[feature request] Support Time64Type[ns]

[kevinjqliu]

Feature Request / Improvement

Currently Time64Type[ns] (Time64Type with nanosecond precision) is not supported. Only Time64Type[ms] (Time64Type with microsecond precision) is supported.

iceberg-python/pyiceberg/io/pyarrow.py

Lines 1071 to 1072 in d8d509f

	elif isinstance(primitive, pa.Time64Type) and primitive.unit == "us":
	return TimeType()

Also add the ability to downcast, similar to the pa.types.is_timestamp(primitive): branch.

Interestingly Time64Type[ns] is False when evaluating pa.types.is_timestamp(primitive).

[zaryab-ali]

@kevinjqliu if the issue is still available can you assign it to me please

[kevinjqliu]

@zaryab-ali assigned to you

[zaryab-ali]

@kevinjqliu can you please review my PR and let me know if i made a mistake (please check with extra caution as it is my first contribution to any open source project)

[zaryab-ali]

@kevinjqliu did someone else solve the issue while it was still assigned to me??? or is this still open??? because i just made the changes and added the test case

[kevinjqliu]

@zaryab-ali Hey, sorry about the confusion. I did not see that 2 PRs were opened for the same issue. I just assumed it was from the same person.
The issue is still open, #1188, #1206, and #1215 are all trying to address it. Since it's already assigned to you, I'll take a look at #1215.

Hey @JE-Chen, since this issue is already assigned to @zaryab-ali, would you mind collaborating with him on it?

[github-actions]

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[0x26res]

| Interestingly Time64Type[ns] is False when evaluating pa.types.is_timestamp(primitive).

I think this is expected, time64/32 is not a timestamp but a time.

>>> import pyarrow as pa
>>> pa.types.is_timestamp(pa.time64("ns"))
False
>>> pa.types.is_time(pa.time64("ns"))
True

[jaimeferj]

Hi, I see there’s an existing PR #1252 for this issue but it looks stale.
If there’s no objection, I can pick this up and open a new PR to move it forward, referencing the original work.
Please let me know if that’s okay.

[romanzdk]

We would love to have this feature!