mark distribute matrices experimental

Author: mengxr

mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/CoordinateMatrix.scala

@@ -19,6 +19,7 @@ package org.apache.spark.mllib.linalg.distributed
 
 import breeze.linalg.{DenseMatrix => BDM}
 
+import org.apache.spark.annotation.Experimental
 import org.apache.spark.rdd.RDD
 import org.apache.spark.SparkContext._
 import org.apache.spark.mllib.linalg.Vectors
@@ -32,6 +33,8 @@ import org.apache.spark.mllib.linalg.Vectors
 case class MatrixEntry(i: Long, j: Long, value: Double)
 
 /**
+ * :: Experimental ::
+ *
  * Represents a matrix in coordinate format.
  *
  * @param entries matrix entries
@@ -40,6 +43,7 @@ case class MatrixEntry(i: Long, j: Long, value: Double)
  * @param nCols number of columns. A non-positive value means unknown, and then the number of
  *              columns will be determined by the max column index plus one.
  */
+@Experimental
 class CoordinateMatrix(
     val entries: RDD[MatrixEntry],
     private var nRows: Long,

mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/DistributedMatrix.scala

@@ -19,8 +19,6 @@ package org.apache.spark.mllib.linalg.distributed
 
 import breeze.linalg.{DenseMatrix => BDM}
 
-import org.apache.spark.mllib.linalg.Matrix
-
 /**
  * Represents a distributively stored matrix backed by one or more RDDs.
  */

mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/IndexedRowMatrix.scala

@@ -19,14 +19,22 @@ package org.apache.spark.mllib.linalg.distributed
 
 import breeze.linalg.{DenseMatrix => BDM}
 
+import org.apache.spark.annotation.Experimental
 import org.apache.spark.rdd.RDD
 import org.apache.spark.mllib.linalg._
 import org.apache.spark.mllib.linalg.SingularValueDecomposition
 
-/** Represents a row of [[org.apache.spark.mllib.linalg.distributed.IndexedRowMatrix]]. */
+/**
+ * :: Experimental ::
+ *
+ * Represents a row of [[org.apache.spark.mllib.linalg.distributed.IndexedRowMatrix]].
+ */
+@Experimental
 case class IndexedRow(index: Long, vector: Vector)
 
 /**
+ * :: Experimental ::
+ *
  * Represents a row-oriented [[org.apache.spark.mllib.linalg.distributed.DistributedMatrix]] with
  * indexed rows.
  *
@@ -36,6 +44,7 @@ case class IndexedRow(index: Long, vector: Vector)
  * @param nCols number of columns. A non-positive value means unknown, and then the number of
  *              columns will be determined by the size of the first row.
  */
+@Experimental
 class IndexedRowMatrix(
     val rows: RDD[IndexedRow],
     private var nRows: Long,

mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala

@@ -23,11 +23,14 @@ import breeze.linalg.{DenseMatrix => BDM, DenseVector => BDV, svd => brzSvd}
 import breeze.numerics.{sqrt => brzSqrt}
 import com.github.fommil.netlib.BLAS.{getInstance => blas}
 
+import org.apache.spark.annotation.Experimental
 import org.apache.spark.mllib.linalg._
 import org.apache.spark.rdd.RDD
 import org.apache.spark.Logging
 
 /**
+ * :: Experimental ::
+ *
  * Represents a row-oriented distributed Matrix with no meaningful row indices.
  *
  * @param rows rows stored as an RDD[Vector]
@@ -36,6 +39,7 @@ import org.apache.spark.Logging
  * @param nCols number of columns. A non-positive value means unknown, and then the number of
  *              columns will be determined by the size of the first row.
  */
+@Experimental
 class RowMatrix(
     val rows: RDD[Vector],
     private var nRows: Long,