Repository: spark Updated Branches: refs/heads/branch-1.4 ab62d73dd -> 7b5dffb80
[SPARK-7911] [MLLIB] A workaround for VectorUDT serialize (or deserialize) being called multiple times ~~A PythonUDT shouldn't be serialized into external Scala types in PythonRDD. I'm not sure whether this should fix one of the bugs related to SQL UDT/UDF in PySpark.~~ The fix above didn't work. So I added a workaround for this. If a Python UDF is applied to a Python UDT. This will put the Python SQL types as inputs. Still incorrect, but at least it doesn't throw exceptions on the Scala side. davies harsha2010 Author: Xiangrui Meng <m...@databricks.com> Closes #6442 from mengxr/SPARK-7903 and squashes the following commits: c257d2a [Xiangrui Meng] add a workaround for VectorUDT (cherry picked from commit 530efe3e80c62b25c869b85167e00330eb1ddea6) 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/7b5dffb8 Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/7b5dffb8 Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/7b5dffb8 Branch: refs/heads/branch-1.4 Commit: 7b5dffb80288cb491cd9de9da653a78d800be55b Parents: ab62d73 Author: Xiangrui Meng <m...@databricks.com> Authored: Thu May 28 12:03:46 2015 -0700 Committer: Xiangrui Meng <m...@databricks.com> Committed: Thu May 28 12:03:55 2015 -0700 ---------------------------------------------------------------------- .../org/apache/spark/mllib/linalg/Vectors.scala | 19 ++++++++++++++----- 1 file changed, 14 insertions(+), 5 deletions(-) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/spark/blob/7b5dffb8/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 f6bcdf8..2ffa497 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 @@ -176,27 +176,31 @@ private[spark] class VectorUDT extends UserDefinedType[Vector] { } override def serialize(obj: Any): Row = { - val row = new GenericMutableRow(4) obj match { case SparseVector(size, indices, values) => + val row = new GenericMutableRow(4) row.setByte(0, 0) row.setInt(1, size) row.update(2, indices.toSeq) row.update(3, values.toSeq) + row case DenseVector(values) => + val row = new GenericMutableRow(4) row.setByte(0, 1) row.setNullAt(1) row.setNullAt(2) row.update(3, values.toSeq) + row + // TODO: There are bugs in UDT serialization because we don't have a clear separation between + // TODO: internal SQL types and language specific types (including UDT). UDT serialize and + // TODO: deserialize may get called twice. See SPARK-7186. + case row: Row => + row } - row } override def deserialize(datum: Any): Vector = { datum match { - // TODO: something wrong with UDT serialization - case v: Vector => - v case row: Row => require(row.length == 4, s"VectorUDT.deserialize given row with length ${row.length} but requires length == 4") @@ -211,6 +215,11 @@ private[spark] class VectorUDT extends UserDefinedType[Vector] { val values = row.getAs[Iterable[Double]](3).toArray new DenseVector(values) } + // TODO: There are bugs in UDT serialization because we don't have a clear separation between + // TODO: internal SQL types and language specific types (including UDT). UDT serialize and + // TODO: deserialize may get called twice. See SPARK-7186. + case v: Vector => + v } } --------------------------------------------------------------------- To unsubscribe, e-mail: commits-unsubscr...@spark.apache.org For additional commands, e-mail: commits-h...@spark.apache.org
