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[SPARK-49387][PYTHON] Fix type hint for accuracy in percentile_approx and approx_percentile #47869

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[SPARK-49387][PYTHON] Fix type hint for accuracy in percentile_approx and approx_percentile #47869

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4 changes: 2 additions & 2 deletions python/pyspark/sql/connect/functions/builtin.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1223,7 +1223,7 @@ def percentile(
def percentile_approx(
col: "ColumnOrName",
percentage: Union[Column, float, Sequence[float], Tuple[float]],
accuracy: Union[Column, float] = 10000,
accuracy: Union[Column, int] = 10000,
) -> Column:
percentage = lit(list(percentage)) if isinstance(percentage, (list, tuple)) else lit(percentage)
return _invoke_function_over_columns("percentile_approx", col, percentage, lit(accuracy))
Expand All @@ -1235,7 +1235,7 @@ def percentile_approx(
def approx_percentile(
col: "ColumnOrName",
percentage: Union[Column, float, Sequence[float], Tuple[float]],
accuracy: Union[Column, float] = 10000,
accuracy: Union[Column, int] = 10000,
) -> Column:
percentage = lit(list(percentage)) if isinstance(percentage, (list, tuple)) else lit(percentage)
return _invoke_function_over_columns("approx_percentile", col, percentage, lit(accuracy))
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8 changes: 4 additions & 4 deletions python/pyspark/sql/functions/builtin.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6339,7 +6339,7 @@ def percentile(
def percentile_approx(
col: "ColumnOrName",
percentage: Union[Column, float, Sequence[float], Tuple[float]],
accuracy: Union[Column, float] = 10000,
accuracy: Union[Column, int] = 10000,
) -> Column:
"""Returns the approximate `percentile` of the numeric column `col` which is the smallest value
in the ordered `col` values (sorted from least to greatest) such that no more than `percentage`
Expand All @@ -6360,7 +6360,7 @@ def percentile_approx(
When percentage is an array, each value of the percentage array must be between 0.0 and 1.0.
In this case, returns the approximate percentile array of column col
at the given percentage array.
accuracy : :class:`~pyspark.sql.Column` or float
accuracy : :class:`~pyspark.sql.Column` or int
is a positive numeric literal which controls approximation accuracy
at the cost of memory. Higher value of accuracy yields better accuracy,
1.0/accuracy is the relative error of the approximation. (default: 10000).
Expand Down Expand Up @@ -6397,7 +6397,7 @@ def percentile_approx(
def approx_percentile(
col: "ColumnOrName",
percentage: Union[Column, float, Sequence[float], Tuple[float]],
accuracy: Union[Column, float] = 10000,
accuracy: Union[Column, int] = 10000,
) -> Column:
"""Returns the approximate `percentile` of the numeric column `col` which is the smallest value
in the ordered `col` values (sorted from least to greatest) such that no more than `percentage`
Expand All @@ -6414,7 +6414,7 @@ def approx_percentile(
When percentage is an array, each value of the percentage array must be between 0.0 and 1.0.
In this case, returns the approximate percentile array of column col
at the given percentage array.
accuracy : :class:`~pyspark.sql.Column` or float
accuracy : :class:`~pyspark.sql.Column` or int
is a positive numeric literal which controls approximation accuracy
at the cost of memory. Higher value of accuracy yields better accuracy,
1.0/accuracy is the relative error of the approximation. (default: 10000).
Expand Down