Raphael Taylor-Davies created ARROW-16184: ---------------------------------------------
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 -- This message was sent by Atlassian Jira (v8.20.1#820001)