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[SPARK-28003][PYTHON] Allow NaT values when creating Spark dataframe from pandas with Arrow #24844

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[SPARK-28003][PYTHON] Allow NaT values when creating Spark dataframe from pandas with Arrow #24844

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af6c2db
Fix NaT bug with Arrow
icexelloss Jun 11, 2019
1c5b8a7
Simplify test cases; Test both arrow and non arrow path
icexelloss Jun 12, 2019
ae144e1
Add Jira numbers
icexelloss Jun 13, 2019
60733ac
Refactor to forloop
icexelloss Jun 13, 2019
bda31b5
Use _createDataFrame_toggle
icexelloss Jun 13, 2019
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3 changes: 1 addition & 2 deletions python/pyspark/serializers.py
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Original file line number Diff line number Diff line change
Expand Up @@ -296,8 +296,7 @@ def create_array(s, t):
mask = s.isnull()
# Ensure timestamp series are in expected form for Spark internal representation
if t is not None and pa.types.is_timestamp(t):
s = _check_series_convert_timestamps_internal(s.fillna(0), self._timezone)

s = _check_series_convert_timestamps_internal(s, self._timezone)
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@icexelloss icexelloss Jun 11, 2019

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Removing this doesn't fail existing tests. @BryanCutler do you remember why are we doing fillna(0) here?

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@BryanCutler BryanCutler Jun 12, 2019

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I believe it was due to a Pandas error, most likely because we were testing with 0.19.2 at the time. Can you manually run some tests with different Pandas versions? It will be best to test with older versions, but it might be kind of hard to get 0.19.2 working with pyarrow 0.12.1 though..

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@icexelloss icexelloss Jun 12, 2019 •
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Yeah pandas 0.19.2 doesn't work with pyarrow 0.12. I cannot run arrow tests with pandas 0.19.2 anymore.

Since we are requiring min arrow version to be 0.12, it means pandas version 0.19.2 is not supported if the user wants to use Arrow.

try:
array = pa.Array.from_pandas(s, mask=mask, type=t, safe=self._safecheck)
except pa.ArrowException as e:
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9 changes: 9 additions & 0 deletions python/pyspark/sql/tests/test_arrow.py
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Expand Up @@ -383,6 +383,15 @@ def test_timestamp_dst(self):
assert_frame_equal(pdf, df_from_python.toPandas())
assert_frame_equal(pdf, df_from_pandas.toPandas())

# Regression test for SPARK-28003
def test_timestamp_nat(self):
dt = [pd.NaT, pd.Timestamp('2019-06-11'), None] * 100
pdf = pd.DataFrame({'time': dt})
df_no_arrow, df_arrow = self._createDataFrame_toggle(pdf)

assert_frame_equal(pdf, df_no_arrow.toPandas())
assert_frame_equal(pdf, df_arrow.toPandas())

def test_toPandas_batch_order(self):

def delay_first_part(partition_index, iterator):
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