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From m...@apache.org
Subject spark git commit: [SPARK-15414][MLLIB] Make the mllib, ml linalg type conversion APIs public
Date Fri, 20 May 2016 00:24:52 GMT
Repository: spark
Updated Branches:
  refs/heads/branch-2.0 ebf30eddd -> 758253f7c


[SPARK-15414][MLLIB] Make the mllib,ml linalg type conversion APIs public

## What changes were proposed in this pull request?
Open up APIs for converting between new, old linear algebra types (in spark.mllib.linalg):
`Sparse`/`Dense` X `Vector`/`Matrices` `.asML` and `.fromML`

## How was this patch tested?
Existing Tests

Author: Sandeep Singh <sandeep@techaddict.me>

Closes #13202 from techaddict/SPARK-15414.

(cherry picked from commit ef43a5fe51614eecce2d144cc13b33004a47533a)
Signed-off-by: Xiangrui Meng <meng@databricks.com>


Project: http://git-wip-us.apache.org/repos/asf/spark/repo
Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/758253f7
Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/758253f7
Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/758253f7

Branch: refs/heads/branch-2.0
Commit: 758253f7c7493df60e417ed5c3ee360015cfd166
Parents: ebf30ed
Author: Sandeep Singh <sandeep@techaddict.me>
Authored: Thu May 19 17:24:42 2016 -0700
Committer: Xiangrui Meng <meng@databricks.com>
Committed: Thu May 19 17:24:49 2016 -0700

----------------------------------------------------------------------
 .../apache/spark/mllib/linalg/Matrices.scala    | 30 ++++++++++++++------
 .../org/apache/spark/mllib/linalg/Vectors.scala | 30 ++++++++++++++------
 2 files changed, 42 insertions(+), 18 deletions(-)
----------------------------------------------------------------------


http://git-wip-us.apache.org/repos/asf/spark/blob/758253f7/mllib/src/main/scala/org/apache/spark/mllib/linalg/Matrices.scala
----------------------------------------------------------------------
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/linalg/Matrices.scala b/mllib/src/main/scala/org/apache/spark/mllib/linalg/Matrices.scala
index 5c9a112..ee1956c 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/linalg/Matrices.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/linalg/Matrices.scala
@@ -164,7 +164,8 @@ sealed trait Matrix extends Serializable {
    * Convert this matrix to the new mllib-local representation.
    * This does NOT copy the data; it copies references.
    */
-  private[spark] def asML: newlinalg.Matrix
+  @Since("2.0.0")
+  def asML: newlinalg.Matrix
 }
 
 private[spark] class MatrixUDT extends UserDefinedType[Matrix] {
@@ -427,7 +428,8 @@ class DenseMatrix @Since("1.3.0") (
     }
   }
 
-  private[spark] override def asML: newlinalg.DenseMatrix = {
+  @Since("2.0.0")
+  override def asML: newlinalg.DenseMatrix = {
     new newlinalg.DenseMatrix(numRows, numCols, values, isTransposed)
   }
 }
@@ -527,8 +529,11 @@ object DenseMatrix {
     matrix
   }
 
-  /** Convert new linalg type to spark.mllib type.  Light copy; only copies references */
-  private[spark] def fromML(m: newlinalg.DenseMatrix): DenseMatrix = {
+  /**
+   * Convert new linalg type to spark.mllib type.  Light copy; only copies references
+   */
+  @Since("2.0.0")
+  def fromML(m: newlinalg.DenseMatrix): DenseMatrix = {
     new DenseMatrix(m.numRows, m.numCols, m.values, m.isTransposed)
   }
 }
@@ -740,7 +745,8 @@ class SparseMatrix @Since("1.3.0") (
     }
   }
 
-  private[spark] override def asML: newlinalg.SparseMatrix = {
+  @Since("2.0.0")
+  override def asML: newlinalg.SparseMatrix = {
     new newlinalg.SparseMatrix(numRows, numCols, colPtrs, rowIndices, values, isTransposed)
   }
 }
@@ -918,8 +924,11 @@ object SparseMatrix {
     }
   }
 
-  /** Convert new linalg type to spark.mllib type.  Light copy; only copies references */
-  private[spark] def fromML(m: newlinalg.SparseMatrix): SparseMatrix = {
+  /**
+   * Convert new linalg type to spark.mllib type.  Light copy; only copies references
+   */
+  @Since("2.0.0")
+  def fromML(m: newlinalg.SparseMatrix): SparseMatrix = {
     new SparseMatrix(m.numRows, m.numCols, m.colPtrs, m.rowIndices, m.values, m.isTransposed)
   }
 }
@@ -1205,8 +1214,11 @@ object Matrices {
     }
   }
 
-  /** Convert new linalg type to spark.mllib type.  Light copy; only copies references */
-  private[spark] def fromML(m: newlinalg.Matrix): Matrix = m match {
+  /**
+   * Convert new linalg type to spark.mllib type.  Light copy; only copies references
+   */
+  @Since("2.0.0")
+  def fromML(m: newlinalg.Matrix): Matrix = m match {
     case dm: newlinalg.DenseMatrix =>
       DenseMatrix.fromML(dm)
     case sm: newlinalg.SparseMatrix =>

http://git-wip-us.apache.org/repos/asf/spark/blob/758253f7/mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala
----------------------------------------------------------------------
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala b/mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala
index 1f1cfa0..7ebcd29 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/linalg/Vectors.scala
@@ -186,7 +186,8 @@ sealed trait Vector extends Serializable {
    * Convert this vector to the new mllib-local representation.
    * This does NOT copy the data; it copies references.
    */
-  private[spark] def asML: newlinalg.Vector
+  @Since("2.0.0")
+  def asML: newlinalg.Vector
 }
 
 /**
@@ -581,8 +582,11 @@ object Vectors {
   /** Max number of nonzero entries used in computing hash code. */
   private[linalg] val MAX_HASH_NNZ = 128
 
-  /** Convert new linalg type to spark.mllib type.  Light copy; only copies references */
-  private[spark] def fromML(v: newlinalg.Vector): Vector = v match {
+  /**
+   * Convert new linalg type to spark.mllib type.  Light copy; only copies references
+   */
+  @Since("2.0.0")
+  def fromML(v: newlinalg.Vector): Vector = v match {
     case dv: newlinalg.DenseVector =>
       DenseVector.fromML(dv)
     case sv: newlinalg.SparseVector =>
@@ -704,7 +708,8 @@ class DenseVector @Since("1.0.0") (
     compact(render(jValue))
   }
 
-  private[spark] override def asML: newlinalg.DenseVector = {
+  @Since("2.0.0")
+  override def asML: newlinalg.DenseVector = {
     new newlinalg.DenseVector(values)
   }
 }
@@ -716,8 +721,11 @@ object DenseVector {
   @Since("1.3.0")
   def unapply(dv: DenseVector): Option[Array[Double]] = Some(dv.values)
 
-  /** Convert new linalg type to spark.mllib type.  Light copy; only copies references */
-  private[spark] def fromML(v: newlinalg.DenseVector): DenseVector = {
+  /**
+   * Convert new linalg type to spark.mllib type.  Light copy; only copies references
+   */
+  @Since("2.0.0")
+  def fromML(v: newlinalg.DenseVector): DenseVector = {
     new DenseVector(v.values)
   }
 }
@@ -911,7 +919,8 @@ class SparseVector @Since("1.0.0") (
     compact(render(jValue))
   }
 
-  private[spark] override def asML: newlinalg.SparseVector = {
+  @Since("2.0.0")
+  override def asML: newlinalg.SparseVector = {
     new newlinalg.SparseVector(size, indices, values)
   }
 }
@@ -922,8 +931,11 @@ object SparseVector {
   def unapply(sv: SparseVector): Option[(Int, Array[Int], Array[Double])] =
     Some((sv.size, sv.indices, sv.values))
 
-  /** Convert new linalg type to spark.mllib type.  Light copy; only copies references */
-  private[spark] def fromML(v: newlinalg.SparseVector): SparseVector = {
+  /**
+   * Convert new linalg type to spark.mllib type.  Light copy; only copies references
+   */
+  @Since("2.0.0")
+  def fromML(v: newlinalg.SparseVector): SparseVector = {
     new SparseVector(v.size, v.indices, v.values)
   }
 }


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