Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/1367#discussion_r15133828
--- Diff: mllib/src/main/scala/org/apache/spark/mllib/stat/Statistics.scala
---
@@ -0,0 +1,76 @@
+/*
+ * 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.mllib.stat
+
+import org.apache.spark.annotation.Experimental
+import org.apache.spark.mllib.linalg.{Matrix, Vector}
+import org.apache.spark.mllib.stat.correlation.Correlations
+import org.apache.spark.rdd.RDD
+
+/**
+ * API for statistical functions in MLlib
+ */
+@Experimental
+object Statistics {
+
+ /**
+ * Compute the Pearson correlation matrix for the input RDD of Vectors.
+ * Returns NaN if either vector has 0 variance.
+ *
+ * @param X an RDD[Vector] for which the correlation matrix is to be
computed.
+ * @return Pearson correlation matrix comparing columns in X.
+ */
+ def corr(X: RDD[Vector]): Matrix = Correlations.corrMatrix(X)
+
+ /**
+ * Compute the correlation matrix for the input RDD of Vectors using the
specified method.
+ * Methods currently supported: pearson (default), spearman
+ *
+ * Note that for Spearman, a rank correlation, we need to create an
RDD[Double] for each column
+ * and sort it in order to retrieve the ranks and then join the columns
back into an RDD[Vector],
+ * which is fairly costly. Cache the input RDD before calling corr with
`method = "spearman"` to
+ * avoid recomputing the common lineage
--- End diff --
Missing `.` at the end.
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