Loading local datasets got strangely stuck
Yesterday I waited for more than 12 hours to make sure it was really **stuck** instead of proceeding too slow. I've had similar weird issues with `load_dataset` as well. Not multiple files, but dataset is quite big, about 50G.
### Describe the bug

I try to use `load_dataset()` to load several local `.jsonl` files as a dataset. Every line of these files is a json structure only containing one key `text` (yeah it is a dataset for NLP model). The code snippet is as:
```python
ds = load_dataset("json", data_files=LIST_OF_FILE_PATHS, num_proc=16)['train']
```
However, I found that the loading process can get stuck -- the progress bar `Generating train split` no more proceed. When I was trying to find the cause and solution, I found a really strange behavior. If I load the dataset in this way:
```python
dlist = list()
for _ in LIST_OF_FILE_PATHS:
    dlist.append(load_dataset("json", data_files=_)['train'])
ds = concatenate_datasets(dlist)
```
I can actually successfully load all the files despite its slow speed. But if I load them in batch like above, things go wrong. I did try to use Control-C to trace the stuck point but the program cannot be terminated in this way when `num_proc` is set to `None`. The only thing I can do is use Control-Z to hang it up then kill it. If I use more than 2 cpus, a Control-C would simply cause the following error:
```bash
^C
Process ForkPoolWorker-1:
Traceback (most recent call last):
  File "/usr/local/lib/python3.10/dist-packages/multiprocess/process.py", line 314, in _bootstrap
    self.run()
  File "/usr/local/lib/python3.10/dist-packages/multiprocess/process.py", line 108, in run
    self._target(*self._args, **self._kwargs)
  File "/usr/local/lib/python3.10/dist-packages/multiprocess/pool.py", line 114, in worker
    task = get()
  File "/usr/local/lib/python3.10/dist-packages/multiprocess/queues.py", line 368, in get
    res = self._reader.recv_bytes()
  File "/usr/local/lib/python3.10/dist-packages/multiprocess/connection.py", line 224, in recv_bytes
    buf = self._recv_bytes(maxlength)
  File "/usr/local/lib/python3.10/dist-packages/multiprocess/connection.py", line 422, in _recv_bytes
    buf = self._recv(4)
  File "/usr/local/lib/python3.10/dist-packages/multiprocess/connection.py", line 387, in _recv
    chunk = read(handle, remaining)
KeyboardInterrupt
Generating train split: 92431 examples [01:23, 1104.25 examples/s]  
Traceback (most recent call last):
  File "/usr/local/lib/python3.10/dist-packages/datasets/utils/py_utils.py", line 1373, in iflatmap_unordered
    yield queue.get(timeout=0.05)
  File "<string>", line 2, in get
  File "/usr/local/lib/python3.10/dist-packages/multiprocess/managers.py", line 818, in _callmethod
    kind, result = conn.recv()
  File "/usr/local/lib/python3.10/dist-packages/multiprocess/connection.py", line 258, in recv
    buf = self._recv_bytes()
  File "/usr/local/lib/python3.10/dist-packages/multiprocess/connection.py", line 422, in _recv_bytes
    buf = self._recv(4)
  File "/usr/local/lib/python3.10/dist-packages/multiprocess/connection.py", line 387, in _recv
    chunk = read(handle, remaining)
KeyboardInterrupt

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/mnt/data/liyongyuan/source/batch_load.py", line 11, in <module>
    a = load_dataset(
  File "/usr/local/lib/python3.10/dist-packages/datasets/load.py", line 2133, in load_dataset
    builder_instance.download_and_prepare(
  File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 954, in download_and_prepare
    self._download_and_prepare(
  File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 1049, in _download_and_prepare
    self._prepare_split(split_generator, **prepare_split_kwargs)
  File "/usr/local/lib/python3.10/dist-packages/datasets/builder.py", line 1842, in _prepare_split
    for job_id, done, content in iflatmap_unordered(
  File "/usr/local/lib/python3.10/dist-packages/datasets/utils/py_utils.py", line 1387, in iflatmap_unordered
    [async_result.get(timeout=0.05) for async_result in async_results]
  File "/usr/local/lib/python3.10/dist-packages/datasets/utils/py_utils.py", line 1387, in <listcomp>
    [async_result.get(timeout=0.05) for async_result in async_results]
  File "/usr/local/lib/python3.10/dist-packages/multiprocess/pool.py", line 770, in get
    raise TimeoutError
multiprocess.context.TimeoutError
```
I have validated the basic correctness of these `.jsonl` files. They are correctly formatted (or they cannot be loaded singly by `load_dataset`) though some of the json may contain too long text (more than 1e7 characters). I do not know if this could be the problem. And there should not be any bottleneck in system's resource. The whole dataset is ~300GB, and I am using a cloud server with plenty of storage and 1TB ram. 
Thanks for your efforts and patience! Any suggestion or help would be appreciated.

### Steps to reproduce the bug

1. use load_dataset() with `data_files = LIST_OF_FILES`

### Expected behavior

All the files should be smoothly loaded. 

### Environment info

- Datasets: A private dataset. ~2500 `.jsonl` files. ~300GB in total. Each json structure only contains one key: `text`. Format checked.
- `datasets` version: 2.14.2
- Platform: Linux-4.19.91-014.kangaroo.alios7.x86_64-x86_64-with-glibc2.35
- Python version: 3.10.6
- Huggingface_hub version: 0.15.1
- PyArrow version: 10.0.1.dev0+ga6eabc2b.d20230609
- Pandas version: 1.5.2