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[SPARK-23334][SQL][PYTHON] Fix pandas_udf with return type StringType() to handle str type properly in Python 2. #20507

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[SPARK-23334][SQL][PYTHON] Fix pandas_udf with return type StringType() to handle str type properly in Python 2. #20507

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Fix pandas_udf with return type StringType() to handle str type prope…
ueshin Feb 5, 2018
06ae568
Address comments.
ueshin Feb 5, 2018
b3d5209
Address a comment.
ueshin Feb 6, 2018
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4 changes: 4 additions & 0 deletions python/pyspark/serializers.py
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Original file line number Diff line number Diff line change
Expand Up @@ -230,6 +230,10 @@ def create_array(s, t):
s = _check_series_convert_timestamps_internal(s.fillna(0), timezone)
# TODO: need cast after Arrow conversion, ns values cause error with pandas 0.19.2
return pa.Array.from_pandas(s, mask=mask).cast(t, safe=False)
elif t is not None and pa.types.is_string(t) and sys.version < '3':
# TODO: need decode before converting to Arrow in Python 2
return pa.Array.from_pandas(s.apply(
lambda v: v.decode("utf-8") if isinstance(v, str) else v), mask=mask, type=t)
return pa.Array.from_pandas(s, mask=mask, type=t)

arrs = [create_array(s, t) for s, t in series]
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9 changes: 9 additions & 0 deletions python/pyspark/sql/tests.py
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Expand Up @@ -3920,6 +3920,15 @@ def test_vectorized_udf_null_string(self):
res = df.select(str_f(col('str')))
self.assertEquals(df.collect(), res.collect())

def test_vectorized_udf_string_in_udf(self):
from pyspark.sql.functions import pandas_udf, col
import pandas as pd
df = self.spark.range(10)
str_f = pandas_udf(lambda x: pd.Series(map(str, x)), StringType())
actual = df.select(str_f(col('id')))
expected = df.select(col('id').cast('string'))
self.assertEquals(expected.collect(), actual.collect())

def test_vectorized_udf_datatype_string(self):
from pyspark.sql.functions import pandas_udf, col
df = self.spark.range(10).select(
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