In [1]: df = pd.DataFrame({"dates": list(pd.date_range("2012-01-01", periods=2, freq="D")) * 5, "col": range(10)})
In [2]: table = pa.table(df)
In [8]: part = ds.partitioning(table.select(["dates"]).schema, flavor="hive")
In [9]: ds.write_dataset(table, "test_partition_timestamp", format="parquet", partitioning=part)
In [10]: !ls test_partition_timestamp/
'dates=1325376000000000000' 'dates=1325462400000000000'
Same happens for non-ns timestamp types.
(didn't directly find an existing issue about it)
Reporter: Joris Van den Bossche / @jorisvandenbossche
Related issues:
Note: This issue was originally created as ARROW-11378. Please see the migration documentation for further details.