Github user BryanCutler commented on a diff in the pull request:
https://github.com/apache/spark/pull/18664#discussion_r144166470
--- Diff: python/pyspark/serializers.py ---
@@ -223,12 +224,13 @@ def _create_batch(series):
# If a nullable integer series has been promoted to floating point
with NaNs, need to cast
# NOTE: this is not necessary with Arrow >= 0.7
def cast_series(s, t):
- if t is None or s.dtype == t.to_pandas_dtype():
+ if t is None or s.dtype == t.to_pandas_dtype() or type(t) ==
pa.TimestampType:
--- End diff --
for timestamps, pyarrow.DataType.to_pandas_dtype will be a "datetime64[us]"
while s.dtype is "datetime64[ns]" so they are not equal but trying to use
`astype` will give an error. So I think this is fine.
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