[ARROW-1957] [Python] Write nanosecond timestamps using new NANO LogicalType Parquet unit

• Type: Improvement
• Status: Resolved
• Priority: Minor
• Resolution: Fixed
• Affects Version/s: 0.8.0
• Fix Version/s: 0.14.0
• Component/s: Python
• Labels: parquet
• Environment: Python 3.6.4. Mac OSX and CentOS Linux release 7.3.1611. Pandas 0.21.1 .
• External issue URL: https://github.com/apache/arrow/issues/17945
• Assignee: TP Boudreau
• Reporter: Jordan Samuels
• Created: 29/Dec/17 14:55
• Updated: 11/Jan/23 07:18
• Resolved: 19/Jun/19 21:16

Description

The following code

import pyarrow as pa
import pyarrow.parquet as pq
import pandas as pd

n=3
df = pd.DataFrame({'x': range(n)}, index=pd.DatetimeIndex(start='2017-01-01', freq='1n', periods=n))
pq.write_table(pa.Table.from_pandas(df), '/tmp/t.parquet')

results in:

ArrowInvalid: Casting from timestamp[ns] to timestamp[us] would lose data: 1483228800000000001

The desired effect is that we can save nanosecond resolution without losing precision (e.g. conversion to ms). Note that if freq='1u' is used, the code runs properly.

Issue Links

• depends upon: PARQUET-1411 [C++] Upgrade to use LogicalType annotations instead of ConvertedType
• is related to: ARROW-2026 [Python] Cast all timestamp resolutions to INT96 use_deprecated_int96_timestamps=True
• is related to: ARROW-3729 [C++] Support for writing TIMESTAMP_NANOS Parquet metadata