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[SPARK-31441][PYSPARK][SQL][2.4] Support duplicated column names for toPandas with arrow execution. #28221

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[SPARK-31441][PYSPARK][SQL][2.4] Support duplicated column names for toPandas with arrow execution. #28221

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6 changes: 5 additions & 1 deletion python/pyspark/sql/dataframe.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2127,10 +2127,14 @@ def toPandas(self):
from pyspark.sql.types import _check_dataframe_convert_date, \
_check_dataframe_localize_timestamps
import pyarrow
batches = self._collectAsArrow()
# Rename columns to avoid duplicated column names.
tmp_column_names = ['col_{}'.format(i) for i in range(len(self.columns))]
batches = self.toDF(*tmp_column_names)._collectAsArrow()
if len(batches) > 0:
table = pyarrow.Table.from_batches(batches)
pdf = table.to_pandas()
# Rename back to the original column names.
pdf.columns = self.columns
pdf = _check_dataframe_convert_date(pdf, self.schema)
return _check_dataframe_localize_timestamps(pdf, timezone)
else:
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27 changes: 21 additions & 6 deletions python/pyspark/sql/tests.py
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Expand Up @@ -3296,6 +3296,19 @@ def test_to_pandas(self):
self.assertEquals(types[4], np.object) # datetime.date
self.assertEquals(types[5], 'datetime64[ns]')

@unittest.skipIf(not _have_pandas, _pandas_requirement_message)
def test_to_pandas_with_duplicated_column_names(self):
import numpy as np

sql = "select 1 v, 1 v"
for arrowEnabled in [False, True]:
with self.sql_conf({"spark.sql.execution.arrow.enabled": arrowEnabled}):
df = self.spark.sql(sql)
pdf = df.toPandas()
types = pdf.dtypes
self.assertEquals(types.iloc[0], np.int32)
self.assertEquals(types.iloc[1], np.int32)

@unittest.skipIf(not _have_pandas, _pandas_requirement_message)
def test_to_pandas_on_cross_join(self):
import numpy as np
Expand All @@ -3307,12 +3320,14 @@ def test_to_pandas_on_cross_join(self):
select explode(sequence(1, 3)) v
) t2
"""
with self.sql_conf({"spark.sql.crossJoin.enabled": True}):
df = self.spark.sql(sql)
pdf = df.toPandas()
types = pdf.dtypes
self.assertEquals(types.iloc[0], np.int32)
self.assertEquals(types.iloc[1], np.int32)
for arrowEnabled in [False, True]:
with self.sql_conf({"spark.sql.crossJoin.enabled": True,
"spark.sql.execution.arrow.enabled": arrowEnabled}):
df = self.spark.sql(sql)
pdf = df.toPandas()
types = pdf.dtypes
self.assertEquals(types.iloc[0], np.int32)
self.assertEquals(types.iloc[1], np.int32)

@unittest.skipIf(_have_pandas, "Required Pandas was found.")
def test_to_pandas_required_pandas_not_found(self):
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