Github user imatiach-msft commented on a diff in the pull request:
https://github.com/apache/spark/pull/17108#discussion_r103747651
--- Diff: mllib/src/main/scala/org/apache/spark/ml/stat/Statistics.scala ---
@@ -0,0 +1,89 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.ml.stat
+
+import scala.collection.JavaConverters._
+
+import org.apache.spark.annotation.Since
+import org.apache.spark.ml.linalg.{SQLDataTypes, Vector}
+import org.apache.spark.mllib.linalg.{Vectors => OldVectors}
+import org.apache.spark.mllib.stat.{Statistics => OldStatistics}
+import org.apache.spark.sql.{DataFrame, Dataset, Row}
+import org.apache.spark.sql.types.{StructField, StructType}
+
+/**
+ * API for statistical functions in MLlib, compatible with Dataframes and
Datasets.
+ *
+ * The functions in this package generalize the functions in
[[org.apache.spark.sql.Dataset.stat]]
+ * to MLlib's Vector types.
+ */
+@Since("2.2.0")
+object Statistics {
+
+ /**
+ * Compute the correlation matrix for the input RDD of Vectors using the
specified method.
+ * Methods currently supported: `pearson` (default), `spearman`.
+ *
+ * @param dataset a dataset or a dataframe
--- End diff --
it seems there are inconsistencies in a lot of comments. I wish we had
something like scalastyle for comments...
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