Raphael Taylor-Davies created ARROW-16184:
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Summary: [Python] Incorrect Timestamp Unit in Embedded Arrow
Schema Within Parquet
Key: ARROW-16184
URL: https://issues.apache.org/jira/browse/ARROW-16184
Project: Apache Arrow
Issue Type: Bug
Reporter: Raphael Taylor-Davies
As pointed out in https://issues.apache.org/jira/browse/ARROW-2429 the
following code results in the schema changing when reading/writing a parquet
file.
#!/usr/bin/env pythonimport pyarrow as paimport pyarrow.parquet as pqimport
pandas as pd# create DataFrame with a datetime columndf =
pd.DataFrame({'created': ['2018-04-04T10:14:14Z']})
df['created'] = pd.to_datetime(df['created'])# create Arrow table from
DataFrametable = pa.Table.from_pandas(df, preserve_index=False)# write the
table as a parquet file, then read it back againpq.write_table(table,
'foo.parquet')
table2 = pq.read_table('foo.parquet')print(table.schema[0]) #
pyarrow.Field<created: timestamp[ns]> (nanosecond units)print(table2.schema[0])
# pyarrow.Field<created: timestamp[us]> (microsecond units)
This was closed as a limitation of the parquet 1.x format for representing
nanosecond timestamps. This is fine, however, the arrow schema embedded within
the parquet metadata still lists the data as being a nanosecond array.
This was discovered as part of the investigation into a bug report on the
arrow-rs parquet implementation - https://github.com/apache/arrow-rs/issues/1459
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