henrydavidge commented on a change in pull request #24953:
[SPARK-28140][MLLIB][PYTHON] Accept DataFrames in RowMatrix and
IndexedRowMatrix constructors
URL: https://github.com/apache/spark/pull/24953#discussion_r296945212
##########
File path:
mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala
##########
@@ -1142,12 +1141,21 @@ private[python] class PythonMLLibAPI extends
Serializable {
new RowMatrix(rows.rdd, numRows, numCols)
}
+ def createRowMatrix(df: DataFrame, numRows: Long, numCols: Int): RowMatrix =
{
+ require(df.schema.length == 1 && df.schema.head.dataType.getClass ==
classOf[VectorUDT],
+ "DataFrame must have a single vector type column")
+ new RowMatrix(df.rdd.map { case Row(vector: Vector) => vector }, numRows,
numCols)
Review comment:
I'm not sure I follow what you mean by "doesn't save much". Could you
elaborate?
From Python, you don't need to specify the number of rows / columns. They're
0 by default, which will cause `RowMatrix` to infer the dimensions.
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