beliefer commented on code in PR #39017:
URL: https://github.com/apache/spark/pull/39017#discussion_r1050418759
##########
python/pyspark/sql/connect/dataframe.py:
##########
@@ -875,6 +877,60 @@ def to_jcols(
melt = unpivot
+ def randomSplit(
+ self,
+ weights: List[float],
+ seed: Optional[int] = None,
+ ) -> List["DataFrame"]:
+ """Randomly splits this :class:`DataFrame` with the provided weights.
+
+ .. versionadded:: 3.4.0
+
+ Parameters
+ ----------
+ weights : list
+ list of doubles as weights with which to split the
:class:`DataFrame`.
+ Weights will be normalized if they don't sum up to 1.0.
+ seed : int, optional
+ The seed for sampling.
+
+ Returns
+ -------
+ list
+ List of DataFrames.
+ """
+ for w in weights:
+ if w < 0.0:
+ raise ValueError("Weights must be positive. Found weight
value: %s" % w)
Review Comment:
More lightweight to check at client.
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