[SPARK-14615][ML] Use the new ML Vector and Matrix in the ML pipeline based algorithms

## What changes were proposed in this pull request?

Once SPARK-14487 and SPARK-14549 are merged, we will migrate to use the new vector and matrix type in the new ml pipeline based apis.

## How was this patch tested?

Unit tests

Author: DB Tsai <dbt@netflix.com>
Author: Liang-Chi Hsieh <simonh@tw.ibm.com>
Author: Xiangrui Meng <meng@databricks.com>

Closes #12627 from dbtsai/SPARK-14615-NewML.

85 files changed, 513 insertions, 213 deletions

diff --git a/mllib/src/test/java/org/apache/spark/ml/JavaPipelineSuite.java b/mllib/src/test/java/org/apache/spark/ml/JavaPipelineSuite.java
index e0c4363597..46c26e8b92 100644
--- a/mllib/src/test/java/org/apache/spark/ml/JavaPipelineSuite.java
+++ b/mllib/src/test/java/org/apache/spark/ml/JavaPipelineSuite.java
@@ -24,12 +24,12 @@ import org.junit.Test;
 import org.apache.spark.api.java.JavaRDD;
 import org.apache.spark.api.java.JavaSparkContext;
 import org.apache.spark.ml.classification.LogisticRegression;
+import static org.apache.spark.ml.classification.LogisticRegressionSuite.generateLogisticInputAsList;
+import org.apache.spark.ml.feature.LabeledPoint;
 import org.apache.spark.ml.feature.StandardScaler;
-import org.apache.spark.mllib.regression.LabeledPoint;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.SparkSession;
-import static org.apache.spark.mllib.classification.LogisticRegressionSuite.generateLogisticInputAsList;
 
 /**
  * Test Pipeline construction and fitting in Java.
diff --git a/mllib/src/test/java/org/apache/spark/ml/classification/JavaDecisionTreeClassifierSuite.java b/mllib/src/test/java/org/apache/spark/ml/classification/JavaDecisionTreeClassifierSuite.java
index 8b89991327..c76a1947c6 100644
--- a/mllib/src/test/java/org/apache/spark/ml/classification/JavaDecisionTreeClassifierSuite.java
+++ b/mllib/src/test/java/org/apache/spark/ml/classification/JavaDecisionTreeClassifierSuite.java
@@ -27,9 +27,9 @@ import org.junit.Test;
 
 import org.apache.spark.api.java.JavaRDD;
 import org.apache.spark.api.java.JavaSparkContext;
+import org.apache.spark.ml.classification.LogisticRegressionSuite;
+import org.apache.spark.ml.feature.LabeledPoint;
 import org.apache.spark.ml.tree.impl.TreeTests;
-import org.apache.spark.mllib.classification.LogisticRegressionSuite;
-import org.apache.spark.mllib.regression.LabeledPoint;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.SparkSession;
diff --git a/mllib/src/test/java/org/apache/spark/ml/classification/JavaGBTClassifierSuite.java b/mllib/src/test/java/org/apache/spark/ml/classification/JavaGBTClassifierSuite.java
index 682371eb9e..4648926c34 100644
--- a/mllib/src/test/java/org/apache/spark/ml/classification/JavaGBTClassifierSuite.java
+++ b/mllib/src/test/java/org/apache/spark/ml/classification/JavaGBTClassifierSuite.java
@@ -27,9 +27,9 @@ import org.junit.Test;
 
 import org.apache.spark.api.java.JavaRDD;
 import org.apache.spark.api.java.JavaSparkContext;
+import org.apache.spark.ml.classification.LogisticRegressionSuite;
+import org.apache.spark.ml.feature.LabeledPoint;
 import org.apache.spark.ml.tree.impl.TreeTests;
-import org.apache.spark.mllib.classification.LogisticRegressionSuite;
-import org.apache.spark.mllib.regression.LabeledPoint;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.SparkSession;
diff --git a/mllib/src/test/java/org/apache/spark/ml/classification/JavaLogisticRegressionSuite.java b/mllib/src/test/java/org/apache/spark/ml/classification/JavaLogisticRegressionSuite.java
index e3ff68364e..98abca221c 100644
--- a/mllib/src/test/java/org/apache/spark/ml/classification/JavaLogisticRegressionSuite.java
+++ b/mllib/src/test/java/org/apache/spark/ml/classification/JavaLogisticRegressionSuite.java
@@ -27,12 +27,12 @@ import org.junit.Test;
 
 import org.apache.spark.api.java.JavaRDD;
 import org.apache.spark.api.java.JavaSparkContext;
-import org.apache.spark.mllib.linalg.Vector;
-import org.apache.spark.mllib.regression.LabeledPoint;
+import static org.apache.spark.ml.classification.LogisticRegressionSuite.generateLogisticInputAsList;
+import org.apache.spark.ml.feature.LabeledPoint;
+import org.apache.spark.ml.linalg.Vector;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.SparkSession;
-import static org.apache.spark.mllib.classification.LogisticRegressionSuite.generateLogisticInputAsList;
 
 public class JavaLogisticRegressionSuite implements Serializable {
 
diff --git a/mllib/src/test/java/org/apache/spark/ml/classification/JavaMultilayerPerceptronClassifierSuite.java b/mllib/src/test/java/org/apache/spark/ml/classification/JavaMultilayerPerceptronClassifierSuite.java
index b0624cea3e..48edbc838c 100644
--- a/mllib/src/test/java/org/apache/spark/ml/classification/JavaMultilayerPerceptronClassifierSuite.java
+++ b/mllib/src/test/java/org/apache/spark/ml/classification/JavaMultilayerPerceptronClassifierSuite.java
@@ -26,8 +26,8 @@ import org.junit.Assert;
 import org.junit.Before;
 import org.junit.Test;
 
-import org.apache.spark.mllib.linalg.Vectors;
-import org.apache.spark.mllib.regression.LabeledPoint;
+import org.apache.spark.ml.feature.LabeledPoint;
+import org.apache.spark.ml.linalg.Vectors;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.SparkSession;
diff --git a/mllib/src/test/java/org/apache/spark/ml/classification/JavaNaiveBayesSuite.java b/mllib/src/test/java/org/apache/spark/ml/classification/JavaNaiveBayesSuite.java
index 3fc3648627..787909821b 100644
--- a/mllib/src/test/java/org/apache/spark/ml/classification/JavaNaiveBayesSuite.java
+++ b/mllib/src/test/java/org/apache/spark/ml/classification/JavaNaiveBayesSuite.java
@@ -26,8 +26,8 @@ import org.junit.Before;
 import org.junit.Test;
 import static org.junit.Assert.assertEquals;
 
-import org.apache.spark.mllib.linalg.VectorUDT;
-import org.apache.spark.mllib.linalg.Vectors;
+import org.apache.spark.ml.linalg.VectorUDT;
+import org.apache.spark.ml.linalg.Vectors;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.RowFactory;
diff --git a/mllib/src/test/java/org/apache/spark/ml/classification/JavaOneVsRestSuite.java b/mllib/src/test/java/org/apache/spark/ml/classification/JavaOneVsRestSuite.java
index 486fbbd58c..58bc5a448a 100644
--- a/mllib/src/test/java/org/apache/spark/ml/classification/JavaOneVsRestSuite.java
+++ b/mllib/src/test/java/org/apache/spark/ml/classification/JavaOneVsRestSuite.java
@@ -29,11 +29,11 @@ import org.junit.Test;
 
 import org.apache.spark.api.java.JavaRDD;
 import org.apache.spark.api.java.JavaSparkContext;
-import org.apache.spark.mllib.regression.LabeledPoint;
+import static org.apache.spark.ml.classification.LogisticRegressionSuite.generateMultinomialLogisticInput;
+import org.apache.spark.ml.feature.LabeledPoint;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.SparkSession;
-import static org.apache.spark.mllib.classification.LogisticRegressionSuite.generateMultinomialLogisticInput;
 
 public class JavaOneVsRestSuite implements Serializable {
 
diff --git a/mllib/src/test/java/org/apache/spark/ml/classification/JavaRandomForestClassifierSuite.java b/mllib/src/test/java/org/apache/spark/ml/classification/JavaRandomForestClassifierSuite.java
index e3855662fb..1ed20b1bfa 100644
--- a/mllib/src/test/java/org/apache/spark/ml/classification/JavaRandomForestClassifierSuite.java
+++ b/mllib/src/test/java/org/apache/spark/ml/classification/JavaRandomForestClassifierSuite.java
@@ -28,10 +28,10 @@ import org.junit.Test;
 
 import org.apache.spark.api.java.JavaRDD;
 import org.apache.spark.api.java.JavaSparkContext;
+import org.apache.spark.ml.classification.LogisticRegressionSuite;
+import org.apache.spark.ml.feature.LabeledPoint;
+import org.apache.spark.ml.linalg.Vector;
 import org.apache.spark.ml.tree.impl.TreeTests;
-import org.apache.spark.mllib.classification.LogisticRegressionSuite;
-import org.apache.spark.mllib.linalg.Vector;
-import org.apache.spark.mllib.regression.LabeledPoint;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.SparkSession;
diff --git a/mllib/src/test/java/org/apache/spark/ml/clustering/JavaKMeansSuite.java b/mllib/src/test/java/org/apache/spark/ml/clustering/JavaKMeansSuite.java
index 3ab09ac27d..9d07170fa1 100644
--- a/mllib/src/test/java/org/apache/spark/ml/clustering/JavaKMeansSuite.java
+++ b/mllib/src/test/java/org/apache/spark/ml/clustering/JavaKMeansSuite.java
@@ -28,7 +28,7 @@ import org.junit.After;
 import org.junit.Before;
 import org.junit.Test;
 
-import org.apache.spark.mllib.linalg.Vector;
+import org.apache.spark.ml.linalg.Vector;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.SparkSession;
diff --git a/mllib/src/test/java/org/apache/spark/ml/feature/JavaDCTSuite.java b/mllib/src/test/java/org/apache/spark/ml/feature/JavaDCTSuite.java
index 06482d8f0d..9d8c09b30c 100644
--- a/mllib/src/test/java/org/apache/spark/ml/feature/JavaDCTSuite.java
+++ b/mllib/src/test/java/org/apache/spark/ml/feature/JavaDCTSuite.java
@@ -27,9 +27,9 @@ import org.junit.Assert;
 import org.junit.Before;
 import org.junit.Test;
 
-import org.apache.spark.mllib.linalg.Vector;
-import org.apache.spark.mllib.linalg.VectorUDT;
-import org.apache.spark.mllib.linalg.Vectors;
+import org.apache.spark.ml.linalg.Vector;
+import org.apache.spark.ml.linalg.VectorUDT;
+import org.apache.spark.ml.linalg.Vectors;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.RowFactory;
diff --git a/mllib/src/test/java/org/apache/spark/ml/feature/JavaHashingTFSuite.java b/mllib/src/test/java/org/apache/spark/ml/feature/JavaHashingTFSuite.java
index 0e21d4a94f..3c37441a77 100644
--- a/mllib/src/test/java/org/apache/spark/ml/feature/JavaHashingTFSuite.java
+++ b/mllib/src/test/java/org/apache/spark/ml/feature/JavaHashingTFSuite.java
@@ -25,7 +25,7 @@ import org.junit.Assert;
 import org.junit.Before;
 import org.junit.Test;
 
-import org.apache.spark.mllib.linalg.Vector;
+import org.apache.spark.ml.linalg.Vector;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.RowFactory;
diff --git a/mllib/src/test/java/org/apache/spark/ml/feature/JavaNormalizerSuite.java b/mllib/src/test/java/org/apache/spark/ml/feature/JavaNormalizerSuite.java
index 04b2897b18..b3e213a497 100644
--- a/mllib/src/test/java/org/apache/spark/ml/feature/JavaNormalizerSuite.java
+++ b/mllib/src/test/java/org/apache/spark/ml/feature/JavaNormalizerSuite.java
@@ -25,7 +25,7 @@ import org.junit.Test;
 
 import org.apache.spark.api.java.JavaRDD;
 import org.apache.spark.api.java.JavaSparkContext;
-import org.apache.spark.mllib.linalg.Vectors;
+import org.apache.spark.ml.linalg.Vectors;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.SparkSession;
diff --git a/mllib/src/test/java/org/apache/spark/ml/feature/JavaPCASuite.java b/mllib/src/test/java/org/apache/spark/ml/feature/JavaPCASuite.java
index 32f6b4375e..a4bce2283b 100644
--- a/mllib/src/test/java/org/apache/spark/ml/feature/JavaPCASuite.java
+++ b/mllib/src/test/java/org/apache/spark/ml/feature/JavaPCASuite.java
@@ -31,9 +31,9 @@ import org.junit.Test;
 import org.apache.spark.api.java.JavaRDD;
 import org.apache.spark.api.java.JavaSparkContext;
 import org.apache.spark.api.java.function.Function;
+import org.apache.spark.ml.linalg.Vector;
+import org.apache.spark.ml.linalg.Vectors;
 import org.apache.spark.mllib.linalg.Matrix;
-import org.apache.spark.mllib.linalg.Vector;
-import org.apache.spark.mllib.linalg.Vectors;
 import org.apache.spark.mllib.linalg.distributed.RowMatrix;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
@@ -88,9 +88,25 @@ public class JavaPCASuite implements Serializable {
     );
     JavaRDD<Vector> dataRDD = jsc.parallelize(points, 2);
 
-    RowMatrix mat = new RowMatrix(dataRDD.rdd());
+    RowMatrix mat = new RowMatrix(dataRDD.map(
+            new Function<Vector, org.apache.spark.mllib.linalg.Vector>() {
+              public org.apache.spark.mllib.linalg.Vector call(Vector vector) {
+                return new org.apache.spark.mllib.linalg.DenseVector(vector.toArray());
+              }
+            }
+    ).rdd());
+    
     Matrix pc = mat.computePrincipalComponents(3);
-    JavaRDD<Vector> expected = mat.multiply(pc).rows().toJavaRDD();
+
+    mat.multiply(pc).rows().toJavaRDD();
+
+    JavaRDD<Vector> expected = mat.multiply(pc).rows().toJavaRDD().map(
+      new Function<org.apache.spark.mllib.linalg.Vector, Vector>() {
+        public Vector call(org.apache.spark.mllib.linalg.Vector vector) {
+          return vector.asML();
+        }
+      }
+    );
 
     JavaRDD<VectorPair> featuresExpected = dataRDD.zip(expected).map(
       new Function<Tuple2<Vector, Vector>, VectorPair>() {
diff --git a/mllib/src/test/java/org/apache/spark/ml/feature/JavaPolynomialExpansionSuite.java b/mllib/src/test/java/org/apache/spark/ml/feature/JavaPolynomialExpansionSuite.java
index 8f726077a2..a28f73f10a 100644
--- a/mllib/src/test/java/org/apache/spark/ml/feature/JavaPolynomialExpansionSuite.java
+++ b/mllib/src/test/java/org/apache/spark/ml/feature/JavaPolynomialExpansionSuite.java
@@ -26,9 +26,9 @@ import org.junit.Before;
 import org.junit.Test;
 
 import org.apache.spark.api.java.JavaSparkContext;
-import org.apache.spark.mllib.linalg.Vector;
-import org.apache.spark.mllib.linalg.VectorUDT;
-import org.apache.spark.mllib.linalg.Vectors;
+import org.apache.spark.ml.linalg.Vector;
+import org.apache.spark.ml.linalg.VectorUDT;
+import org.apache.spark.ml.linalg.Vectors;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.RowFactory;
diff --git a/mllib/src/test/java/org/apache/spark/ml/feature/JavaStandardScalerSuite.java b/mllib/src/test/java/org/apache/spark/ml/feature/JavaStandardScalerSuite.java
index c7397bdd68..8415fdb84f 100644
--- a/mllib/src/test/java/org/apache/spark/ml/feature/JavaStandardScalerSuite.java
+++ b/mllib/src/test/java/org/apache/spark/ml/feature/JavaStandardScalerSuite.java
@@ -25,7 +25,7 @@ import org.junit.Before;
 import org.junit.Test;
 
 import org.apache.spark.api.java.JavaSparkContext;
-import org.apache.spark.mllib.linalg.Vectors;
+import org.apache.spark.ml.linalg.Vectors;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.SparkSession;
diff --git a/mllib/src/test/java/org/apache/spark/ml/feature/JavaVectorAssemblerSuite.java b/mllib/src/test/java/org/apache/spark/ml/feature/JavaVectorAssemblerSuite.java
index 8774cd0c69..fedaa77176 100644
--- a/mllib/src/test/java/org/apache/spark/ml/feature/JavaVectorAssemblerSuite.java
+++ b/mllib/src/test/java/org/apache/spark/ml/feature/JavaVectorAssemblerSuite.java
@@ -25,9 +25,9 @@ import org.junit.Before;
 import org.junit.Test;
 
 import org.apache.spark.SparkConf;
-import org.apache.spark.mllib.linalg.Vector;
-import org.apache.spark.mllib.linalg.VectorUDT;
-import org.apache.spark.mllib.linalg.Vectors;
+import org.apache.spark.ml.linalg.Vector;
+import org.apache.spark.ml.linalg.VectorUDT;
+import org.apache.spark.ml.linalg.Vectors;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.RowFactory;
diff --git a/mllib/src/test/java/org/apache/spark/ml/feature/JavaVectorIndexerSuite.java b/mllib/src/test/java/org/apache/spark/ml/feature/JavaVectorIndexerSuite.java
index c386c9a45b..a8dd44608d 100644
--- a/mllib/src/test/java/org/apache/spark/ml/feature/JavaVectorIndexerSuite.java
+++ b/mllib/src/test/java/org/apache/spark/ml/feature/JavaVectorIndexerSuite.java
@@ -29,7 +29,7 @@ import org.junit.Test;
 
 import org.apache.spark.api.java.JavaSparkContext;
 import org.apache.spark.ml.feature.VectorIndexerSuite.FeatureData;
-import org.apache.spark.mllib.linalg.Vectors;
+import org.apache.spark.ml.linalg.Vectors;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.SparkSession;
diff --git a/mllib/src/test/java/org/apache/spark/ml/feature/JavaVectorSlicerSuite.java b/mllib/src/test/java/org/apache/spark/ml/feature/JavaVectorSlicerSuite.java
index 59ad3c2f61..a565c77af4 100644
--- a/mllib/src/test/java/org/apache/spark/ml/feature/JavaVectorSlicerSuite.java
+++ b/mllib/src/test/java/org/apache/spark/ml/feature/JavaVectorSlicerSuite.java
@@ -28,8 +28,8 @@ import org.junit.Test;
 import org.apache.spark.ml.attribute.Attribute;
 import org.apache.spark.ml.attribute.AttributeGroup;
 import org.apache.spark.ml.attribute.NumericAttribute;
-import org.apache.spark.mllib.linalg.Vector;
-import org.apache.spark.mllib.linalg.Vectors;
+import org.apache.spark.ml.linalg.Vector;
+import org.apache.spark.ml.linalg.Vectors;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.RowFactory;
diff --git a/mllib/src/test/java/org/apache/spark/ml/feature/JavaWord2VecSuite.java b/mllib/src/test/java/org/apache/spark/ml/feature/JavaWord2VecSuite.java
index 392aabc96d..bef7eb0f99 100644
--- a/mllib/src/test/java/org/apache/spark/ml/feature/JavaWord2VecSuite.java
+++ b/mllib/src/test/java/org/apache/spark/ml/feature/JavaWord2VecSuite.java
@@ -24,7 +24,7 @@ import org.junit.Assert;
 import org.junit.Before;
 import org.junit.Test;
 
-import org.apache.spark.mllib.linalg.Vector;
+import org.apache.spark.ml.linalg.Vector;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.RowFactory;
diff --git a/mllib/src/test/java/org/apache/spark/ml/regression/JavaDecisionTreeRegressorSuite.java b/mllib/src/test/java/org/apache/spark/ml/regression/JavaDecisionTreeRegressorSuite.java
index bbd59a04ec..4ea3f2255e 100644
--- a/mllib/src/test/java/org/apache/spark/ml/regression/JavaDecisionTreeRegressorSuite.java
+++ b/mllib/src/test/java/org/apache/spark/ml/regression/JavaDecisionTreeRegressorSuite.java
@@ -27,9 +27,9 @@ import org.junit.Test;
 
 import org.apache.spark.api.java.JavaRDD;
 import org.apache.spark.api.java.JavaSparkContext;
+import org.apache.spark.ml.classification.LogisticRegressionSuite;
+import org.apache.spark.ml.feature.LabeledPoint;
 import org.apache.spark.ml.tree.impl.TreeTests;
-import org.apache.spark.mllib.classification.LogisticRegressionSuite;
-import org.apache.spark.mllib.regression.LabeledPoint;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.SparkSession;
diff --git a/mllib/src/test/java/org/apache/spark/ml/regression/JavaGBTRegressorSuite.java b/mllib/src/test/java/org/apache/spark/ml/regression/JavaGBTRegressorSuite.java
index 5370b58e8f..3b5edf1e15 100644
--- a/mllib/src/test/java/org/apache/spark/ml/regression/JavaGBTRegressorSuite.java
+++ b/mllib/src/test/java/org/apache/spark/ml/regression/JavaGBTRegressorSuite.java
@@ -27,9 +27,9 @@ import org.junit.Test;
 
 import org.apache.spark.api.java.JavaRDD;
 import org.apache.spark.api.java.JavaSparkContext;
+import org.apache.spark.ml.classification.LogisticRegressionSuite;
+import org.apache.spark.ml.feature.LabeledPoint;
 import org.apache.spark.ml.tree.impl.TreeTests;
-import org.apache.spark.mllib.classification.LogisticRegressionSuite;
-import org.apache.spark.mllib.regression.LabeledPoint;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.SparkSession;
diff --git a/mllib/src/test/java/org/apache/spark/ml/regression/JavaLinearRegressionSuite.java b/mllib/src/test/java/org/apache/spark/ml/regression/JavaLinearRegressionSuite.java
index 00c59f08b6..d3ef5f6fca 100644
--- a/mllib/src/test/java/org/apache/spark/ml/regression/JavaLinearRegressionSuite.java
+++ b/mllib/src/test/java/org/apache/spark/ml/regression/JavaLinearRegressionSuite.java
@@ -27,11 +27,11 @@ import static org.junit.Assert.assertEquals;
 
 import org.apache.spark.api.java.JavaRDD;
 import org.apache.spark.api.java.JavaSparkContext;
-import org.apache.spark.mllib.regression.LabeledPoint;
+import static org.apache.spark.ml.classification.LogisticRegressionSuite.generateLogisticInputAsList;
+import org.apache.spark.ml.feature.LabeledPoint;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.SparkSession;
-import static org.apache.spark.mllib.classification.LogisticRegressionSuite.generateLogisticInputAsList;
 
 public class JavaLinearRegressionSuite implements Serializable {
 
diff --git a/mllib/src/test/java/org/apache/spark/ml/regression/JavaRandomForestRegressorSuite.java b/mllib/src/test/java/org/apache/spark/ml/regression/JavaRandomForestRegressorSuite.java
index fdb41ffc10..d601e7c540 100644
--- a/mllib/src/test/java/org/apache/spark/ml/regression/JavaRandomForestRegressorSuite.java
+++ b/mllib/src/test/java/org/apache/spark/ml/regression/JavaRandomForestRegressorSuite.java
@@ -28,10 +28,10 @@ import org.junit.Test;
 
 import org.apache.spark.api.java.JavaRDD;
 import org.apache.spark.api.java.JavaSparkContext;
+import org.apache.spark.ml.classification.LogisticRegressionSuite;
+import org.apache.spark.ml.feature.LabeledPoint;
+import org.apache.spark.ml.linalg.Vector;
 import org.apache.spark.ml.tree.impl.TreeTests;
-import org.apache.spark.mllib.classification.LogisticRegressionSuite;
-import org.apache.spark.mllib.linalg.Vector;
-import org.apache.spark.mllib.regression.LabeledPoint;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.SparkSession;
diff --git a/mllib/src/test/java/org/apache/spark/ml/source/libsvm/JavaLibSVMRelationSuite.java b/mllib/src/test/java/org/apache/spark/ml/source/libsvm/JavaLibSVMRelationSuite.java
index 058f2ddafd..022dcf94bd 100644
--- a/mllib/src/test/java/org/apache/spark/ml/source/libsvm/JavaLibSVMRelationSuite.java
+++ b/mllib/src/test/java/org/apache/spark/ml/source/libsvm/JavaLibSVMRelationSuite.java
@@ -28,8 +28,8 @@ import org.junit.Assert;
 import org.junit.Before;
 import org.junit.Test;
 
-import org.apache.spark.mllib.linalg.DenseVector;
-import org.apache.spark.mllib.linalg.Vectors;
+import org.apache.spark.ml.linalg.DenseVector;
+import org.apache.spark.ml.linalg.Vectors;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.SparkSession;
diff --git a/mllib/src/test/java/org/apache/spark/ml/tuning/JavaCrossValidatorSuite.java b/mllib/src/test/java/org/apache/spark/ml/tuning/JavaCrossValidatorSuite.java
index 8b4d034ffe..b874ccd48b 100644
--- a/mllib/src/test/java/org/apache/spark/ml/tuning/JavaCrossValidatorSuite.java
+++ b/mllib/src/test/java/org/apache/spark/ml/tuning/JavaCrossValidatorSuite.java
@@ -27,13 +27,13 @@ import org.junit.Test;
 
 import org.apache.spark.api.java.JavaSparkContext;
 import org.apache.spark.ml.classification.LogisticRegression;
+import static org.apache.spark.ml.classification.LogisticRegressionSuite.generateLogisticInputAsList;
+import org.apache.spark.ml.feature.LabeledPoint;
 import org.apache.spark.ml.evaluation.BinaryClassificationEvaluator;
 import org.apache.spark.ml.param.ParamMap;
-import org.apache.spark.mllib.regression.LabeledPoint;
 import org.apache.spark.sql.Dataset;
 import org.apache.spark.sql.Row;
 import org.apache.spark.sql.SparkSession;
-import static org.apache.spark.mllib.classification.LogisticRegressionSuite.generateLogisticInputAsList;
 
 public class JavaCrossValidatorSuite implements Serializable {
 
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 55448325e4..3b490cdf56 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/PipelineSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/PipelineSuite.scala
@@ -27,9 +27,9 @@ import org.scalatest.mock.MockitoSugar.mock
 import org.apache.spark.SparkFunSuite
 import org.apache.spark.ml.Pipeline.SharedReadWrite
 import org.apache.spark.ml.feature.{HashingTF, MinMaxScaler}
-import org.apache.spark.ml.param.{IntParam, ParamMap, ParamPair}
+import org.apache.spark.ml.linalg.Vectors
+import org.apache.spark.ml.param.{IntParam, ParamMap}
 import org.apache.spark.ml.util._
-import org.apache.spark.mllib.linalg.Vectors
 import org.apache.spark.mllib.util.MLlibTestSparkContext
 import org.apache.spark.sql.{DataFrame, Dataset}
 import org.apache.spark.sql.types.StructType
diff --git a/mllib/src/test/scala/org/apache/spark/ml/ann/ANNSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/ann/ANNSuite.scala
index dc91fc5f9e..35586320cb 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/ann/ANNSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/ann/ANNSuite.scala
@@ -18,10 +18,9 @@
 package org.apache.spark.ml.ann
 
 import org.apache.spark.SparkFunSuite
-import org.apache.spark.mllib.linalg.Vectors
+import org.apache.spark.ml.linalg.Vectors
+import org.apache.spark.ml.util.TestingUtils._
 import org.apache.spark.mllib.util.MLlibTestSparkContext
-import org.apache.spark.mllib.util.TestingUtils._
-
 
 class ANNSuite extends SparkFunSuite with MLlibTestSparkContext {
 
diff --git a/mllib/src/test/scala/org/apache/spark/ml/ann/GradientSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/ann/GradientSuite.scala
index 04cc426c40..f0c0183323 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/ann/GradientSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/ann/GradientSuite.scala
@@ -20,7 +20,7 @@ package org.apache.spark.ml.ann
 import breeze.linalg.{DenseMatrix => BDM}
 
 import org.apache.spark.SparkFunSuite
-import org.apache.spark.mllib.linalg.Vectors
+import org.apache.spark.ml.linalg.Vectors
 import org.apache.spark.mllib.util.MLlibTestSparkContext
 
 class GradientSuite extends SparkFunSuite with MLlibTestSparkContext {
diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/ClassifierSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/ClassifierSuite.scala
index 98116656ba..4db5f03fb0 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/classification/ClassifierSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/classification/ClassifierSuite.scala
@@ -19,10 +19,10 @@ package org.apache.spark.ml.classification
 
 import org.apache.spark.{SparkException, SparkFunSuite}
 import org.apache.spark.ml.classification.ClassifierSuite.MockClassifier
+import org.apache.spark.ml.feature.LabeledPoint
+import org.apache.spark.ml.linalg.{Vector, Vectors}
 import org.apache.spark.ml.param.ParamMap
 import org.apache.spark.ml.util.Identifiable
-import org.apache.spark.mllib.linalg.{Vector, Vectors}
-import org.apache.spark.mllib.regression.LabeledPoint
 import org.apache.spark.mllib.util.MLlibTestSparkContext
 import org.apache.spark.rdd.RDD
 import org.apache.spark.sql.{DataFrame, Dataset}
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 91a947f44b..089d30abb5 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
@@ -18,12 +18,13 @@
 package org.apache.spark.ml.classification
 
 import org.apache.spark.SparkFunSuite
+import org.apache.spark.ml.feature.LabeledPoint
+import org.apache.spark.ml.linalg.{Vector, Vectors}
 import org.apache.spark.ml.param.ParamsSuite
 import org.apache.spark.ml.tree.{CategoricalSplit, InternalNode, LeafNode}
 import org.apache.spark.ml.tree.impl.TreeTests
 import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils}
-import org.apache.spark.mllib.linalg.{Vector, Vectors}
-import org.apache.spark.mllib.regression.LabeledPoint
+import org.apache.spark.mllib.regression.{LabeledPoint => OldLabeledPoint}
 import org.apache.spark.mllib.tree.{DecisionTree => OldDecisionTree, DecisionTreeSuite => OldDecisionTreeSuite}
 import org.apache.spark.mllib.util.MLlibTestSparkContext
 import org.apache.spark.rdd.RDD
@@ -44,17 +45,18 @@ class DecisionTreeClassifierSuite
   override def beforeAll() {
     super.beforeAll()
     categoricalDataPointsRDD =
-      sc.parallelize(OldDecisionTreeSuite.generateCategoricalDataPoints())
+      sc.parallelize(OldDecisionTreeSuite.generateCategoricalDataPoints()).map(_.asML)
     orderedLabeledPointsWithLabel0RDD =
-      sc.parallelize(OldDecisionTreeSuite.generateOrderedLabeledPointsWithLabel0())
+      sc.parallelize(OldDecisionTreeSuite.generateOrderedLabeledPointsWithLabel0()).map(_.asML)
     orderedLabeledPointsWithLabel1RDD =
-      sc.parallelize(OldDecisionTreeSuite.generateOrderedLabeledPointsWithLabel1())
+      sc.parallelize(OldDecisionTreeSuite.generateOrderedLabeledPointsWithLabel1()).map(_.asML)
     categoricalDataPointsForMulticlassRDD =
-      sc.parallelize(OldDecisionTreeSuite.generateCategoricalDataPointsForMulticlass())
+      sc.parallelize(OldDecisionTreeSuite.generateCategoricalDataPointsForMulticlass()).map(_.asML)
     continuousDataPointsForMulticlassRDD =
-      sc.parallelize(OldDecisionTreeSuite.generateContinuousDataPointsForMulticlass())
+      sc.parallelize(OldDecisionTreeSuite.generateContinuousDataPointsForMulticlass()).map(_.asML)
     categoricalDataPointsForMulticlassForOrderedFeaturesRDD = sc.parallelize(
       OldDecisionTreeSuite.generateCategoricalDataPointsForMulticlassForOrderedFeatures())
+      .map(_.asML)
   }
 
   test("params") {
@@ -395,7 +397,7 @@ private[ml] object DecisionTreeClassifierSuite extends SparkFunSuite {
       numClasses: Int): Unit = {
     val numFeatures = data.first().features.size
     val oldStrategy = dt.getOldStrategy(categoricalFeatures, numClasses)
-    val oldTree = OldDecisionTree.train(data, oldStrategy)
+    val oldTree = OldDecisionTree.train(data.map(OldLabeledPoint.fromML), oldStrategy)
     val newData: DataFrame = TreeTests.setMetadata(data, categoricalFeatures, numClasses)
     val newTree = dt.fit(newData)
     // Use parent from newTree since this is not checked anyways.
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 5a5e5c15fc..8d588ccfd3 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
@@ -18,13 +18,14 @@
 package org.apache.spark.ml.classification
 
 import org.apache.spark.{SparkException, SparkFunSuite}
+import org.apache.spark.ml.feature.LabeledPoint
+import org.apache.spark.ml.linalg.Vectors
 import org.apache.spark.ml.param.ParamsSuite
 import org.apache.spark.ml.regression.DecisionTreeRegressionModel
 import org.apache.spark.ml.tree.LeafNode
 import org.apache.spark.ml.tree.impl.TreeTests
 import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils}
-import org.apache.spark.mllib.linalg.Vectors
-import org.apache.spark.mllib.regression.LabeledPoint
+import org.apache.spark.mllib.regression.{LabeledPoint => OldLabeledPoint}
 import org.apache.spark.mllib.tree.{EnsembleTestHelper, GradientBoostedTrees => OldGBT}
 import org.apache.spark.mllib.tree.configuration.{Algo => OldAlgo}
 import org.apache.spark.mllib.util.MLlibTestSparkContext
@@ -51,10 +52,13 @@ class GBTClassifierSuite extends SparkFunSuite with MLlibTestSparkContext
   override def beforeAll() {
     super.beforeAll()
     data = sc.parallelize(EnsembleTestHelper.generateOrderedLabeledPoints(numFeatures = 10, 100), 2)
+      .map(_.asML)
     trainData =
       sc.parallelize(EnsembleTestHelper.generateOrderedLabeledPoints(numFeatures = 20, 120), 2)
+        .map(_.asML)
     validationData =
       sc.parallelize(EnsembleTestHelper.generateOrderedLabeledPoints(numFeatures = 20, 80), 2)
+        .map(_.asML)
   }
 
   test("params") {
@@ -229,7 +233,7 @@ private object GBTClassifierSuite extends SparkFunSuite {
     val oldBoostingStrategy =
       gbt.getOldBoostingStrategy(categoricalFeatures, OldAlgo.Classification)
     val oldGBT = new OldGBT(oldBoostingStrategy, gbt.getSeed.toInt)
-    val oldModel = oldGBT.run(data)
+    val oldModel = oldGBT.run(data.map(OldLabeledPoint.fromML))
     val newData: DataFrame = TreeTests.setMetadata(data, categoricalFeatures, numClasses = 2)
     val newModel = gbt.fit(newData)
     // Use parent from newTree since this is not checked anyways.
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 69650ebb36..a1b48539c4 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
@@ -17,18 +17,19 @@
 
 package org.apache.spark.ml.classification
 
+import scala.collection.JavaConverters._
 import scala.language.existentials
 import scala.util.Random
+import scala.util.control.Breaks._
 
 import org.apache.spark.SparkFunSuite
-import org.apache.spark.ml.feature.Instance
+import org.apache.spark.ml.classification.LogisticRegressionSuite._
+import org.apache.spark.ml.feature.{Instance, LabeledPoint}
+import org.apache.spark.ml.linalg.{Vector, Vectors}
 import org.apache.spark.ml.param.ParamsSuite
 import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils}
-import org.apache.spark.mllib.classification.LogisticRegressionSuite._
-import org.apache.spark.mllib.linalg.{Vector, Vectors}
-import org.apache.spark.mllib.regression.LabeledPoint
+import org.apache.spark.ml.util.TestingUtils._
 import org.apache.spark.mllib.util.MLlibTestSparkContext
-import org.apache.spark.mllib.util.TestingUtils._
 import org.apache.spark.sql.{DataFrame, Dataset, Row}
 import org.apache.spark.sql.functions.lit
 
@@ -967,4 +968,122 @@ object LogisticRegressionSuite {
     "standardization" -> false,
     "threshold" -> 0.6
   )
+
+  def generateLogisticInputAsList(
+    offset: Double,
+    scale: Double,
+    nPoints: Int,
+    seed: Int): java.util.List[LabeledPoint] = {
+    generateLogisticInput(offset, scale, nPoints, seed).asJava
+  }
+
+  // Generate input of the form Y = logistic(offset + scale*X)
+  def generateLogisticInput(
+      offset: Double,
+      scale: Double,
+      nPoints: Int,
+      seed: Int): Seq[LabeledPoint] = {
+    val rnd = new Random(seed)
+    val x1 = Array.fill[Double](nPoints)(rnd.nextGaussian())
+
+    val y = (0 until nPoints).map { i =>
+      val p = 1.0 / (1.0 + math.exp(-(offset + scale * x1(i))))
+      if (rnd.nextDouble() < p) 1.0 else 0.0
+    }
+
+    val testData = (0 until nPoints).map(i => LabeledPoint(y(i), Vectors.dense(Array(x1(i)))))
+    testData
+  }
+
+  /**
+   * Generates `k` classes multinomial synthetic logistic input in `n` dimensional space given the
+   * model weights and mean/variance of the features. The synthetic data will be drawn from
+   * the probability distribution constructed by weights using the following formula.
+   *
+   * P(y = 0 | x) = 1 / norm
+   * P(y = 1 | x) = exp(x * w_1) / norm
+   * P(y = 2 | x) = exp(x * w_2) / norm
+   * ...
+   * P(y = k-1 | x) = exp(x * w_{k-1}) / norm
+   * where norm = 1 + exp(x * w_1) + exp(x * w_2) + ... + exp(x * w_{k-1})
+   *
+   * @param weights matrix is flatten into a vector; as a result, the dimension of weights vector
+   *                will be (k - 1) * (n + 1) if `addIntercept == true`, and
+   *                if `addIntercept != true`, the dimension will be (k - 1) * n.
+   * @param xMean the mean of the generated features. Lots of time, if the features are not properly
+   *              standardized, the algorithm with poor implementation will have difficulty
+   *              to converge.
+   * @param xVariance the variance of the generated features.
+   * @param addIntercept whether to add intercept.
+   * @param nPoints the number of instance of generated data.
+   * @param seed the seed for random generator. For consistent testing result, it will be fixed.
+   */
+  def generateMultinomialLogisticInput(
+      weights: Array[Double],
+      xMean: Array[Double],
+      xVariance: Array[Double],
+      addIntercept: Boolean,
+      nPoints: Int,
+      seed: Int): Seq[LabeledPoint] = {
+    val rnd = new Random(seed)
+
+    val xDim = xMean.length
+    val xWithInterceptsDim = if (addIntercept) xDim + 1 else xDim
+    val nClasses = weights.length / xWithInterceptsDim + 1
+
+    val x = Array.fill[Vector](nPoints)(Vectors.dense(Array.fill[Double](xDim)(rnd.nextGaussian())))
+
+    x.foreach { vector =>
+      // This doesn't work if `vector` is a sparse vector.
+      val vectorArray = vector.toArray
+      var i = 0
+      val len = vectorArray.length
+      while (i < len) {
+        vectorArray(i) = vectorArray(i) * math.sqrt(xVariance(i)) + xMean(i)
+        i += 1
+      }
+    }
+
+    val y = (0 until nPoints).map { idx =>
+      val xArray = x(idx).toArray
+      val margins = Array.ofDim[Double](nClasses)
+      val probs = Array.ofDim[Double](nClasses)
+
+      for (i <- 0 until nClasses - 1) {
+        for (j <- 0 until xDim) margins(i + 1) += weights(i * xWithInterceptsDim + j) * xArray(j)
+        if (addIntercept) margins(i + 1) += weights((i + 1) * xWithInterceptsDim - 1)
+      }
+      // Preventing the overflow when we compute the probability
+      val maxMargin = margins.max
+      if (maxMargin > 0) for (i <- 0 until nClasses) margins(i) -= maxMargin
+
+      // Computing the probabilities for each class from the margins.
+      val norm = {
+        var temp = 0.0
+        for (i <- 0 until nClasses) {
+          probs(i) = math.exp(margins(i))
+          temp += probs(i)
+        }
+        temp
+      }
+      for (i <- 0 until nClasses) probs(i) /= norm
+
+      // Compute the cumulative probability so we can generate a random number and assign a label.
+      for (i <- 1 until nClasses) probs(i) += probs(i - 1)
+      val p = rnd.nextDouble()
+      var y = 0
+      breakable {
+        for (i <- 0 until nClasses) {
+          if (p < probs(i)) {
+            y = i
+            break
+          }
+        }
+      }
+      y
+    }
+
+    val testData = (0 until nPoints).map(i => LabeledPoint(y(i), x(i)))
+    testData
+  }
 }
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 d5282e07d6..85f325f076 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
@@ -18,14 +18,16 @@
 package org.apache.spark.ml.classification
 
 import org.apache.spark.SparkFunSuite
+import org.apache.spark.ml.classification.LogisticRegressionSuite._
+import org.apache.spark.ml.linalg.{Vector, Vectors}
 import org.apache.spark.ml.util.DefaultReadWriteTest
 import org.apache.spark.ml.util.MLTestingUtils
-import org.apache.spark.mllib.classification.LogisticRegressionSuite._
+import org.apache.spark.ml.util.TestingUtils._
 import org.apache.spark.mllib.classification.LogisticRegressionWithLBFGS
 import org.apache.spark.mllib.evaluation.MulticlassMetrics
-import org.apache.spark.mllib.linalg.{Vector, Vectors}
+import org.apache.spark.mllib.linalg.{Vectors => OldVectors}
+import org.apache.spark.mllib.regression.{LabeledPoint => OldLabeledPoint}
 import org.apache.spark.mllib.util.MLlibTestSparkContext
-import org.apache.spark.mllib.util.TestingUtils._
 import org.apache.spark.sql.{Dataset, Row}
 
 class MultilayerPerceptronClassifierSuite
@@ -134,12 +136,13 @@ class MultilayerPerceptronClassifierSuite
       .setNumClasses(numClasses)
     lr.optimizer.setRegParam(0.0)
       .setNumIterations(numIterations)
-    val lrModel = lr.run(rdd)
-    val lrPredictionAndLabels = lrModel.predict(rdd.map(_.features)).zip(rdd.map(_.label))
+    val lrModel = lr.run(rdd.map(OldLabeledPoint.fromML))
+    val lrPredictionAndLabels =
+      lrModel.predict(rdd.map(p => OldVectors.fromML(p.features))).zip(rdd.map(_.label))
     // MLP's predictions should not differ a lot from LR's.
     val lrMetrics = new MulticlassMetrics(lrPredictionAndLabels)
     val mlpMetrics = new MulticlassMetrics(mlpPredictionAndLabels)
-    assert(mlpMetrics.confusionMatrix ~== lrMetrics.confusionMatrix absTol 100)
+    assert(mlpMetrics.confusionMatrix.asML ~== lrMetrics.confusionMatrix.asML absTol 100)
   }
 
   test("read/write: MultilayerPerceptronClassifier") {
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 2a05c446e5..ff52115ec0 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
@@ -17,16 +17,20 @@
 
 package org.apache.spark.ml.classification
 
-import breeze.linalg.{Vector => BV}
+import scala.util.Random
+
+import breeze.linalg.{DenseVector => BDV, Vector => BV}
+import breeze.stats.distributions.{Multinomial => BrzMultinomial}
 
 import org.apache.spark.SparkFunSuite
+import org.apache.spark.ml.classification.NaiveBayesSuite._
+import org.apache.spark.ml.feature.LabeledPoint
+import org.apache.spark.ml.linalg._
 import org.apache.spark.ml.param.ParamsSuite
 import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils}
+import org.apache.spark.ml.util.TestingUtils._
 import org.apache.spark.mllib.classification.NaiveBayes.{Bernoulli, Multinomial}
-import org.apache.spark.mllib.classification.NaiveBayesSuite._
-import org.apache.spark.mllib.linalg._
 import org.apache.spark.mllib.util.MLlibTestSparkContext
-import org.apache.spark.mllib.util.TestingUtils._
 import org.apache.spark.sql.{DataFrame, Dataset, Row}
 
 class NaiveBayesSuite extends SparkFunSuite with MLlibTestSparkContext with DefaultReadWriteTest {
@@ -206,4 +210,48 @@ object NaiveBayesSuite {
     "predictionCol" -> "myPrediction",
     "smoothing" -> 0.1
   )
+
+  private def calcLabel(p: Double, pi: Array[Double]): Int = {
+    var sum = 0.0
+    for (j <- 0 until pi.length) {
+      sum += pi(j)
+      if (p < sum) return j
+    }
+    -1
+  }
+
+  // Generate input of the form Y = (theta * x).argmax()
+  def generateNaiveBayesInput(
+    pi: Array[Double],            // 1XC
+    theta: Array[Array[Double]],  // CXD
+    nPoints: Int,
+    seed: Int,
+    modelType: String = Multinomial,
+    sample: Int = 10): Seq[LabeledPoint] = {
+    val D = theta(0).length
+    val rnd = new Random(seed)
+    val _pi = pi.map(math.pow(math.E, _))
+    val _theta = theta.map(row => row.map(math.pow(math.E, _)))
+
+    for (i <- 0 until nPoints) yield {
+      val y = calcLabel(rnd.nextDouble(), _pi)
+      val xi = modelType match {
+        case Bernoulli => Array.tabulate[Double] (D) { j =>
+            if (rnd.nextDouble () < _theta(y)(j) ) 1 else 0
+        }
+        case Multinomial =>
+          val mult = BrzMultinomial(BDV(_theta(y)))
+          val emptyMap = (0 until D).map(x => (x, 0.0)).toMap
+          val counts = emptyMap ++ mult.sample(sample).groupBy(x => x).map {
+            case (index, reps) => (index, reps.size.toDouble)
+          }
+          counts.toArray.sortBy(_._1).map(_._2)
+        case _ =>
+          // This should never happen.
+          throw new UnknownError(s"Invalid modelType: $modelType.")
+      }
+
+      LabeledPoint(y, Vectors.dense(xi))
+    }
+  }
 }
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 5044d40998..361dd74cb0 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
@@ -19,14 +19,16 @@ package org.apache.spark.ml.classification
 
 import org.apache.spark.SparkFunSuite
 import org.apache.spark.ml.attribute.NominalAttribute
+import org.apache.spark.ml.classification.LogisticRegressionSuite._
+import org.apache.spark.ml.feature.LabeledPoint
 import org.apache.spark.ml.feature.StringIndexer
+import org.apache.spark.ml.linalg.Vectors
 import org.apache.spark.ml.param.{ParamMap, ParamsSuite}
 import org.apache.spark.ml.util.{DefaultReadWriteTest, MetadataUtils, MLTestingUtils}
-import org.apache.spark.mllib.classification.LogisticRegressionSuite._
 import org.apache.spark.mllib.classification.LogisticRegressionWithLBFGS
 import org.apache.spark.mllib.evaluation.MulticlassMetrics
-import org.apache.spark.mllib.linalg.Vectors
-import org.apache.spark.mllib.regression.LabeledPoint
+import org.apache.spark.mllib.linalg.{Vectors => OldVectors}
+import org.apache.spark.mllib.regression.{LabeledPoint => OldLabeledPoint}
 import org.apache.spark.mllib.util.MLlibTestSparkContext
 import org.apache.spark.mllib.util.TestingUtils._
 import org.apache.spark.rdd.RDD
@@ -88,8 +90,8 @@ class OneVsRestSuite extends SparkFunSuite with MLlibTestSparkContext with Defau
     val lr = new LogisticRegressionWithLBFGS().setIntercept(true).setNumClasses(numClasses)
     lr.optimizer.setRegParam(0.1).setNumIterations(100)
 
-    val model = lr.run(rdd)
-    val results = model.predict(rdd.map(_.features)).zip(rdd.map(_.label))
+    val model = lr.run(rdd.map(OldLabeledPoint.fromML))
+    val results = model.predict(rdd.map(p => OldVectors.fromML(p.features))).zip(rdd.map(_.label))
     // determine the #confusion matrix in each class.
     // bound how much error we allow compared to multinomial logistic regression.
     val expectedMetrics = new MulticlassMetrics(results)
diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/ProbabilisticClassifierSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/ProbabilisticClassifierSuite.scala
index cfa75ecf38..b3bd2b3e57 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/classification/ProbabilisticClassifierSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/classification/ProbabilisticClassifierSuite.scala
@@ -18,7 +18,7 @@
 package org.apache.spark.ml.classification
 
 import org.apache.spark.SparkFunSuite
-import org.apache.spark.mllib.linalg.{Vector, Vectors}
+import org.apache.spark.ml.linalg.{Vector, Vectors}
 
 final class TestProbabilisticClassificationModel(
     override val uid: String,
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 8002a2f4f2..2e99ee157a 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
@@ -18,12 +18,13 @@
 package org.apache.spark.ml.classification
 
 import org.apache.spark.SparkFunSuite
+import org.apache.spark.ml.feature.LabeledPoint
+import org.apache.spark.ml.linalg.{Vector, Vectors}
 import org.apache.spark.ml.param.ParamsSuite
 import org.apache.spark.ml.tree.LeafNode
 import org.apache.spark.ml.tree.impl.TreeTests
 import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils}
-import org.apache.spark.mllib.linalg.{Vector, Vectors}
-import org.apache.spark.mllib.regression.LabeledPoint
+import org.apache.spark.mllib.regression.{LabeledPoint => OldLabeledPoint}
 import org.apache.spark.mllib.tree.{EnsembleTestHelper, RandomForest => OldRandomForest}
 import org.apache.spark.mllib.tree.configuration.{Algo => OldAlgo}
 import org.apache.spark.mllib.util.MLlibTestSparkContext
@@ -46,8 +47,10 @@ class RandomForestClassifierSuite
     super.beforeAll()
     orderedLabeledPoints50_1000 =
       sc.parallelize(EnsembleTestHelper.generateOrderedLabeledPoints(numFeatures = 50, 1000))
+        .map(_.asML)
     orderedLabeledPoints5_20 =
       sc.parallelize(EnsembleTestHelper.generateOrderedLabeledPoints(numFeatures = 5, 20))
+        .map(_.asML)
   }
 
   /////////////////////////////////////////////////////////////////////////////
@@ -233,7 +236,8 @@ private object RandomForestClassifierSuite extends SparkFunSuite {
     val oldStrategy =
       rf.getOldStrategy(categoricalFeatures, numClasses, OldAlgo.Classification, rf.getOldImpurity)
     val oldModel = OldRandomForest.trainClassifier(
-      data, oldStrategy, rf.getNumTrees, rf.getFeatureSubsetStrategy, rf.getSeed.toInt)
+      data.map(OldLabeledPoint.fromML), oldStrategy, rf.getNumTrees, rf.getFeatureSubsetStrategy,
+      rf.getSeed.toInt)
     val newData: DataFrame = TreeTests.setMetadata(data, categoricalFeatures, numClasses)
     val newModel = rf.fit(newData)
     // Use parent from newTree since this is not checked anyways.
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 2832db2f99..88f31a1cd2 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
@@ -18,9 +18,9 @@
 package org.apache.spark.ml.clustering
 
 import org.apache.spark.SparkFunSuite
+import org.apache.spark.ml.linalg.{Vector, Vectors}
 import org.apache.spark.ml.util.DefaultReadWriteTest
 import org.apache.spark.mllib.clustering.{KMeans => MLlibKMeans}
-import org.apache.spark.mllib.linalg.{Vector, Vectors}
 import org.apache.spark.mllib.util.MLlibTestSparkContext
 import org.apache.spark.sql.{DataFrame, Dataset, SparkSession}
 
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 34e8964286..ddfa875554 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
@@ -20,10 +20,10 @@ package org.apache.spark.ml.clustering
 import org.apache.hadoop.fs.Path
 
 import org.apache.spark.SparkFunSuite
+import org.apache.spark.ml.linalg.{Vector, Vectors}
 import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils}
-import org.apache.spark.mllib.linalg.{Vector, Vectors}
+import org.apache.spark.ml.util.TestingUtils._
 import org.apache.spark.mllib.util.MLlibTestSparkContext
-import org.apache.spark.mllib.util.TestingUtils._
 import org.apache.spark.sql._
 
 
diff --git a/mllib/src/test/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluatorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluatorSuite.scala
index a8766f9035..9ee3df5eb5 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluatorSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluatorSuite.scala
@@ -18,9 +18,9 @@
 package org.apache.spark.ml.evaluation
 
 import org.apache.spark.SparkFunSuite
+import org.apache.spark.ml.linalg.Vectors
 import org.apache.spark.ml.param.ParamsSuite
 import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils}
-import org.apache.spark.mllib.linalg.Vectors
 import org.apache.spark.mllib.util.MLlibTestSparkContext
 
 class BinaryClassificationEvaluatorSuite
diff --git a/mllib/src/test/scala/org/apache/spark/ml/evaluation/RegressionEvaluatorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/evaluation/RegressionEvaluatorSuite.scala
index dcc004358d..42ff8adf6b 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/evaluation/RegressionEvaluatorSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/evaluation/RegressionEvaluatorSuite.scala
@@ -44,7 +44,7 @@ class RegressionEvaluatorSuite
      */
     val dataset = spark.createDataFrame(
       sc.parallelize(LinearDataGenerator.generateLinearInput(
-        6.3, Array(4.7, 7.2), Array(0.9, -1.3), Array(0.7, 1.2), 100, 42, 0.1), 2))
+        6.3, Array(4.7, 7.2), Array(0.9, -1.3), Array(0.7, 1.2), 100, 42, 0.1), 2).map(_.asML))
 
     /**
      * Using the following R code to load the data, train the model and evaluate metrics.
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/BinarizerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/BinarizerSuite.scala
index e91f758112..9cb84a6ee9 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/BinarizerSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/BinarizerSuite.scala
@@ -18,9 +18,9 @@
 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.mllib.linalg.{Vector, Vectors}
 import org.apache.spark.mllib.util.MLlibTestSparkContext
 import org.apache.spark.sql.{DataFrame, Row}
 
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/BucketizerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/BucketizerSuite.scala
index 98b2316d78..cd10c78311 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/BucketizerSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/BucketizerSuite.scala
@@ -20,11 +20,11 @@ package org.apache.spark.ml.feature
 import scala.util.Random
 
 import org.apache.spark.{SparkException, SparkFunSuite}
+import org.apache.spark.ml.linalg.Vectors
 import org.apache.spark.ml.param.ParamsSuite
 import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils}
-import org.apache.spark.mllib.linalg.Vectors
+import org.apache.spark.ml.util.TestingUtils._
 import org.apache.spark.mllib.util.MLlibTestSparkContext
-import org.apache.spark.mllib.util.TestingUtils._
 import org.apache.spark.sql.{DataFrame, Row}
 
 class BucketizerSuite extends SparkFunSuite with MLlibTestSparkContext with DefaultReadWriteTest {
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 4fcc9745b7..40d5b4881f 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
@@ -18,12 +18,11 @@
 package org.apache.spark.ml.feature
 
 import org.apache.spark.SparkFunSuite
+import org.apache.spark.ml.linalg.{Vector, Vectors}
 import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils}
+import org.apache.spark.ml.util.TestingUtils._
 import org.apache.spark.mllib.feature
-import org.apache.spark.mllib.linalg.{Vector, Vectors}
-import org.apache.spark.mllib.regression.LabeledPoint
 import org.apache.spark.mllib.util.MLlibTestSparkContext
-import org.apache.spark.mllib.util.TestingUtils._
 import org.apache.spark.sql.{Row, SparkSession}
 
 class ChiSqSelectorSuite extends SparkFunSuite with MLlibTestSparkContext
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 b82e3e90b4..a59203c33d 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
@@ -17,11 +17,11 @@
 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.mllib.linalg.{Vector, Vectors}
+import org.apache.spark.ml.util.TestingUtils._
 import org.apache.spark.mllib.util.MLlibTestSparkContext
-import org.apache.spark.mllib.util.TestingUtils._
 import org.apache.spark.sql.Row
 
 class CountVectorizerSuite extends SparkFunSuite with MLlibTestSparkContext
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/DCTSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/DCTSuite.scala
index dbd5ae8345..c02e961041 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/DCTSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/DCTSuite.scala
@@ -22,8 +22,8 @@ import scala.beans.BeanInfo
 import edu.emory.mathcs.jtransforms.dct.DoubleDCT_1D
 
 import org.apache.spark.SparkFunSuite
+import org.apache.spark.ml.linalg.{Vector, Vectors}
 import org.apache.spark.ml.util.DefaultReadWriteTest
-import org.apache.spark.mllib.linalg.{Vector, Vectors}
 import org.apache.spark.mllib.util.MLlibTestSparkContext
 import org.apache.spark.sql.Row
 
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/ElementwiseProductSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/ElementwiseProductSuite.scala
index fc1c05de23..a4cca27be7 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/ElementwiseProductSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/ElementwiseProductSuite.scala
@@ -18,8 +18,8 @@
 package org.apache.spark.ml.feature
 
 import org.apache.spark.SparkFunSuite
+import org.apache.spark.ml.linalg.Vectors
 import org.apache.spark.ml.util.DefaultReadWriteTest
-import org.apache.spark.mllib.linalg.Vectors
 import org.apache.spark.mllib.util.MLlibTestSparkContext
 
 class ElementwiseProductSuite
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/HashingTFSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/HashingTFSuite.scala
index 89d67d8e6f..99b800776b 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/HashingTFSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/HashingTFSuite.scala
@@ -19,12 +19,12 @@ package org.apache.spark.ml.feature
 
 import org.apache.spark.SparkFunSuite
 import org.apache.spark.ml.attribute.AttributeGroup
+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.TestingUtils._
 import org.apache.spark.mllib.feature.{HashingTF => MLlibHashingTF}
-import org.apache.spark.mllib.linalg.{Vector, Vectors}
 import org.apache.spark.mllib.util.MLlibTestSparkContext
-import org.apache.spark.mllib.util.TestingUtils._
 import org.apache.spark.util.Utils
 
 class HashingTFSuite extends SparkFunSuite with MLlibTestSparkContext with DefaultReadWriteTest {
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 208ea84913..09dc8b9b93 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
@@ -18,12 +18,13 @@
 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.TestingUtils._
 import org.apache.spark.mllib.feature.{IDFModel => OldIDFModel}
-import org.apache.spark.mllib.linalg.{DenseVector, SparseVector, Vector, Vectors}
+import org.apache.spark.mllib.linalg.VectorImplicits._
 import org.apache.spark.mllib.util.MLlibTestSparkContext
-import org.apache.spark.mllib.util.TestingUtils._
 import org.apache.spark.sql.Row
 
 class IDFSuite extends SparkFunSuite with MLlibTestSparkContext with DefaultReadWriteTest {
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/InteractionSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/InteractionSuite.scala
index 3409928007..3429172a8c 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/InteractionSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/InteractionSuite.scala
@@ -21,9 +21,9 @@ import scala.collection.mutable.ArrayBuilder
 
 import org.apache.spark.{SparkException, SparkFunSuite}
 import org.apache.spark.ml.attribute._
+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.mllib.linalg.{Vector, Vectors}
 import org.apache.spark.mllib.util.MLlibTestSparkContext
 import org.apache.spark.sql.functions.col
 
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 73d69ebfee..d6400ee02f 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
@@ -17,8 +17,8 @@
 package org.apache.spark.ml.feature
 
 import org.apache.spark.SparkFunSuite
+import org.apache.spark.ml.linalg.{Vector, Vectors}
 import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils}
-import org.apache.spark.mllib.linalg.{Vector, Vectors}
 import org.apache.spark.mllib.util.MLlibTestSparkContext
 import org.apache.spark.sql.Row
 
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 e495c8e571..5da8471175 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
@@ -18,8 +18,8 @@
 package org.apache.spark.ml.feature
 
 import org.apache.spark.SparkFunSuite
+import org.apache.spark.ml.linalg.{Vector, Vectors}
 import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils}
-import org.apache.spark.mllib.linalg.{Vector, Vectors}
 import org.apache.spark.mllib.util.MLlibTestSparkContext
 import org.apache.spark.sql.Row
 
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/NormalizerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/NormalizerSuite.scala
index 241a1e9fb5..b692831714 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/NormalizerSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/NormalizerSuite.scala
@@ -18,10 +18,10 @@
 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.util.DefaultReadWriteTest
-import org.apache.spark.mllib.linalg.{DenseVector, SparseVector, Vector, Vectors}
+import org.apache.spark.ml.util.TestingUtils._
 import org.apache.spark.mllib.util.MLlibTestSparkContext
-import org.apache.spark.mllib.util.TestingUtils._
 import org.apache.spark.sql.{DataFrame, Row}
 
 
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/OneHotEncoderSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/OneHotEncoderSuite.scala
index 06ffbc386f..7841b4fbc7 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/OneHotEncoderSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/OneHotEncoderSuite.scala
@@ -19,9 +19,9 @@ package org.apache.spark.ml.feature
 
 import org.apache.spark.SparkFunSuite
 import org.apache.spark.ml.attribute.{AttributeGroup, BinaryAttribute, NominalAttribute}
+import org.apache.spark.ml.linalg.Vector
 import org.apache.spark.ml.param.ParamsSuite
 import org.apache.spark.ml.util.DefaultReadWriteTest
-import org.apache.spark.mllib.linalg.Vector
 import org.apache.spark.mllib.util.MLlibTestSparkContext
 import org.apache.spark.sql.DataFrame
 import org.apache.spark.sql.functions.col
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 4befa84dbb..ddb51fb170 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
@@ -18,12 +18,13 @@
 package org.apache.spark.ml.feature
 
 import org.apache.spark.SparkFunSuite
+import org.apache.spark.ml.linalg._
 import org.apache.spark.ml.param.ParamsSuite
 import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils}
-import org.apache.spark.mllib.linalg._
+import org.apache.spark.ml.util.TestingUtils._
+import org.apache.spark.mllib.linalg.{Vectors => OldVectors}
 import org.apache.spark.mllib.linalg.distributed.RowMatrix
 import org.apache.spark.mllib.util.MLlibTestSparkContext
-import org.apache.spark.mllib.util.TestingUtils._
 import org.apache.spark.sql.Row
 
 class PCASuite extends SparkFunSuite with MLlibTestSparkContext with DefaultReadWriteTest {
@@ -45,9 +46,9 @@ class PCASuite extends SparkFunSuite with MLlibTestSparkContext with DefaultRead
 
     val dataRDD = sc.parallelize(data, 2)
 
-    val mat = new RowMatrix(dataRDD)
+    val mat = new RowMatrix(dataRDD.map(OldVectors.fromML))
     val pc = mat.computePrincipalComponents(3)
-    val expected = mat.multiply(pc).rows
+    val expected = mat.multiply(pc).rows.map(_.asML)
 
     val df = spark.createDataFrame(dataRDD.zip(expected)).toDF("features", "expected")
 
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/PolynomialExpansionSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/PolynomialExpansionSuite.scala
index e3adbba9d5..8e1f9ddb36 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/PolynomialExpansionSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/PolynomialExpansionSuite.scala
@@ -20,11 +20,11 @@ package org.apache.spark.ml.feature
 import org.scalatest.exceptions.TestFailedException
 
 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.mllib.linalg.{DenseVector, SparseVector, Vector, Vectors}
+import org.apache.spark.ml.util.TestingUtils._
 import org.apache.spark.mllib.util.MLlibTestSparkContext
-import org.apache.spark.mllib.util.TestingUtils._
 import org.apache.spark.sql.Row
 
 class PolynomialExpansionSuite
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 c623a6210b..c12ab8fe9e 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
@@ -19,9 +19,9 @@ package org.apache.spark.ml.feature
 
 import org.apache.spark.SparkFunSuite
 import org.apache.spark.ml.attribute._
+import org.apache.spark.ml.linalg.Vectors
 import org.apache.spark.ml.param.ParamsSuite
 import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils}
-import org.apache.spark.mllib.linalg.Vectors
 import org.apache.spark.mllib.util.MLlibTestSparkContext
 import org.apache.spark.sql.types.DoubleType
 
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 d62301be14..2243a0f972 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
@@ -18,11 +18,11 @@
 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.mllib.linalg.{Vector, Vectors}
+import org.apache.spark.ml.util.TestingUtils._
 import org.apache.spark.mllib.util.MLlibTestSparkContext
-import org.apache.spark.mllib.util.TestingUtils._
 import org.apache.spark.sql.{DataFrame, Row}
 
 class StandardScalerSuite extends SparkFunSuite with MLlibTestSparkContext
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/VectorAssemblerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorAssemblerSuite.scala
index 250011c859..14973e79bf 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/VectorAssemblerSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorAssemblerSuite.scala
@@ -19,9 +19,9 @@ package org.apache.spark.ml.feature
 
 import org.apache.spark.{SparkException, SparkFunSuite}
 import org.apache.spark.ml.attribute.{AttributeGroup, NominalAttribute, NumericAttribute}
+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.mllib.linalg.{DenseVector, SparseVector, Vector, Vectors}
 import org.apache.spark.mllib.util.MLlibTestSparkContext
 import org.apache.spark.sql.Row
 import org.apache.spark.sql.functions.col
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 d1c0270a02..7071423323 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
@@ -22,9 +22,9 @@ import scala.beans.{BeanInfo, BeanProperty}
 import org.apache.spark.{SparkException, SparkFunSuite}
 import org.apache.spark.internal.Logging
 import org.apache.spark.ml.attribute._
+import org.apache.spark.ml.linalg.{SparseVector, Vector, Vectors}
 import org.apache.spark.ml.param.ParamsSuite
 import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils}
-import org.apache.spark.mllib.linalg.{SparseVector, Vector, Vectors}
 import org.apache.spark.mllib.util.MLlibTestSparkContext
 import org.apache.spark.rdd.RDD
 import org.apache.spark.sql.DataFrame
diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/VectorSlicerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorSlicerSuite.scala
index 88a077f9a1..1746ce5310 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/VectorSlicerSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorSlicerSuite.scala
@@ -19,9 +19,9 @@ package org.apache.spark.ml.feature
 
 import org.apache.spark.SparkFunSuite
 import org.apache.spark.ml.attribute.{Attribute, AttributeGroup, NumericAttribute}
+import org.apache.spark.ml.linalg.{Vector, Vectors, VectorUDT}
 import org.apache.spark.ml.param.ParamsSuite
 import org.apache.spark.ml.util.DefaultReadWriteTest
-import org.apache.spark.mllib.linalg.{Vector, Vectors, VectorUDT}
 import org.apache.spark.mllib.util.MLlibTestSparkContext
 import org.apache.spark.sql.{DataFrame, Row}
 import org.apache.spark.sql.types.{StructField, StructType}
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 8cbe0f3def..280a36f56e 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
@@ -18,12 +18,12 @@
 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, MLTestingUtils}
+import org.apache.spark.ml.util.TestingUtils._
 import org.apache.spark.mllib.feature.{Word2VecModel => OldWord2VecModel}
-import org.apache.spark.mllib.linalg.{Vector, Vectors}
 import org.apache.spark.mllib.util.MLlibTestSparkContext
-import org.apache.spark.mllib.util.TestingUtils._
 import org.apache.spark.sql.Row
 
 class Word2VecSuite extends SparkFunSuite with MLlibTestSparkContext with DefaultReadWriteTest {
diff --git a/mllib/src/test/scala/org/apache/spark/ml/linalg/VectorUDTSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/linalg/VectorUDTSuite.scala
index 7b50876d33..6ddb12cb76 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/linalg/VectorUDTSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/linalg/VectorUDTSuite.scala
@@ -17,19 +17,11 @@
 
 package org.apache.spark.ml.linalg
 
-import scala.beans.BeanInfo
-
 import org.apache.spark.SparkFunSuite
+import org.apache.spark.ml.feature.LabeledPoint
 import org.apache.spark.sql.catalyst.JavaTypeInference
 import org.apache.spark.sql.types._
 
-@BeanInfo
-case class LabeledPoint(label: Double, features: Vector) {
-  override def toString: String = {
-    s"($label,$features)"
-  }
-}
-
 class VectorUDTSuite extends SparkFunSuite {
 
   test("preloaded VectorUDT") {
diff --git a/mllib/src/test/scala/org/apache/spark/ml/optim/IterativelyReweightedLeastSquaresSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/optim/IterativelyReweightedLeastSquaresSuite.scala
index 604021220a..b30d995794 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/optim/IterativelyReweightedLeastSquaresSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/optim/IterativelyReweightedLeastSquaresSuite.scala
@@ -19,9 +19,9 @@ package org.apache.spark.ml.optim
 
 import org.apache.spark.SparkFunSuite
 import org.apache.spark.ml.feature.Instance
-import org.apache.spark.mllib.linalg.Vectors
+import org.apache.spark.ml.linalg.Vectors
+import org.apache.spark.ml.util.TestingUtils._
 import org.apache.spark.mllib.util.MLlibTestSparkContext
-import org.apache.spark.mllib.util.TestingUtils._
 import org.apache.spark.rdd.RDD
 
 class IterativelyReweightedLeastSquaresSuite extends SparkFunSuite with MLlibTestSparkContext {
diff --git a/mllib/src/test/scala/org/apache/spark/ml/optim/WeightedLeastSquaresSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/optim/WeightedLeastSquaresSuite.scala
index 0b58a9821f..c8de796b2d 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/optim/WeightedLeastSquaresSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/optim/WeightedLeastSquaresSuite.scala
@@ -19,9 +19,9 @@ package org.apache.spark.ml.optim
 
 import org.apache.spark.SparkFunSuite
 import org.apache.spark.ml.feature.Instance
-import org.apache.spark.mllib.linalg.Vectors
+import org.apache.spark.ml.linalg.Vectors
+import org.apache.spark.ml.util.TestingUtils._
 import org.apache.spark.mllib.util.MLlibTestSparkContext
-import org.apache.spark.mllib.util.TestingUtils._
 import org.apache.spark.rdd.RDD
 
 class WeightedLeastSquaresSuite extends SparkFunSuite with MLlibTestSparkContext {
diff --git a/mllib/src/test/scala/org/apache/spark/ml/param/ParamsSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/param/ParamsSuite.scala
index a3366c0e59..aa9c53ca30 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/param/ParamsSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/param/ParamsSuite.scala
@@ -17,11 +17,11 @@
 
 package org.apache.spark.ml.param
 
-import java.io.{ByteArrayOutputStream, NotSerializableException, ObjectOutputStream}
+import java.io.{ByteArrayOutputStream, ObjectOutputStream}
 
 import org.apache.spark.SparkFunSuite
+import org.apache.spark.ml.linalg.{Vector, Vectors}
 import org.apache.spark.ml.util.MyParams
-import org.apache.spark.mllib.linalg.{Vector, Vectors}
 
 class ParamsSuite extends SparkFunSuite {
 
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 9da0c32dee..bbfc415cbb 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
@@ -31,11 +31,11 @@ import org.apache.commons.io.filefilter.TrueFileFilter
 
 import org.apache.spark._
 import org.apache.spark.internal.Logging
+import org.apache.spark.ml.linalg.Vectors
 import org.apache.spark.ml.recommendation.ALS._
 import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils}
-import org.apache.spark.mllib.linalg.Vectors
+import org.apache.spark.ml.util.TestingUtils._
 import org.apache.spark.mllib.util.MLlibTestSparkContext
-import org.apache.spark.mllib.util.TestingUtils._
 import org.apache.spark.rdd.RDD
 import org.apache.spark.scheduler.{SparkListener, SparkListenerStageCompleted}
 import org.apache.spark.sql.{DataFrame, Row, SparkSession}
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 e4772df622..05aae80c66 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
@@ -20,12 +20,12 @@ package org.apache.spark.ml.regression
 import scala.util.Random
 
 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, MLTestingUtils}
-import org.apache.spark.mllib.linalg.{Vector, Vectors}
+import org.apache.spark.ml.util.TestingUtils._
 import org.apache.spark.mllib.random.{ExponentialGenerator, WeibullGenerator}
 import org.apache.spark.mllib.util.MLlibTestSparkContext
-import org.apache.spark.mllib.util.TestingUtils._
 import org.apache.spark.sql.{DataFrame, Row}
 
 class AFTSurvivalRegressionSuite
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 2d30cbf367..9afb742406 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
@@ -18,10 +18,11 @@
 package org.apache.spark.ml.regression
 
 import org.apache.spark.SparkFunSuite
+import org.apache.spark.ml.feature.LabeledPoint
+import org.apache.spark.ml.linalg.Vector
 import org.apache.spark.ml.tree.impl.TreeTests
 import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils}
-import org.apache.spark.mllib.linalg.Vector
-import org.apache.spark.mllib.regression.LabeledPoint
+import org.apache.spark.mllib.regression.{LabeledPoint => OldLabeledPoint}
 import org.apache.spark.mllib.tree.{DecisionTree => OldDecisionTree,
   DecisionTreeSuite => OldDecisionTreeSuite}
 import org.apache.spark.mllib.util.MLlibTestSparkContext
@@ -38,7 +39,7 @@ class DecisionTreeRegressorSuite
   override def beforeAll() {
     super.beforeAll()
     categoricalDataPointsRDD =
-      sc.parallelize(OldDecisionTreeSuite.generateCategoricalDataPoints())
+      sc.parallelize(OldDecisionTreeSuite.generateCategoricalDataPoints().map(_.asML))
   }
 
   /////////////////////////////////////////////////////////////////////////////
@@ -170,7 +171,7 @@ private[ml] object DecisionTreeRegressorSuite extends SparkFunSuite {
       categoricalFeatures: Map[Int, Int]): Unit = {
     val numFeatures = data.first().features.size
     val oldStrategy = dt.getOldStrategy(categoricalFeatures)
-    val oldTree = OldDecisionTree.train(data, oldStrategy)
+    val oldTree = OldDecisionTree.train(data.map(OldLabeledPoint.fromML), oldStrategy)
     val newData: DataFrame = TreeTests.setMetadata(data, categoricalFeatures, numClasses = 0)
     val newTree = dt.fit(newData)
     // Use parent from newTree since this is not checked anyways.
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 ac833b833d..7b5df8f31b 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
@@ -18,10 +18,11 @@
 package org.apache.spark.ml.regression
 
 import org.apache.spark.SparkFunSuite
+import org.apache.spark.ml.feature.LabeledPoint
+import org.apache.spark.ml.linalg.Vectors
 import org.apache.spark.ml.tree.impl.TreeTests
 import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils}
-import org.apache.spark.mllib.linalg.Vectors
-import org.apache.spark.mllib.regression.LabeledPoint
+import org.apache.spark.mllib.regression.{LabeledPoint => OldLabeledPoint}
 import org.apache.spark.mllib.tree.{EnsembleTestHelper, GradientBoostedTrees => OldGBT}
 import org.apache.spark.mllib.tree.configuration.{Algo => OldAlgo}
 import org.apache.spark.mllib.util.MLlibTestSparkContext
@@ -48,10 +49,13 @@ class GBTRegressorSuite extends SparkFunSuite with MLlibTestSparkContext
   override def beforeAll() {
     super.beforeAll()
     data = sc.parallelize(EnsembleTestHelper.generateOrderedLabeledPoints(numFeatures = 10, 100), 2)
+      .map(_.asML)
     trainData =
       sc.parallelize(EnsembleTestHelper.generateOrderedLabeledPoints(numFeatures = 20, 120), 2)
+        .map(_.asML)
     validationData =
       sc.parallelize(EnsembleTestHelper.generateOrderedLabeledPoints(numFeatures = 20, 80), 2)
+        .map(_.asML)
   }
 
   test("Regression with continuous features") {
@@ -197,7 +201,7 @@ private object GBTRegressorSuite extends SparkFunSuite {
     val numFeatures = data.first().features.size
     val oldBoostingStrategy = gbt.getOldBoostingStrategy(categoricalFeatures, OldAlgo.Regression)
     val oldGBT = new OldGBT(oldBoostingStrategy, gbt.getSeed.toInt)
-    val oldModel = oldGBT.run(data)
+    val oldModel = oldGBT.run(data.map(OldLabeledPoint.fromML))
     val newData: DataFrame = TreeTests.setMetadata(data, categoricalFeatures, numClasses = 0)
     val newModel = gbt.fit(newData)
     // Use parent from newTree since this is not checked anyways.
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 3d9aeb8c0a..a4568e83fa 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
@@ -20,15 +20,15 @@ package org.apache.spark.ml.regression
 import scala.util.Random
 
 import org.apache.spark.SparkFunSuite
+import org.apache.spark.ml.classification.LogisticRegressionSuite._
 import org.apache.spark.ml.feature.Instance
+import org.apache.spark.ml.feature.LabeledPoint
+import org.apache.spark.ml.linalg.{BLAS, DenseVector, Vector, Vectors}
 import org.apache.spark.ml.param.ParamsSuite
 import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils}
-import org.apache.spark.mllib.classification.LogisticRegressionSuite._
-import org.apache.spark.mllib.linalg.{BLAS, DenseVector, Vector, Vectors}
+import org.apache.spark.ml.util.TestingUtils._
 import org.apache.spark.mllib.random._
-import org.apache.spark.mllib.regression.LabeledPoint
 import org.apache.spark.mllib.util.MLlibTestSparkContext
-import org.apache.spark.mllib.util.TestingUtils._
 import org.apache.spark.sql.{DataFrame, Row}
 import org.apache.spark.sql.functions._
 
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 bed4978b25..14d8a4e4e3 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
@@ -18,9 +18,9 @@
 package org.apache.spark.ml.regression
 
 import org.apache.spark.SparkFunSuite
+import org.apache.spark.ml.linalg.Vectors
 import org.apache.spark.ml.param.ParamsSuite
 import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils}
-import org.apache.spark.mllib.linalg.Vectors
 import org.apache.spark.mllib.util.MLlibTestSparkContext
 import org.apache.spark.sql.{DataFrame, Row}
 
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 a98227d2c1..332d331a47 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
@@ -21,12 +21,12 @@ import scala.util.Random
 
 import org.apache.spark.SparkFunSuite
 import org.apache.spark.ml.feature.Instance
+import org.apache.spark.ml.feature.LabeledPoint
+import org.apache.spark.ml.linalg.{DenseVector, Vector, Vectors}
 import org.apache.spark.ml.param.ParamsSuite
 import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils}
-import org.apache.spark.mllib.linalg.{DenseVector, Vector, Vectors}
-import org.apache.spark.mllib.regression.LabeledPoint
+import org.apache.spark.ml.util.TestingUtils._
 import org.apache.spark.mllib.util.{LinearDataGenerator, MLlibTestSparkContext}
-import org.apache.spark.mllib.util.TestingUtils._
 import org.apache.spark.sql.{DataFrame, Row}
 
 class LinearRegressionSuite
@@ -45,7 +45,7 @@ class LinearRegressionSuite
     datasetWithDenseFeature = spark.createDataFrame(
       sc.parallelize(LinearDataGenerator.generateLinearInput(
         intercept = 6.3, weights = Array(4.7, 7.2), xMean = Array(0.9, -1.3),
-        xVariance = Array(0.7, 1.2), nPoints = 10000, seed, eps = 0.1), 2))
+        xVariance = Array(0.7, 1.2), nPoints = 10000, seed, eps = 0.1), 2).map(_.asML))
     /*
        datasetWithDenseFeatureWithoutIntercept is not needed for correctness testing
        but is useful for illustrating training model without intercept
@@ -53,7 +53,7 @@ class LinearRegressionSuite
     datasetWithDenseFeatureWithoutIntercept = spark.createDataFrame(
       sc.parallelize(LinearDataGenerator.generateLinearInput(
         intercept = 0.0, weights = Array(4.7, 7.2), xMean = Array(0.9, -1.3),
-        xVariance = Array(0.7, 1.2), nPoints = 10000, seed, eps = 0.1), 2))
+        xVariance = Array(0.7, 1.2), nPoints = 10000, seed, eps = 0.1), 2).map(_.asML))
 
     val r = new Random(seed)
     // When feature size is larger than 4096, normal optimizer is choosed
@@ -64,7 +64,7 @@ class LinearRegressionSuite
         intercept = 0.0, weights = Seq.fill(featureSize)(r.nextDouble()).toArray,
         xMean = Seq.fill(featureSize)(r.nextDouble()).toArray,
         xVariance = Seq.fill(featureSize)(r.nextDouble()).toArray, nPoints = 200,
-        seed, eps = 0.1, sparsity = 0.7), 2))
+        seed, eps = 0.1, sparsity = 0.7), 2).map(_.asML))
 
     /*
        R code:
@@ -795,7 +795,7 @@ class LinearRegressionSuite
     Seq("auto", "l-bfgs", "normal").foreach { solver =>
       val (data, weightedData) = {
         val activeData = LinearDataGenerator.generateLinearInput(
-          6.3, Array(4.7, 7.2), Array(0.9, -1.3), Array(0.7, 1.2), 500, 1, 0.1)
+          6.3, Array(4.7, 7.2), Array(0.9, -1.3), Array(0.7, 1.2), 500, 1, 0.1).map(_.asML)
 
         val rnd = new Random(8392)
         val signedData = activeData.map { case p: LabeledPoint =>
@@ -822,7 +822,7 @@ class LinearRegressionSuite
         }
 
         val noiseData = LinearDataGenerator.generateLinearInput(
-          2, Array(1, 3), Array(0.9, -1.3), Array(0.7, 1.2), 500, 1, 0.1)
+          2, Array(1, 3), Array(0.9, -1.3), Array(0.7, 1.2), 500, 1, 0.1).map(_.asML)
         val weightedNoiseData = noiseData.map {
           case LabeledPoint(label, features) => Instance(label, weight = 0, features)
         }
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 7a3a3698f9..c08335f9f8 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
@@ -18,9 +18,10 @@
 package org.apache.spark.ml.regression
 
 import org.apache.spark.SparkFunSuite
+import org.apache.spark.ml.feature.LabeledPoint
 import org.apache.spark.ml.tree.impl.TreeTests
 import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils}
-import org.apache.spark.mllib.regression.LabeledPoint
+import org.apache.spark.mllib.regression.{LabeledPoint => OldLabeledPoint}
 import org.apache.spark.mllib.tree.{EnsembleTestHelper, RandomForest => OldRandomForest}
 import org.apache.spark.mllib.tree.configuration.{Algo => OldAlgo}
 import org.apache.spark.mllib.util.MLlibTestSparkContext
@@ -40,7 +41,8 @@ class RandomForestRegressorSuite extends SparkFunSuite with MLlibTestSparkContex
   override def beforeAll() {
     super.beforeAll()
     orderedLabeledPoints50_1000 =
-      sc.parallelize(EnsembleTestHelper.generateOrderedLabeledPoints(numFeatures = 50, 1000))
+      sc.parallelize(EnsembleTestHelper.generateOrderedLabeledPoints(numFeatures = 50, 1000)
+        .map(_.asML))
   }
 
   /////////////////////////////////////////////////////////////////////////////
@@ -139,8 +141,8 @@ private object RandomForestRegressorSuite extends SparkFunSuite {
     val numFeatures = data.first().features.size
     val oldStrategy =
       rf.getOldStrategy(categoricalFeatures, numClasses = 0, OldAlgo.Regression, rf.getOldImpurity)
-    val oldModel = OldRandomForest.trainRegressor(
-      data, oldStrategy, rf.getNumTrees, rf.getFeatureSubsetStrategy, rf.getSeed.toInt)
+    val oldModel = OldRandomForest.trainRegressor(data.map(OldLabeledPoint.fromML), oldStrategy,
+      rf.getNumTrees, rf.getFeatureSubsetStrategy, rf.getSeed.toInt)
     val newData: DataFrame = TreeTests.setMetadata(data, categoricalFeatures, numClasses = 0)
     val newModel = rf.fit(newData)
     // Use parent from newTree since this is not checked anyways.
diff --git a/mllib/src/test/scala/org/apache/spark/ml/source/libsvm/LibSVMRelationSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/source/libsvm/LibSVMRelationSuite.scala
index 7d0e01fd8f..2517de59fe 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/source/libsvm/LibSVMRelationSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/source/libsvm/LibSVMRelationSuite.scala
@@ -23,7 +23,7 @@ import java.nio.charset.StandardCharsets
 import com.google.common.io.Files
 
 import org.apache.spark.{SparkException, SparkFunSuite}
-import org.apache.spark.mllib.linalg.{DenseVector, SparseVector, Vector, Vectors}
+import org.apache.spark.ml.linalg.{DenseVector, SparseVector, Vector, Vectors}
 import org.apache.spark.mllib.util.MLlibTestSparkContext
 import org.apache.spark.sql.{Row, SaveMode}
 import org.apache.spark.util.Utils
diff --git a/mllib/src/test/scala/org/apache/spark/ml/tree/impl/GradientBoostedTreesSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/tree/impl/GradientBoostedTreesSuite.scala
index de92b51eb0..5c50a88c83 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/tree/impl/GradientBoostedTreesSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/tree/impl/GradientBoostedTreesSuite.scala
@@ -19,7 +19,7 @@ package org.apache.spark.ml.tree.impl
 
 import org.apache.spark.SparkFunSuite
 import org.apache.spark.internal.Logging
-import org.apache.spark.mllib.regression.LabeledPoint
+import org.apache.spark.ml.feature.LabeledPoint
 import org.apache.spark.mllib.tree.{GradientBoostedTreesSuite => OldGBTSuite}
 import org.apache.spark.mllib.tree.configuration.{BoostingStrategy, Strategy}
 import org.apache.spark.mllib.tree.configuration.Algo._
@@ -35,8 +35,8 @@ class GradientBoostedTreesSuite extends SparkFunSuite with MLlibTestSparkContext
   test("runWithValidation stops early and performs better on a validation dataset") {
     // Set numIterations large enough so that it stops early.
     val numIterations = 20
-    val trainRdd = sc.parallelize(OldGBTSuite.trainData, 2)
-    val validateRdd = sc.parallelize(OldGBTSuite.validateData, 2)
+    val trainRdd = sc.parallelize(OldGBTSuite.trainData, 2).map(_.asML)
+    val validateRdd = sc.parallelize(OldGBTSuite.validateData, 2).map(_.asML)
     val trainDF = spark.createDataFrame(trainRdd)
     val validateDF = spark.createDataFrame(validateRdd)
 
diff --git a/mllib/src/test/scala/org/apache/spark/ml/tree/impl/RandomForestSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/tree/impl/RandomForestSuite.scala
index 9739e6c05d..dcc2f305df 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/tree/impl/RandomForestSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/tree/impl/RandomForestSuite.scala
@@ -21,14 +21,14 @@ import scala.collection.mutable
 
 import org.apache.spark.SparkFunSuite
 import org.apache.spark.ml.classification.DecisionTreeClassificationModel
+import org.apache.spark.ml.feature.LabeledPoint
+import org.apache.spark.ml.linalg.{Vector, Vectors}
 import org.apache.spark.ml.tree._
-import org.apache.spark.mllib.linalg.{Vector, Vectors}
-import org.apache.spark.mllib.regression.LabeledPoint
+import org.apache.spark.ml.util.TestingUtils._
 import org.apache.spark.mllib.tree.{DecisionTreeSuite => OldDTSuite, EnsembleTestHelper}
 import org.apache.spark.mllib.tree.configuration.{Algo => OldAlgo, QuantileStrategy, Strategy => OldStrategy}
 import org.apache.spark.mllib.tree.impurity.{Entropy, Gini, GiniCalculator}
 import org.apache.spark.mllib.util.MLlibTestSparkContext
-import org.apache.spark.mllib.util.TestingUtils._
 import org.apache.spark.util.collection.OpenHashMap
 
 /**
@@ -43,7 +43,7 @@ class RandomForestSuite extends SparkFunSuite with MLlibTestSparkContext {
   /////////////////////////////////////////////////////////////////////////////
 
   test("Binary classification with continuous features: split calculation") {
-    val arr = OldDTSuite.generateOrderedLabeledPointsWithLabel1()
+    val arr = OldDTSuite.generateOrderedLabeledPointsWithLabel1().map(_.asML)
     assert(arr.length === 1000)
     val rdd = sc.parallelize(arr)
     val strategy = new OldStrategy(OldAlgo.Classification, Gini, 3, 2, 100)
@@ -55,7 +55,7 @@ class RandomForestSuite extends SparkFunSuite with MLlibTestSparkContext {
   }
 
   test("Binary classification with binary (ordered) categorical features: split calculation") {
-    val arr = OldDTSuite.generateCategoricalDataPoints()
+    val arr = OldDTSuite.generateCategoricalDataPoints().map(_.asML)
     assert(arr.length === 1000)
     val rdd = sc.parallelize(arr)
     val strategy = new OldStrategy(OldAlgo.Classification, Gini, maxDepth = 2, numClasses = 2,
@@ -72,7 +72,7 @@ class RandomForestSuite extends SparkFunSuite with MLlibTestSparkContext {
 
   test("Binary classification with 3-ary (ordered) categorical features," +
     " with no samples for one category: split calculation") {
-    val arr = OldDTSuite.generateCategoricalDataPoints()
+    val arr = OldDTSuite.generateCategoricalDataPoints().map(_.asML)
     assert(arr.length === 1000)
     val rdd = sc.parallelize(arr)
     val strategy = new OldStrategy(OldAlgo.Classification, Gini, maxDepth = 2, numClasses = 2,
@@ -148,7 +148,7 @@ class RandomForestSuite extends SparkFunSuite with MLlibTestSparkContext {
   }
 
   test("Multiclass classification with unordered categorical features: split calculations") {
-    val arr = OldDTSuite.generateCategoricalDataPoints()
+    val arr = OldDTSuite.generateCategoricalDataPoints().map(_.asML)
     assert(arr.length === 1000)
     val rdd = sc.parallelize(arr)
     val strategy = new OldStrategy(
@@ -189,7 +189,7 @@ class RandomForestSuite extends SparkFunSuite with MLlibTestSparkContext {
   }
 
   test("Multiclass classification with ordered categorical features: split calculations") {
-    val arr = OldDTSuite.generateCategoricalDataPointsForMulticlassForOrderedFeatures()
+    val arr = OldDTSuite.generateCategoricalDataPointsForMulticlassForOrderedFeatures().map(_.asML)
     assert(arr.length === 3000)
     val rdd = sc.parallelize(arr)
     val strategy = new OldStrategy(OldAlgo.Classification, Gini, maxDepth = 2, numClasses = 100,
@@ -334,7 +334,7 @@ class RandomForestSuite extends SparkFunSuite with MLlibTestSparkContext {
   }
 
   test("Second level node building with vs. without groups") {
-    val arr = OldDTSuite.generateOrderedLabeledPoints()
+    val arr = OldDTSuite.generateOrderedLabeledPoints().map(_.asML)
     assert(arr.length === 1000)
     val rdd = sc.parallelize(arr)
     // For tree with 1 group
@@ -378,7 +378,7 @@ class RandomForestSuite extends SparkFunSuite with MLlibTestSparkContext {
   def binaryClassificationTestWithContinuousFeaturesAndSubsampledFeatures(strategy: OldStrategy) {
     val numFeatures = 50
     val arr = EnsembleTestHelper.generateOrderedLabeledPoints(numFeatures, 1000)
-    val rdd = sc.parallelize(arr)
+    val rdd = sc.parallelize(arr).map(_.asML)
 
     // Select feature subset for top nodes.  Return true if OK.
     def checkFeatureSubsetStrategy(
diff --git a/mllib/src/test/scala/org/apache/spark/ml/tree/impl/TreeTests.scala b/mllib/src/test/scala/org/apache/spark/ml/tree/impl/TreeTests.scala
index 12ade4c92f..8cbd652bac 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/tree/impl/TreeTests.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/tree/impl/TreeTests.scala
@@ -22,9 +22,9 @@ import scala.collection.JavaConverters._
 import org.apache.spark.{SparkContext, SparkFunSuite}
 import org.apache.spark.api.java.JavaRDD
 import org.apache.spark.ml.attribute.{AttributeGroup, NominalAttribute, NumericAttribute}
+import org.apache.spark.ml.feature.LabeledPoint
+import org.apache.spark.ml.linalg.Vectors
 import org.apache.spark.ml.tree._
-import org.apache.spark.mllib.linalg.Vectors
-import org.apache.spark.mllib.regression.LabeledPoint
 import org.apache.spark.rdd.RDD
 import org.apache.spark.sql.{DataFrame, SparkSession}
 
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 85df6da7a1..30bd390381 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
@@ -20,17 +20,17 @@ package org.apache.spark.ml.tuning
 import org.apache.spark.SparkFunSuite
 import org.apache.spark.ml.{Estimator, Model, Pipeline}
 import org.apache.spark.ml.classification.{LogisticRegression, LogisticRegressionModel}
+import org.apache.spark.ml.classification.LogisticRegressionSuite.generateLogisticInput
 import org.apache.spark.ml.evaluation.{BinaryClassificationEvaluator, Evaluator, RegressionEvaluator}
 import org.apache.spark.ml.feature.HashingTF
+import org.apache.spark.ml.linalg.Vectors
 import org.apache.spark.ml.param.{ParamMap, ParamPair}
 import org.apache.spark.ml.param.shared.HasInputCol
 import org.apache.spark.ml.regression.LinearRegression
 import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils}
-import org.apache.spark.mllib.classification.LogisticRegressionSuite.generateLogisticInput
-import org.apache.spark.mllib.linalg.Vectors
 import org.apache.spark.mllib.util.{LinearDataGenerator, MLlibTestSparkContext}
-import org.apache.spark.sql.{DataFrame, Dataset}
-import org.apache.spark.sql.types.{StructField, StructType}
+import org.apache.spark.sql.Dataset
+import org.apache.spark.sql.types.StructType
 
 class CrossValidatorSuite
   extends SparkFunSuite with MLlibTestSparkContext with DefaultReadWriteTest {
@@ -69,7 +69,7 @@ class CrossValidatorSuite
   test("cross validation with linear regression") {
     val dataset = spark.createDataFrame(
       sc.parallelize(LinearDataGenerator.generateLinearInput(
-        6.3, Array(4.7, 7.2), Array(0.9, -1.3), Array(0.7, 1.2), 100, 42, 0.1), 2))
+        6.3, Array(4.7, 7.2), Array(0.9, -1.3), Array(0.7, 1.2), 100, 42, 0.1), 2).map(_.asML))
 
     val trainer = new LinearRegression().setSolver("l-bfgs")
     val lrParamMaps = new ParamGridBuilder()
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 f8d3de19b0..c1e9c2fc1d 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
@@ -20,15 +20,15 @@ package org.apache.spark.ml.tuning
 import org.apache.spark.SparkFunSuite
 import org.apache.spark.ml.{Estimator, Model}
 import org.apache.spark.ml.classification.{LogisticRegression, LogisticRegressionModel}
+import org.apache.spark.ml.classification.LogisticRegressionSuite.generateLogisticInput
 import org.apache.spark.ml.evaluation.{BinaryClassificationEvaluator, Evaluator, RegressionEvaluator}
+import org.apache.spark.ml.linalg.Vectors
 import org.apache.spark.ml.param.ParamMap
 import org.apache.spark.ml.param.shared.HasInputCol
 import org.apache.spark.ml.regression.LinearRegression
 import org.apache.spark.ml.util.DefaultReadWriteTest
-import org.apache.spark.mllib.classification.LogisticRegressionSuite.generateLogisticInput
-import org.apache.spark.mllib.linalg.Vectors
 import org.apache.spark.mllib.util.{LinearDataGenerator, MLlibTestSparkContext}
-import org.apache.spark.sql.{DataFrame, Dataset}
+import org.apache.spark.sql.Dataset
 import org.apache.spark.sql.types.StructType
 
 class TrainValidationSplitSuite
@@ -60,7 +60,7 @@ class TrainValidationSplitSuite
   test("train validation with linear regression") {
     val dataset = spark.createDataFrame(
         sc.parallelize(LinearDataGenerator.generateLinearInput(
-            6.3, Array(4.7, 7.2), Array(0.9, -1.3), Array(0.7, 1.2), 100, 42, 0.1), 2))
+            6.3, Array(4.7, 7.2), Array(0.9, -1.3), Array(0.7, 1.2), 100, 42, 0.1), 2).map(_.asML))
 
     val trainer = new LinearRegression().setSolver("l-bfgs")
     val lrParamMaps = new ParamGridBuilder()
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 ad7d2c9b8d..6aae625fc8 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
@@ -20,9 +20,9 @@ package org.apache.spark.ml.util
 import org.apache.spark.SparkFunSuite
 import org.apache.spark.ml.{Estimator, Model}
 import org.apache.spark.ml.evaluation.Evaluator
+import org.apache.spark.ml.linalg.Vectors
 import org.apache.spark.ml.param.ParamMap
 import org.apache.spark.ml.tree.impl.TreeTests
-import org.apache.spark.mllib.linalg.Vectors
 import org.apache.spark.sql.{DataFrame, SparkSession}
 import org.apache.spark.sql.functions._
 import org.apache.spark.sql.types._
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/linalg/MatricesSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/linalg/MatricesSuite.scala
index b7df02e6c0..8c5b4bda25 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/linalg/MatricesSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/linalg/MatricesSuite.scala
@@ -560,4 +560,55 @@ class MatricesSuite extends SparkFunSuite {
     compare(oldSM0, newSM0)
     compare(oldDM0, newDM0)
   }
+
+  test("implicit conversions between new local linalg and mllib linalg") {
+
+    def mllibMatrixToTriple(m: Matrix): (Array[Double], Int, Int) =
+      (m.toArray, m.numCols, m.numRows)
+
+    def mllibDenseMatrixToTriple(m: DenseMatrix): (Array[Double], Int, Int) =
+      (m.toArray, m.numCols, m.numRows)
+
+    def mllibSparseMatrixToTriple(m: SparseMatrix): (Array[Double], Int, Int) =
+      (m.toArray, m.numCols, m.numRows)
+
+    def mlMatrixToTriple(m: newlinalg.Matrix): (Array[Double], Int, Int) =
+      (m.toArray, m.numCols, m.numRows)
+
+    def mlDenseMatrixToTriple(m: newlinalg.DenseMatrix): (Array[Double], Int, Int) =
+      (m.toArray, m.numCols, m.numRows)
+
+    def mlSparseMatrixToTriple(m: newlinalg.SparseMatrix): (Array[Double], Int, Int) =
+      (m.toArray, m.numCols, m.numRows)
+
+    def compare(m1: (Array[Double], Int, Int), m2: (Array[Double], Int, Int)): Unit = {
+      assert(m1._1 === m2._1)
+      assert(m1._2 === m2._2)
+      assert(m1._3 === m2._3)
+    }
+
+    val dm: DenseMatrix = new DenseMatrix(3, 2, Array(0.0, 0.0, 1.0, 0.0, 2.0, 3.5))
+    val sm: SparseMatrix = dm.toSparse
+    val sm0: Matrix = sm.asInstanceOf[Matrix]
+    val dm0: Matrix = dm.asInstanceOf[Matrix]
+
+    val newSM: newlinalg.SparseMatrix = sm.asML
+    val newDM: newlinalg.DenseMatrix = dm.asML
+    val newSM0: newlinalg.Matrix = sm0.asML
+    val newDM0: newlinalg.Matrix = dm0.asML
+
+    import org.apache.spark.mllib.linalg.MatrixImplicits._
+
+    compare(mllibMatrixToTriple(dm0), mllibMatrixToTriple(newDM0))
+    compare(mllibMatrixToTriple(sm0), mllibMatrixToTriple(newSM0))
+
+    compare(mllibDenseMatrixToTriple(dm), mllibDenseMatrixToTriple(newDM))
+    compare(mllibSparseMatrixToTriple(sm), mllibSparseMatrixToTriple(newSM))
+
+    compare(mlMatrixToTriple(dm0), mlMatrixToTriple(newDM))
+    compare(mlMatrixToTriple(sm0), mlMatrixToTriple(newSM0))
+
+    compare(mlDenseMatrixToTriple(dm), mlDenseMatrixToTriple(newDM))
+    compare(mlSparseMatrixToTriple(sm), mlSparseMatrixToTriple(newSM))
+  }
 }
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/linalg/VectorsSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/linalg/VectorsSuite.scala
index a7c1a07604..2e9c40ab88 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/linalg/VectorsSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/linalg/VectorsSuite.scala
@@ -422,4 +422,43 @@ class VectorsSuite extends SparkFunSuite with Logging {
     assert(oldSV0.toArray === newSV0.toArray)
     assert(oldDV0.toArray === newDV0.toArray)
   }
+
+  test("implicit conversions between new local linalg and mllib linalg") {
+
+    def mllibVectorToArray(v: Vector): Array[Double] = v.toArray
+
+    def mllibDenseVectorToArray(v: DenseVector): Array[Double] = v.toArray
+
+    def mllibSparseVectorToArray(v: SparseVector): Array[Double] = v.toArray
+
+    def mlVectorToArray(v: newlinalg.Vector): Array[Double] = v.toArray
+
+    def mlDenseVectorToArray(v: newlinalg.DenseVector): Array[Double] = v.toArray
+
+    def mlSparseVectorToArray(v: newlinalg.SparseVector): Array[Double] = v.toArray
+
+    val dv: DenseVector = new DenseVector(Array(1.0, 2.0, 3.5))
+    val sv: SparseVector = new SparseVector(5, Array(1, 2, 4), Array(1.1, 2.2, 4.4))
+    val sv0: Vector = sv.asInstanceOf[Vector]
+    val dv0: Vector = dv.asInstanceOf[Vector]
+
+    val newSV: newlinalg.SparseVector = sv.asML
+    val newDV: newlinalg.DenseVector = dv.asML
+    val newSV0: newlinalg.Vector = sv0.asML
+    val newDV0: newlinalg.Vector = dv0.asML
+
+    import org.apache.spark.mllib.linalg.VectorImplicits._
+
+    assert(mllibVectorToArray(dv0) === mllibVectorToArray(newDV0))
+    assert(mllibVectorToArray(sv0) === mllibVectorToArray(newSV0))
+
+    assert(mllibDenseVectorToArray(dv) === mllibDenseVectorToArray(newDV))
+    assert(mllibSparseVectorToArray(sv) === mllibSparseVectorToArray(newSV))
+
+    assert(mlVectorToArray(dv0) === mlVectorToArray(newDV0))
+    assert(mlVectorToArray(sv0) === mlVectorToArray(newSV0))
+
+    assert(mlDenseVectorToArray(dv) === mlDenseVectorToArray(newDV))
+    assert(mlSparseVectorToArray(sv) === mlSparseVectorToArray(newSV))
+  }
 }
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/regression/LabeledPointSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/regression/LabeledPointSuite.scala
index f8d0af8820..252a068dcd 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/regression/LabeledPointSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/regression/LabeledPointSuite.scala
@@ -18,6 +18,7 @@
 package org.apache.spark.mllib.regression
 
 import org.apache.spark.SparkFunSuite
+import org.apache.spark.ml.feature.{LabeledPoint => NewLabeledPoint}
 import org.apache.spark.mllib.linalg.Vectors
 
 class LabeledPointSuite extends SparkFunSuite {
@@ -40,4 +41,16 @@ class LabeledPointSuite extends SparkFunSuite {
     val point = LabeledPoint.parse("1.0,1.0 0.0 -2.0")
     assert(point === LabeledPoint(1.0, Vectors.dense(1.0, 0.0, -2.0)))
   }
+
+  test("conversions between new ml LabeledPoint and mllib LabeledPoint") {
+    val points: Seq[LabeledPoint] = Seq(
+      LabeledPoint(1.0, Vectors.dense(1.0, 0.0)),
+      LabeledPoint(0.0, Vectors.sparse(2, Array(1), Array(-1.0))))
+
+    val newPoints: Seq[NewLabeledPoint] = points.map(_.asML)
+
+    points.zip(newPoints).foreach { case (p1, p2) =>
+      assert(p1 === LabeledPoint.fromML(p2))
+    }
+  }
 }
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/tree/DecisionTreeSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/tree/DecisionTreeSuite.scala
index 49cb7e1f24..441d0f7614 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/tree/DecisionTreeSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/tree/DecisionTreeSuite.scala
@@ -73,7 +73,7 @@ class DecisionTreeSuite extends SparkFunSuite with MLlibTestSparkContext {
       maxBins = 100,
       categoricalFeaturesInfo = Map(0 -> 3, 1 -> 3))
 
-    val metadata = DecisionTreeMetadata.buildMetadata(rdd, strategy)
+    val metadata = DecisionTreeMetadata.buildMetadata(rdd.map(_.asML), strategy)
     assert(!metadata.isUnordered(featureIndex = 0))
     assert(!metadata.isUnordered(featureIndex = 1))
 
@@ -100,7 +100,7 @@ class DecisionTreeSuite extends SparkFunSuite with MLlibTestSparkContext {
       maxDepth = 2,
       maxBins = 100,
       categoricalFeaturesInfo = Map(0 -> 2, 1 -> 2))
-    val metadata = DecisionTreeMetadata.buildMetadata(rdd, strategy)
+    val metadata = DecisionTreeMetadata.buildMetadata(rdd.map(_.asML), strategy)
     assert(!metadata.isUnordered(featureIndex = 0))
     assert(!metadata.isUnordered(featureIndex = 1))
 
@@ -116,7 +116,7 @@ class DecisionTreeSuite extends SparkFunSuite with MLlibTestSparkContext {
     val rdd = sc.parallelize(arr)
     val strategy = new Strategy(Classification, Gini, maxDepth = 3,
       numClasses = 2, maxBins = 100)
-    val metadata = DecisionTreeMetadata.buildMetadata(rdd, strategy)
+    val metadata = DecisionTreeMetadata.buildMetadata(rdd.map(_.asML), strategy)
     assert(!metadata.isUnordered(featureIndex = 0))
     assert(!metadata.isUnordered(featureIndex = 1))
 
@@ -133,7 +133,7 @@ class DecisionTreeSuite extends SparkFunSuite with MLlibTestSparkContext {
     val rdd = sc.parallelize(arr)
     val strategy = new Strategy(Classification, Gini, maxDepth = 3,
       numClasses = 2, maxBins = 100)
-    val metadata = DecisionTreeMetadata.buildMetadata(rdd, strategy)
+    val metadata = DecisionTreeMetadata.buildMetadata(rdd.map(_.asML), strategy)
     assert(!metadata.isUnordered(featureIndex = 0))
     assert(!metadata.isUnordered(featureIndex = 1))
 
@@ -150,7 +150,7 @@ class DecisionTreeSuite extends SparkFunSuite with MLlibTestSparkContext {
     val rdd = sc.parallelize(arr)
     val strategy = new Strategy(Classification, Entropy, maxDepth = 3,
       numClasses = 2, maxBins = 100)
-    val metadata = DecisionTreeMetadata.buildMetadata(rdd, strategy)
+    val metadata = DecisionTreeMetadata.buildMetadata(rdd.map(_.asML), strategy)
     assert(!metadata.isUnordered(featureIndex = 0))
     assert(!metadata.isUnordered(featureIndex = 1))
 
@@ -167,7 +167,7 @@ class DecisionTreeSuite extends SparkFunSuite with MLlibTestSparkContext {
     val rdd = sc.parallelize(arr)
     val strategy = new Strategy(Classification, Entropy, maxDepth = 3,
       numClasses = 2, maxBins = 100)
-    val metadata = DecisionTreeMetadata.buildMetadata(rdd, strategy)
+    val metadata = DecisionTreeMetadata.buildMetadata(rdd.map(_.asML), strategy)
     assert(!metadata.isUnordered(featureIndex = 0))
     assert(!metadata.isUnordered(featureIndex = 1))
 
@@ -183,7 +183,7 @@ class DecisionTreeSuite extends SparkFunSuite with MLlibTestSparkContext {
     val rdd = sc.parallelize(arr)
     val strategy = new Strategy(algo = Classification, impurity = Gini, maxDepth = 4,
       numClasses = 3, categoricalFeaturesInfo = Map(0 -> 3, 1 -> 3))
-    val metadata = DecisionTreeMetadata.buildMetadata(rdd, strategy)
+    val metadata = DecisionTreeMetadata.buildMetadata(rdd.map(_.asML), strategy)
     assert(strategy.isMulticlassClassification)
     assert(metadata.isUnordered(featureIndex = 0))
     assert(metadata.isUnordered(featureIndex = 1))
@@ -240,7 +240,7 @@ class DecisionTreeSuite extends SparkFunSuite with MLlibTestSparkContext {
       numClasses = 3, maxBins = maxBins,
       categoricalFeaturesInfo = Map(0 -> 3, 1 -> 3))
     assert(strategy.isMulticlassClassification)
-    val metadata = DecisionTreeMetadata.buildMetadata(rdd, strategy)
+    val metadata = DecisionTreeMetadata.buildMetadata(rdd.map(_.asML), strategy)
     assert(metadata.isUnordered(featureIndex = 0))
     assert(metadata.isUnordered(featureIndex = 1))
 
@@ -288,7 +288,7 @@ class DecisionTreeSuite extends SparkFunSuite with MLlibTestSparkContext {
     val strategy = new Strategy(algo = Classification, impurity = Gini, maxDepth = 4,
       numClasses = 3, maxBins = 100, categoricalFeaturesInfo = Map(0 -> 3))
     assert(strategy.isMulticlassClassification)
-    val metadata = DecisionTreeMetadata.buildMetadata(rdd, strategy)
+    val metadata = DecisionTreeMetadata.buildMetadata(rdd.map(_.asML), strategy)
     assert(metadata.isUnordered(featureIndex = 0))
 
     val model = DecisionTree.train(rdd, strategy)
@@ -310,7 +310,7 @@ class DecisionTreeSuite extends SparkFunSuite with MLlibTestSparkContext {
       numClasses = 3, maxBins = 100,
       categoricalFeaturesInfo = Map(0 -> 10, 1 -> 10))
     assert(strategy.isMulticlassClassification)
-    val metadata = DecisionTreeMetadata.buildMetadata(rdd, strategy)
+    val metadata = DecisionTreeMetadata.buildMetadata(rdd.map(_.asML), strategy)
     assert(!metadata.isUnordered(featureIndex = 0))
     assert(!metadata.isUnordered(featureIndex = 1))