Title: Error loading json dataset with multiple splits if keys in nested dicts have a different order
Author: dthulke (NONE)
State: closed
Created: 2021-10-15T09:33:25Z
Labels: bug

## Describe the bug
Loading a json dataset with multiple splits that have nested dicts with keys in different order results in the error below.

If the keys in the nested dicts always have the same order or even if you just load a single split in which the nested dicts don't have the same order, everything works fine.

## Steps to reproduce the bug
Create two json files:

train.json
```
{"a": {"c": 8, "b": 5}}
{"a": {"b": 7, "c": 6}}
```

test.json
```
{"a": {"b": 1, "c": 2}}
{"a": {"b": 3, "c": 4}}
```

```python
from datasets import load_dataset
# Loading the files individually works (even though the keys in train.json don't have the same order)
load_dataset('json', data_files={"test": "test.json"})
load_dataset('json', data_files={"train": "train.json"})
# Loading both splits fails
load_dataset('json', data_files={"train": "train.json", "test": "test.json"})
```

## Expected results
Loading both splits should not give an error whether the nested dicts are have the same order or not.

## Actual results
```
>>> load_dataset('json', data_files={"train": "train.json", "test": "test.json"})
Using custom data configuration default-f1bc76fd07398c4c
Downloading and preparing dataset json/default to /home/dthulke/.cache/huggingface/datasets/json/default-f1bc76fd07398c4c/0.0.0/c2d554c3377ea79c7664b93dc65d0803b45e3279000f993c7bfd18937fd7f426...
100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 8839.42it/s]
100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 477.82it/s]
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/dthulke/venvs/venv_torch_transformers/lib/python3.6/site-packages/datasets/load.py", line 1632, in load_dataset
    use_auth_token=use_auth_token,
  File "/home/dthulke/venvs/venv_torch_transformers/lib/python3.6/site-packages/datasets/builder.py", line 608, in download_and_prepare
    dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
  File "/home/dthulke/venvs/venv_torch_transformers/lib/python3.6/site-packages/datasets/builder.py", line 697, in _download_and_prepare
    self._prepare_split(split_generator, **prepare_split_kwargs)
  File "/home/dthulke/venvs/venv_torch_transformers/lib/python3.6/site-packages/datasets/builder.py", line 1159, in _prepare_split
    writer.write_table(table)
  File "/home/dthulke/venvs/venv_torch_transformers/lib/python3.6/site-packages/datasets/arrow_writer.py", line 428, in write_table
    pa_table = pa.Table.from_arrays([pa_table[name] for name in self._schema.names], schema=self._schema)
  File "pyarrow/table.pxi", line 1596, in pyarrow.lib.Table.from_arrays
  File "pyarrow/table.pxi", line 592, in pyarrow.lib._sanitize_arrays
  File "pyarrow/array.pxi", line 329, in pyarrow.lib.asarray
  File "pyarrow/table.pxi", line 277, in pyarrow.lib.ChunkedArray.cast
  File "/home/dthulke/venvs/venv_torch_transformers/lib/python3.6/site-packages/pyarrow/compute.py", line 297, in cast
    return call_function("cast", [arr], options)
  File "pyarrow/_compute.pyx", line 527, in pyarrow._compute.call_function
  File "pyarrow/_compute.pyx", line 337, in pyarrow._compute.Function.call
  File "pyarrow/error.pxi", line 143, in pyarrow.lib.pyarrow_internal_check_status
  File "pyarrow/error.pxi", line 120, in pyarrow.lib.check_status
pyarrow.lib.ArrowNotImplementedError: Unsupported cast from struct<b: int64, c: int64> to struct using function cast_struct
```

## Environment info
- `datasets` version: 1.13.2
- Platform: Linux-4.15.0-147-generic-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.6.9
- PyArrow version: 5.0.0

Comments:
Hi, 

even Pandas, which is less strict compared to PyArrow when it comes to reading JSON, doesn't support different orderings:
```python
import io
import pandas as pd

s = """
{"a": {"c": 8, "b": 5}}
{"a": {"b": 7, "c": 6}}
"""

buffer = io.StringIO(s)
df = pd.read_json(buffer, lines=True)

print(df.shape[0]) # 0
```

So we can't even fall back to Pandas in such cases.

It seems the only option is a script that recursively re-orders fields to enforce deterministic order:
```python
with open("train.json", "r") as fin:
    with open("train_reordered.json", "w") as fout:
        for line in fin:
            obj_jsonl = json.loads(line.strip())
            fout.write(json.dumps(obj_jsonl, sort_keys=True) + "\n")
```

Fixed in #3575, so I'm closing this issue.