Github user wesm commented on a diff in the pull request:
https://github.com/apache/spark/pull/18664#discussion_r145415011
--- Diff: python/pyspark/sql/types.py ---
@@ -1619,11 +1619,39 @@ def to_arrow_type(dt):
arrow_type = pa.decimal(dt.precision, dt.scale)
elif type(dt) == StringType:
arrow_type = pa.string()
+ elif type(dt) == DateType:
+ arrow_type = pa.date32()
+ elif type(dt) == TimestampType:
+ # Timestamps should be in UTC, JVM Arrow timestamps require a
timezone to be read
+ arrow_type = pa.timestamp('us', tz='UTC')
else:
raise TypeError("Unsupported type in conversion to Arrow: " +
str(dt))
return arrow_type
+def _check_dataframe_localize_timestamps(df):
+ """ Convert timezone aware timestamps to timezone-naive in local time
+ """
+ from pandas.types.common import is_datetime64tz_dtype
--- End diff --
I am not sure this is the right public API, @jreback could you advise?
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