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 <sand...@techaddict.me> Closes #13202 from techaddict/SPARK-15414. (cherry picked from commit ef43a5fe51614eecce2d144cc13b33004a47533a) Signed-off-by: Xiangrui Meng <m...@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 <sand...@techaddict.me> Authored: Thu May 19 17:24:42 2016 -0700 Committer: Xiangrui Meng <m...@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) } } --------------------------------------------------------------------- To unsubscribe, e-mail: commits-unsubscr...@spark.apache.org For additional commands, e-mail: commits-h...@spark.apache.org
