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[SPARK-7156][SQL] Addressed follow up comments for randomSplit #5795

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[SPARK-7156][SQL] Addressed follow up comments for randomSplit #5795

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1ea456f
Addressed follow up comments
brkyvz Apr 29, 2015
369c522
changed wording a little
brkyvz Apr 29, 2015
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7 changes: 6 additions & 1 deletion python/pyspark/sql/dataframe.py
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Original file line number Diff line number Diff line change
Expand Up @@ -437,6 +437,10 @@ def sample(self, withReplacement, fraction, seed=None):
def randomSplit(self, weights, seed=None):
"""Randomly splits this :class:`DataFrame` with the provided weights.

:param weights: list of doubles as weights with which to split the DataFrame. Weights will
be normalized if they don't sum up to 1.0.
:param seed: The seed for sampling.

>>> splits = df4.randomSplit([1.0, 2.0], 24)
>>> splits[0].count()
1
Expand All @@ -445,7 +449,8 @@ def randomSplit(self, weights, seed=None):
3
"""
for w in weights:
assert w >= 0.0, "Negative weight value: %s" % w
if w < 0.0:
raise ValueError("Weights must be positive. Found weight value: %s" % w)
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does %s work for numeric value?

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oh i checked on command line and it worked.

seed = seed if seed is not None else random.randint(0, sys.maxsize)
rdd_array = self._jdf.randomSplit(_to_seq(self.sql_ctx._sc, weights), long(seed))
return [DataFrame(rdd, self.sql_ctx) for rdd in rdd_array]
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2 changes: 1 addition & 1 deletion sql/core/src/main/scala/org/apache/spark/sql/DataFrame.scala
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Expand Up @@ -752,7 +752,7 @@ class DataFrame private[sql](
* @param seed Seed for sampling.
* @group dfops
*/
def randomSplit(weights: List[Double], seed: Long): Array[DataFrame] = {
private[spark] def randomSplit(weights: List[Double], seed: Long): Array[DataFrame] = {
randomSplit(weights.toArray, seed)
}

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