[ARROW-6492] [Python] file written with latest fastparquet cannot be read with latest pyarrow

• Type: Bug
• Status: Resolved
• Priority: Major
• Resolution: Fixed
• Fix Version/s: 0.15.0
• Component/s: Python
• Labels: parquet pull-request-available
• External issue URL: https://github.com/apache/arrow/issues/22861
• Assignee: Joris Van den Bossche
• Reporter: Joris Van den Bossche
• Created: 09/Sep/19 12:39
• Updated: 11/Jan/23 07:47
• Resolved: 09/Sep/19 20:33

Description

From report on the pandas issue tracker: https://github.com/pandas-dev/pandas/issues/28252

With the latest released versions of fastparquet (0.3.2) and pyarrow (0.14.1), writing a file with pandas using the fastparquet engine cannot be read with the pyarrow engine:

df = pd.DataFrame({'A': [1, 2, 3]})
df.to_parquet("test.parquet", engine="fastparquet", compression=None)                                                                                                                                     
pd.read_parquet("test.parquet", engine="pyarrow")   

gives the following error when reading:

----> 1 pd.read_parquet("test.parquet", engine="pyarrow")

~/miniconda3/lib/python3.7/site-packages/pandas/io/parquet.py in read_parquet(path, engine, columns, **kwargs)
    292 
    293     impl = get_engine(engine)
--> 294     return impl.read(path, columns=columns, **kwargs)

~/miniconda3/lib/python3.7/site-packages/pandas/io/parquet.py in read(self, path, columns, **kwargs)
    123         kwargs["use_pandas_metadata"] = True
    124         result = self.api.parquet.read_table(
--> 125             path, columns=columns, **kwargs
    126         ).to_pandas()
    127         if should_close:

~/miniconda3/lib/python3.7/site-packages/pyarrow/array.pxi in pyarrow.lib._PandasConvertible.to_pandas()

~/miniconda3/lib/python3.7/site-packages/pyarrow/table.pxi in pyarrow.lib.Table._to_pandas()

~/miniconda3/lib/python3.7/site-packages/pyarrow/pandas_compat.py in table_to_blockmanager(options, table, categories, ignore_metadata)
    642         column_indexes = pandas_metadata.get('column_indexes', [])
    643         index_descriptors = pandas_metadata['index_columns']
--> 644         table = _add_any_metadata(table, pandas_metadata)
    645         table, index = _reconstruct_index(table, index_descriptors,
    646                                           all_columns)

~/miniconda3/lib/python3.7/site-packages/pyarrow/pandas_compat.py in _add_any_metadata(table, pandas_metadata)
    965                 raw_name = 'None'
    966 
--> 967         idx = schema.get_field_index(raw_name)
    968         if idx != -1:
    969             if col_meta['pandas_type'] == 'datetimetz':

~/miniconda3/lib/python3.7/site-packages/pyarrow/types.pxi in pyarrow.lib.Schema.get_field_index()

~/miniconda3/lib/python3.7/site-packages/pyarrow/lib.cpython-37m-x86_64-linux-gnu.so in string.from_py.__pyx_convert_string_from_py_std__in_string()

TypeError: expected bytes, dict found

Issue Links

• links to: GitHub Pull Request #5331