MaxGekk commented on code in PR #39239:
URL: https://github.com/apache/spark/pull/39239#discussion_r1058433158
##########
python/pyspark/sql/types.py:
##########
@@ -276,7 +276,15 @@ def toInternal(self, dt: datetime.datetime) -> int:
def fromInternal(self, ts: int) -> datetime.datetime:
if ts is not None:
# using int to avoid precision loss in float
- return datetime.datetime.fromtimestamp(ts //
1000000).replace(microsecond=ts % 1000000)
+ return (
+ datetime.datetime
+ # Set the time zone to UTC because the TIMESTAMP type stores
timestamps
+ # as the number of microseconds from the epoch of
1970-01-01T00:00:00.000000Z
+ # in the UTC time zone.
+ .fromtimestamp(ts // 1000000,
tz=datetime.timezone.utc).replace(
Review Comment:
> TimestampNTZType is a UTC time.
This is NO time zone timestamp that means local or logical timestamp. For
example, 2022-12-28 20:23:31 could be in UTC, America/Los_Angeles and
Europe/Amsterdam. The same local timestamp represents 3 different physical
timestamps. So, this type matches precisely to
```python
datetime.datetime(year, month, day, hour, minute, second, microsecond,
tzinfo=None)
```
> My understanding was that TimestampType is a local time per Spark's
session timezone ...
Yep, this one must be bound to a time zone:
```python
datetime.datetime(year, month, day, hour, minute, second, microsecond,
tzinfo=ZoneInfo('US/Pacific'))
```
or
```python
datetime.datetime(year, month, day, hour, minute, second, microsecond,
tzinfo=datetime.timezone.utc)
```
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