.spark.ml.util.DefaultReadWriteTest
+import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils}
 import org.apache.spark.ml.util.TestingUtils._
 import org.apache.spark.mllib.util.MLlibTestSparkContext
 import org.apache.spark.sql.Row
@@ -68,10 +68,11 @@ class CountVectorizerSuite extends SparkFunSuite with MLlibTestSparkContext
     val cv = new CountVectorizer()
       .setInputCol("words")
       .setOutputCol("features")
-      .fit(df)
-    assert(cv.vocabulary.toSet === Set("a", "b", "c", "d", "e"))
+    val cvm = cv.fit(df)
+    MLTestingUtils.checkCopyAndUids(cv, cvm)
+    assert(cvm.vocabulary.toSet === Set("a", "b", "c", "d", "e"))
 
-    cv.transform(df).select("features", "expected").collect().foreach {
+    cvm.transform(df).select("features", "expected").collect().foreach {
       case Row(features: Vector, expected: Vector) =>
         assert(features ~== expected absTol 1e-14)
     }
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/IDFSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/IDFSuite.scala
index 5325d95526..005edf73d2 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/IDFSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/IDFSuite.scala
@@ -20,7 +20,7 @@ package org.apache.spark.ml.feature
 import org.apache.spark.SparkFunSuite
 import org.apache.spark.ml.linalg.{DenseVector, SparseVector, Vector, Vectors}
 import org.apache.spark.ml.param.ParamsSuite
-import org.apache.spark.ml.util.DefaultReadWriteTest
+import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils}
 import org.apache.spark.ml.util.TestingUtils._
 import org.apache.spark.mllib.feature.{IDFModel => OldIDFModel}
 import org.apache.spark.mllib.linalg.VectorImplicits._
@@ -65,10 +65,12 @@ class IDFSuite extends SparkFunSuite with MLlibTestSparkContext with DefaultRead
 
     val df = data.zip(expected).toSeq.toDF("features", "expected")
 
-    val idfModel = new IDF()
+    val idfEst = new IDF()
       .setInputCol("features")
       .setOutputCol("idfValue")
-      .fit(df)
+    val idfModel = idfEst.fit(df)
+
+    MLTestingUtils.checkCopyAndUids(idfEst, idfModel)
 
     idfModel.transform(df).select("idfValue", "expected").collect().foreach {
       case Row(x: Vector, y: Vector) =>
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/LSHTest.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/LSHTest.scala
index a9b559f7ba..dd4dd62b8c 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/LSHTest.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/LSHTest.scala
@@ -18,7 +18,7 @@
 package org.apache.spark.ml.feature
 
 import org.apache.spark.ml.linalg.{Vector, VectorUDT}
-import org.apache.spark.ml.util.SchemaUtils
+import org.apache.spark.ml.util.{MLTestingUtils, SchemaUtils}
 import org.apache.spark.sql.Dataset
 import org.apache.spark.sql.functions._
 import org.apache.spark.sql.types.DataTypes
@@ -58,6 +58,8 @@ private[ml] object LSHTest {
     val outputCol = model.getOutputCol
     val transformedData = model.transform(dataset)
 
+    MLTestingUtils.checkCopyAndUids(lsh, model)
+
     // Check output column type
     SchemaUtils.checkColumnType(
       transformedData.schema, model.getOutputCol, DataTypes.createArrayType(new VectorUDT))
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/MaxAbsScalerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/MaxAbsScalerSuite.scala
index a12174493b..918da4f938 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/MaxAbsScalerSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/MaxAbsScalerSuite.scala
@@ -50,8 +50,7 @@ class MaxAbsScalerSuite extends SparkFunSuite with MLlibTestSparkContext with De
       assert(vector1.equals(vector2), s"MaxAbsScaler ut error: $vector2 should be $vector1")
     }
 
-    // copied model must have the same parent.
-    MLTestingUtils.checkCopy(model)
+    MLTestingUtils.checkCopyAndUids(scaler, model)
   }
 
   test("MaxAbsScaler read/write") {
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/MinHashLSHSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/MinHashLSHSuite.scala
index 0ddf097a6e..96df68dbdf 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/MinHashLSHSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/MinHashLSHSuite.scala
@@ -63,7 +63,7 @@ class MinHashLSHSuite extends SparkFunSuite with MLlibTestSparkContext with Defa
       .setOutputCol("values")
     val model = mh.fit(dataset)
     assert(mh.uid === model.uid)
-    MLTestingUtils.checkCopy(model)
+    MLTestingUtils.checkCopyAndUids(mh, model)
   }
 
   test("hashFunction") {
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/MinMaxScalerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/MinMaxScalerSuite.scala
index b79eeb2d75..51db74eb73 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/MinMaxScalerSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/MinMaxScalerSuite.scala
@@ -53,8 +53,7 @@ class MinMaxScalerSuite extends SparkFunSuite with MLlibTestSparkContext with De
         assert(vector1.equals(vector2), "Transformed vector is different with expected.")
     }
 
-    // copied model must have the same parent.
-    MLTestingUtils.checkCopy(model)
+    MLTestingUtils.checkCopyAndUids(scaler, model)
   }
 
   test("MinMaxScaler arguments max must be larger than min") {
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/PCASuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/PCASuite.scala
index a60e87590f..3067a52a4d 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/PCASuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/PCASuite.scala
@@ -58,12 +58,12 @@ class PCASuite extends SparkFunSuite with MLlibTestSparkContext with DefaultRead
       .setInputCol("features")
       .setOutputCol("pca_features")
       .setK(3)
-      .fit(df)
 
-    // copied model must have the same parent.
-    MLTestingUtils.checkCopy(pca)
+    val pcaModel = pca.fit(df)
 
-    pca.transform(df).select("pca_features", "expected").collect().foreach {
+    MLTestingUtils.checkCopyAndUids(pca, pcaModel)
+
+    pcaModel.transform(df).select("pca_features", "expected").collect().foreach {
       case Row(x: Vector, y: Vector) =>
         assert(x ~== y absTol 1e-5, "Transformed vector is different with expected vector.")
     }
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/RFormulaSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/RFormulaSuite.scala
index 5cfd59e6b8..fbebd75d70 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/RFormulaSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/RFormulaSuite.scala
@@ -37,7 +37,7 @@ class RFormulaSuite extends SparkFunSuite with MLlibTestSparkContext with Defaul
     val formula = new RFormula().setFormula("id ~ v1 + v2")
     val original = Seq((0, 1.0, 3.0), (2, 2.0, 5.0)).toDF("id", "v1", "v2")
     val model = formula.fit(original)
-    MLTestingUtils.checkCopy(model)
+    MLTestingUtils.checkCopyAndUids(formula, model)
     val result = model.transform(original)
     val resultSchema = model.transformSchema(original.schema)
     val expected = Seq(
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/StandardScalerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/StandardScalerSuite.scala
index a928f93633..350ba44baa 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/StandardScalerSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/StandardScalerSuite.scala
@@ -20,7 +20,7 @@ package org.apache.spark.ml.feature
 import org.apache.spark.SparkFunSuite
 import org.apache.spark.ml.linalg.{Vector, Vectors}
 import org.apache.spark.ml.param.ParamsSuite
-import org.apache.spark.ml.util.DefaultReadWriteTest
+import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils}
 import org.apache.spark.ml.util.TestingUtils._
 import org.apache.spark.mllib.util.MLlibTestSparkContext
 import org.apache.spark.sql.{DataFrame, Row}
@@ -77,10 +77,11 @@ class StandardScalerSuite extends SparkFunSuite with MLlibTestSparkContext
   test("Standardization with default parameter") {
     val df0 = data.zip(resWithStd).toSeq.toDF("features", "expected")
 
-    val standardScaler0 = new StandardScaler()
+    val standardScalerEst0 = new StandardScaler()
       .setInputCol("features")
       .setOutputCol("standardized_features")
-      .fit(df0)
+    val standardScaler0 = standardScalerEst0.fit(df0)
+    MLTestingUtils.checkCopyAndUids(standardScalerEst0, standardScaler0)
 
     assertResult(standardScaler0.transform(df0))
   }
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/StringIndexerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/StringIndexerSuite.scala
index 8d9042b31e..5634d4210f 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/StringIndexerSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/StringIndexerSuite.scala
@@ -45,12 +45,11 @@ class StringIndexerSuite
     val indexer = new StringIndexer()
       .setInputCol("label")
       .setOutputCol("labelIndex")
-      .fit(df)
+    val indexerModel = indexer.fit(df)
 
-    // copied model must have the same parent.
-    MLTestingUtils.checkCopy(indexer)
+    MLTestingUtils.checkCopyAndUids(indexer, indexerModel)
 
-    val transformed = indexer.transform(df)
+    val transformed = indexerModel.transform(df)
     val attr = Attribute.fromStructField(transformed.schema("labelIndex"))
       .asInstanceOf[NominalAttribute]
     assert(attr.values.get === Array("a", "c", "b"))
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/VectorIndexerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorIndexerSuite.scala
index b28ce2ab45..f2cca8aa82 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/VectorIndexerSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorIndexerSuite.scala
@@ -114,8 +114,7 @@ class VectorIndexerSuite extends SparkFunSuite with MLlibTestSparkContext
     val vectorIndexer = getIndexer
     val model = vectorIndexer.fit(densePoints1) // vectors of length 3
 
-    // copied model must have the same parent.
-    MLTestingUtils.checkCopy(model)
+    MLTestingUtils.checkCopyAndUids(vectorIndexer, model)
 
     model.transform(densePoints1) // should work
     model.transform(sparsePoints1) // should work
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/Word2VecSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/Word2VecSuite.scala
index 2043a16c15..a6a1c2b4f3 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/Word2VecSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/Word2VecSuite.scala
@@ -57,15 +57,14 @@ class Word2VecSuite extends SparkFunSuite with MLlibTestSparkContext with Defaul
 
     val docDF = doc.zip(expected).toDF("text", "expected")
 
-    val model = new Word2Vec()
+    val w2v = new Word2Vec()
       .setVectorSize(3)
       .setInputCol("text")
       .setOutputCol("result")
       .setSeed(42L)
-      .fit(docDF)
+    val model = w2v.fit(docDF)
 
-    // copied model must have the same parent.
-    MLTestingUtils.checkCopy(model)
+    MLTestingUtils.checkCopyAndUids(w2v, model)
 
     // These expectations are just magic values, characterizing the current
     // behavior.  The test needs to be updated to be more general, see SPARK-11502
diff --git a/mllib/src/test/scala/org/apache/spark/ml/fpm/FPGrowthSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/fpm/FPGrowthSuite.scala
index 6bec057511..6806cb03bc 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/fpm/FPGrowthSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/fpm/FPGrowthSuite.scala
@@ -17,9 +17,10 @@
 package org.apache.spark.ml.fpm
 
 import org.apache.spark.SparkFunSuite
+import org.apache.spark.ml.param.ParamsSuite
 import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils}
 import org.apache.spark.mllib.util.MLlibTestSparkContext
-import org.apache.spark.sql.{DataFrame, Dataset, Row, SparkSession}
+import org.apache.spark.sql.{DataFrame, Dataset, SparkSession}
 import org.apache.spark.sql.functions._
 import org.apache.spark.sql.types._
 
@@ -121,7 +122,9 @@ class FPGrowthSuite extends SparkFunSuite with MLlibTestSparkContext with Defaul
       .setMinConfidence(0.5678)
     assert(fpGrowth.getMinSupport === 0.4567)
     assert(model.getMinConfidence === 0.5678)
-    MLTestingUtils.checkCopy(model)
+    MLTestingUtils.checkCopyAndUids(fpGrowth, model)
+    ParamsSuite.checkParams(fpGrowth)
+    ParamsSuite.checkParams(model)
   }
 
   test("read/write") {
diff --git a/mllib/src/test/scala/org/apache/spark/ml/recommendation/ALSSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/recommendation/ALSSuite.scala
index a177ed13bf..7574af3d77 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/recommendation/ALSSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/recommendation/ALSSuite.scala
@@ -409,8 +409,7 @@ class ALSSuite
     logInfo(s"Test RMSE is $rmse.")
     assert(rmse < targetRMSE)
 
-    // copied model must have the same parent.
-    MLTestingUtils.checkCopy(model)
+    MLTestingUtils.checkCopyAndUids(als, model)
   }
 
   test("exact rank-1 matrix") {
diff --git a/mllib/src/test/scala/org/apache/spark/ml/regression/AFTSurvivalRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/regression/AFTSurvivalRegressionSuite.scala
index 708185a094..fb39e50a83 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/regression/AFTSurvivalRegressionSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/regression/AFTSurvivalRegressionSuite.scala
@@ -83,8 +83,7 @@ class AFTSurvivalRegressionSuite
       .setQuantilesCol("quantiles")
       .fit(datasetUnivariate)
 
-    // copied model must have the same parent.
-    MLTestingUtils.checkCopy(model)
+    MLTestingUtils.checkCopyAndUids(aftr, model)
 
     model.transform(datasetUnivariate)
       .select("label", "prediction", "quantiles")
diff --git a/mllib/src/test/scala/org/apache/spark/ml/regression/DecisionTreeRegressorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/regression/DecisionTreeRegressorSuite.scala
index 0e91284d03..642f266891 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/regression/DecisionTreeRegressorSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/regression/DecisionTreeRegressorSuite.scala
@@ -69,11 +69,12 @@ class DecisionTreeRegressorSuite
   test("copied model must have the same parent") {
     val categoricalFeatures = Map(0 -> 2, 1 -> 2)
     val df = TreeTests.setMetadata(categoricalDataPointsRDD, categoricalFeatures, numClasses = 0)
-    val model = new DecisionTreeRegressor()
+    val dtr = new DecisionTreeRegressor()
       .setImpurity("variance")
       .setMaxDepth(2)
-      .setMaxBins(8).fit(df)
-    MLTestingUtils.checkCopy(model)
+      .setMaxBins(8)
+    val model = dtr.fit(df)
+    MLTestingUtils.checkCopyAndUids(dtr, model)
   }
 
   test("predictVariance") {
diff --git a/mllib/src/test/scala/org/apache/spark/ml/regression/GBTRegressorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/regression/GBTRegressorSuite.scala
index 03c2f97797..2da25f7e01 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/regression/GBTRegressorSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/regression/GBTRegressorSuite.scala
@@ -90,8 +90,7 @@ class GBTRegressorSuite extends SparkFunSuite with MLlibTestSparkContext
       .setMaxIter(2)
     val model = gbt.fit(df)
 
-    // copied model must have the same parent.
-    MLTestingUtils.checkCopy(model)
+    MLTestingUtils.checkCopyAndUids(gbt, model)
     val preds = model.transform(df)
     val predictions = preds.select("prediction").rdd.map(_.getDouble(0))
     // Checks based on SPARK-8736 (to ensure it is not doing classification)
diff --git a/mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala
index 401911763f..f7c7c001a3 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala
@@ -197,8 +197,7 @@ class GeneralizedLinearRegressionSuite
     val model = glr.setFamily("gaussian").setLink("identity")
       .fit(datasetGaussianIdentity)
 
-    // copied model must have the same parent.
-    MLTestingUtils.checkCopy(model)
+    MLTestingUtils.checkCopyAndUids(glr, model)
     assert(model.hasSummary)
     val copiedModel = model.copy(ParamMap.empty)
     assert(copiedModel.hasSummary)
diff --git a/mllib/src/test/scala/org/apache/spark/ml/regression/IsotonicRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/regression/IsotonicRegressionSuite.scala
index f41a3601b1..180f5f7ce5 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/regression/IsotonicRegressionSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/regression/IsotonicRegressionSuite.scala
@@ -93,8 +93,7 @@ class IsotonicRegressionSuite
 
     val model = ir.fit(dataset)
 
-    // copied model must have the same parent.
-    MLTestingUtils.checkCopy(model)
+    MLTestingUtils.checkCopyAndUids(ir, model)
 
     model.transform(dataset)
       .select("label", "features", "prediction", "weight")
diff --git a/mllib/src/test/scala/org/apache/spark/ml/regression/LinearRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/regression/LinearRegressionSuite.scala
index c6a267b728..e7bd4eb9e0 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/regression/LinearRegressionSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/regression/LinearRegressionSuite.scala
@@ -148,8 +148,7 @@ class LinearRegressionSuite
     assert(lir.getSolver == "auto")
     val model = lir.fit(datasetWithDenseFeature)
 
-    // copied model must have the same parent.
-    MLTestingUtils.checkCopy(model)
+    MLTestingUtils.checkCopyAndUids(lir, model)
     assert(model.hasSummary)
     val copiedModel = model.copy(ParamMap.empty)
     assert(copiedModel.hasSummary)
diff --git a/mllib/src/test/scala/org/apache/spark/ml/regression/RandomForestRegressorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/regression/RandomForestRegressorSuite.scala
index 3bf0445ebd..8b8e8a655f 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/regression/RandomForestRegressorSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/regression/RandomForestRegressorSuite.scala
@@ -90,6 +90,8 @@ class RandomForestRegressorSuite extends SparkFunSuite with MLlibTestSparkContex
 
     val model = rf.fit(df)
 
+    MLTestingUtils.checkCopyAndUids(rf, model)
+
     val importances = model.featureImportances
     val mostImportantFeature = importances.argmax
     assert(mostImportantFeature === 1)
diff --git a/mllib/src/test/scala/org/apache/spark/ml/tuning/CrossValidatorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/tuning/CrossValidatorSuite.scala
index 7116265474..2b4e6b53e4 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/tuning/CrossValidatorSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/tuning/CrossValidatorSuite.scala
@@ -58,8 +58,7 @@ class CrossValidatorSuite
       .setNumFolds(3)
     val cvModel = cv.fit(dataset)
 
-    // copied model must have the same paren.
-    MLTestingUtils.checkCopy(cvModel)
+    MLTestingUtils.checkCopyAndUids(cv, cvModel)
 
     val parent = cvModel.bestModel.parent.asInstanceOf[LogisticRegression]
     assert(parent.getRegParam === 0.001)
diff --git a/mllib/src/test/scala/org/apache/spark/ml/tuning/TrainValidationSplitSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/tuning/TrainValidationSplitSuite.scala
index 4463a9b6e5..a34f930aa1 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/tuning/TrainValidationSplitSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/tuning/TrainValidationSplitSuite.scala
@@ -45,18 +45,18 @@ class TrainValidationSplitSuite
       .addGrid(lr.maxIter, Array(0, 10))
       .build()
     val eval = new BinaryClassificationEvaluator
-    val cv = new TrainValidationSplit()
+    val tvs = new TrainValidationSplit()
       .setEstimator(lr)
       .setEstimatorParamMaps(lrParamMaps)
       .setEvaluator(eval)
       .setTrainRatio(0.5)
       .setSeed(42L)
-    val cvModel = cv.fit(dataset)
-    val parent = cvModel.bestModel.parent.asInstanceOf[LogisticRegression]
-    assert(cv.getTrainRatio === 0.5)
+    val tvsModel = tvs.fit(dataset)
+    val parent = tvsModel.bestModel.parent.asInstanceOf[LogisticRegression]
+    assert(tvs.getTrainRatio === 0.5)
     assert(parent.getRegParam === 0.001)
     assert(parent.getMaxIter === 10)
-    assert(cvModel.validationMetrics.length === lrParamMaps.length)
+    assert(tvsModel.validationMetrics.length === lrParamMaps.length)
   }
 
   test("train validation with linear regression") {
@@ -71,28 +71,27 @@ class TrainValidationSplitSuite
       .addGrid(trainer.maxIter, Array(0, 10))
       .build()
     val eval = new RegressionEvaluator()
-    val cv = new TrainValidationSplit()
+    val tvs = new TrainValidationSplit()
       .setEstimator(trainer)
       .setEstimatorParamMaps(lrParamMaps)
       .setEvaluator(eval)
       .setTrainRatio(0.5)
       .setSeed(42L)
-    val cvModel = cv.fit(dataset)
+    val tvsModel = tvs.fit(dataset)
 
-    // copied model must have the same paren.
-    MLTestingUtils.checkCopy(cvModel)
+    MLTestingUtils.checkCopyAndUids(tvs, tvsModel)
 
-    val parent = cvModel.bestModel.parent.asInstanceOf[LinearRegression]
+    val parent = tvsModel.bestModel.parent.asInstanceOf[LinearRegression]
     assert(parent.getRegParam === 0.001)
     assert(parent.getMaxIter === 10)
-    assert(cvModel.validationMetrics.length === lrParamMaps.length)
+    assert(tvsModel.validationMetrics.length === lrParamMaps.length)
 
       eval.setMetricName("r2")
-    val cvModel2 = cv.fit(dataset)
-    val parent2 = cvModel2.bestModel.parent.asInstanceOf[LinearRegression]
+    val tvsModel2 = tvs.fit(dataset)
+    val parent2 = tvsModel2.bestModel.parent.asInstanceOf[LinearRegression]
     assert(parent2.getRegParam === 0.001)
     assert(parent2.getMaxIter === 10)
-    assert(cvModel2.validationMetrics.length === lrParamMaps.length)
+    assert(tvsModel2.validationMetrics.length === lrParamMaps.length)
   }
 
   test("transformSchema should check estimatorParamMaps") {
@@ -104,17 +103,17 @@ class TrainValidationSplitSuite
       .addGrid(est.inputCol, Array("input1", "input2"))
       .build()
 
-    val cv = new TrainValidationSplit()
+    val tvs = new TrainValidationSplit()
       .setEstimator(est)
       .setEstimatorParamMaps(paramMaps)
       .setEvaluator(eval)
       .setTrainRatio(0.5)
-    cv.transformSchema(new StructType()) // This should pass.
+    tvs.transformSchema(new StructType()) // This should pass.
 
     val invalidParamMaps = paramMaps :+ ParamMap(est.inputCol -> "")
-    cv.setEstimatorParamMaps(invalidParamMaps)
+    tvs.setEstimatorParamMaps(invalidParamMaps)
     intercept[IllegalArgumentException] {
-      cv.transformSchema(new StructType())
+      tvs.transformSchema(new StructType())
     }
   }
 
diff --git a/mllib/src/test/scala/org/apache/spark/ml/util/MLTestingUtils.scala b/mllib/src/test/scala/org/apache/spark/ml/util/MLTestingUtils.scala
index 578f31c8e7..bef79e634f 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/util/MLTestingUtils.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/util/MLTestingUtils.scala
@@ -31,11 +31,15 @@ import org.apache.spark.sql.functions._
 import org.apache.spark.sql.types._
 
 object MLTestingUtils extends SparkFunSuite {
-  def checkCopy(model: Model[_]): Unit = {
+
+  def checkCopyAndUids[T <: Estimator[_]](estimator: T, model: Model[_]): Unit = {
+    assert(estimator.uid === model.uid, "Model uid does not match parent estimator")
+
+    // copied model must have the same parent
     val copied = model.copy(ParamMap.empty)
       .asInstanceOf[Model[_]]
-    assert(copied.parent.uid == model.parent.uid)
     assert(copied.parent == model.parent)
+    assert(copied.parent.uid == model.parent.uid)
   }
 
   def checkNumericTypes[M <: Model[M], T <: Estimator[M]](