brokenjacobs opened a new issue, #43574:
URL: https://github.com/apache/arrow/issues/43574
### Describe the bug, including details regarding any error messages,
version, and platform.
In pyarrow 17.0.0
When accessing a parquet file using parquet.read_parquet an incompatible
types exception is thrown:
```
>>>
pa.parquet.read_table('gs://****/v1/li191r/ms=2023-01/source_id=9319/li191r_9319_2023-01-02.parquet')
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File
"/Users/sjacobs/tmp/venv/lib/python3.12/site-packages/pyarrow/parquet/core.py",
line 1793, in read_table
dataset = ParquetDataset(
^^^^^^^^^^^^^^^
File
"/Users/sjacobs/tmp/venv/lib/python3.12/site-packages/pyarrow/parquet/core.py",
line 1371, in __init__
self._dataset = ds.dataset(path_or_paths, filesystem=filesystem,
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File
"/Users/sjacobs/tmp/venv/lib/python3.12/site-packages/pyarrow/dataset.py", line
794, in dataset
return _filesystem_dataset(source, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File
"/Users/sjacobs/tmp/venv/lib/python3.12/site-packages/pyarrow/dataset.py", line
486, in _filesystem_dataset
return factory.finish(schema)
^^^^^^^^^^^^^^^^^^^^^^
File "pyarrow/_dataset.pyx", line 3089, in
pyarrow._dataset.DatasetFactory.finish
File "pyarrow/error.pxi", line 155, in
pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
pyarrow.lib.ArrowTypeError: Unable to merge: Field source_id has
incompatible types: string vs dictionary<values=int32, indices=int32, ordered=0>
```
But accessing via dataset works:
```
>>> import pyarrow.dataset as ds
>>> df =
ds.dataset('gs://***/v1/li191r/ms=2023-01/source_id=9319/li191r_9319_2023-01-02.parquet').to_table().to_pandas()
df
>>> df
source_id site_id readout_time voltage
0 9319 SJER 2023-01-02 00:00:00+00:00 0.000159
1 9319 SJER 2023-01-02 00:00:01+00:00 0.000159
2 9319 SJER 2023-01-02 00:00:02+00:00 0.000160
3 9319 SJER 2023-01-02 00:00:03+00:00 0.000159
4 9319 SJER 2023-01-02 00:00:04+00:00 0.000157
... ... ... ... ...
86395 9319 SJER 2023-01-02 23:59:55+00:00 0.000049
86396 9319 SJER 2023-01-02 23:59:56+00:00 0.000048
86397 9319 SJER 2023-01-02 23:59:57+00:00 0.000049
86398 9319 SJER 2023-01-02 23:59:58+00:00 0.000048
86399 9319 SJER 2023-01-02 23:59:59+00:00 0.000048
[86400 rows x 4 columns]
>>>
```
When I revert to pyarrow 16.1.0 both methods work:
```
>>> t =
pa.parquet.read_table('gs://***/v1/li191r/ms=2023-01/source_id=9319/li191r_9319_2023-01-02.parquet')
>>> t.to_pandas()
source_id site_id readout_time voltage
0 9319 SJER 2023-01-02 00:00:00+00:00 0.000159
1 9319 SJER 2023-01-02 00:00:01+00:00 0.000159
2 9319 SJER 2023-01-02 00:00:02+00:00 0.000160
3 9319 SJER 2023-01-02 00:00:03+00:00 0.000159
4 9319 SJER 2023-01-02 00:00:04+00:00 0.000157
... ... ... ... ...
86395 9319 SJER 2023-01-02 23:59:55+00:00 0.000049
86396 9319 SJER 2023-01-02 23:59:56+00:00 0.000048
86397 9319 SJER 2023-01-02 23:59:57+00:00 0.000049
86398 9319 SJER 2023-01-02 23:59:58+00:00 0.000048
86399 9319 SJER 2023-01-02 23:59:59+00:00 0.000048
[86400 rows x 4 columns]
```
I've tried using the fs implementation to list the bucket in 17.0.0 and that
works fine, I have no idea what is wrong here:
```
>>> from pyarrow import fs
>>> gcs = fs.GcsFileSystem()
>>> file_list =
gcs.get_file_info(fs.FileSelector('***t/v1/li191r/ms=2023-01/source_id=9319/',
recursive=False))
>>> file_list
[<FileInfo for
'***/v1/li191r/ms=2023-01/source_id=9319/li191r_9319_2023-01-01.parquet':
type=FileType.File, size=418556>, <FileInfo for
'***/v1/li191r/ms=2023-01/source_id=9319/li191r_9319_2023-01-02.parquet':
type=FileType.File, size=401198>, (and so on) ]
```
### Component(s)
Python
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