Issue: Problems with downloading The Pile
State: closed

### Describe the bug

The downloads in the screenshot seem to be interrupted after some time and the last download throws a "Read timed out" error.

![image](https://user-images.githubusercontent.com/11065386/222687870-ec5fcb65-84e8-467d-9593-4ad7bdac4d50.png)

Here are the downloaded files:
![image](https://user-images.githubusercontent.com/11065386/222688200-454c2288-49e5-4682-96e6-1eb69aca0852.png)

They should be all 14GB like here (https://the-eye.eu/public/AI/pile/train/).

Alternatively, can I somehow download the files by myself and use the datasets preparing script?

### Steps to reproduce the bug

dataset = load_dataset('the_pile', split='train', cache_dir='F:\datasets')

### Expected behavior

The files should be downloaded correctly.

### Environment info

- `datasets` version: 2.10.1
- Platform: Windows-10-10.0.22623-SP0
- Python version: 3.10.5
- PyArrow version: 9.0.0
- Pandas version: 1.4.2

Hi! 


You can specify `download_config=DownloadConfig(resume_download=True))` in `load_dataset` to resume the download when re-running the code after the timeout error:
```python
from datasets import load_dataset, DownloadConfig
dataset = load_dataset('the_pile', split='train', cache_dir='F:\datasets', download_config=DownloadConfig(resume_download=True))
```



@mariosasko , I used your suggestion but its not saving anything , just stops and runs from the same point .
below is the script to download and save on disk .

```
from datasets import load_dataset, DownloadConfig


#load the Pile dataset from Hugging Face Datasets
#dataset = load_dataset('the_pile')
dataset = load_dataset('the_pile', split='train', cache_dir='datasets', download_config=DownloadConfig(resume_download=True))


# save each file in the dataset to disk
for i, example in enumerate(dataset['train']):
    filename = f'pile_file_{i}.json'
    with open(filename, 'w') as f:
        f.write(str(example))

print("Finished saving Pile dataset files to disk.")
```


@mariosasko , it shows nothing in dataset folder

```
 du -sh /mnt/nlp/hugging_face/*
20K     /mnt/nlp/hugging_face/datasets
4.0K    /mnt/nlp/hugging_face/download_pile.py
```


@mariosasko 

```
root@d20f0ab8f4f8:/mnt/hugging_face# python3 download_pile.py
No config specified, defaulting to: the_pile/all
Downloading and preparing dataset the_pile/all to /mnt/hugging_face/datasets/the_pile/all/0.0.0/6fadc480ecb32470826cbf5900a9558b791ce55d5e9a0fdc8ad653e7b64bb349...
Downloading data files:   0%|                                                                                                           | 0/3 [00:00<?, ?it/s]





Downloading data:  70%|████████████████████████████████████████████████████████████████████▊                             | 10.7G/15.2G [12:09<11:53, 6.36MB/s]
Downloading data: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████| 15.2G/15.2G [22:15<00:00, 7.25MB/s]
Downloading data: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████| 15.2G/15.2G [46:17<00:00, 5.48MB/s]
Downloading data:  40%|██████████████████████████████████████▏                                                         | 6.07G/15.3G [50:49<1:17:02, 1.99MB/s]
Traceback (most recent call last):██████████████████████████▊                                                         | 6.07G/15.3G [50:49<25:35:23, 99.9kB/s]
  File "/usr/local/lib/python3.8/dist-packages/urllib3/response.py", line 444, in _error_catcher
    yield
  File "/usr/local/lib/python3.8/dist-packages/urllib3/response.py", line 567, in read
    data = self._fp_read(amt) if not fp_closed else b""
  File "/usr/local/lib/python3.8/dist-packages/urllib3/response.py", line 525, in _fp_read
    data = self._fp.read(chunk_amt)
  File "/usr/lib/python3.8/http/client.py", line 459, in read
    n = self.readinto(b)
  File "/usr/lib/python3.8/http/client.py", line 503, in readinto
    n = self.fp.readinto(b)
  File "/usr/lib/python3.8/socket.py", line 669, in readinto
    return self._sock.recv_into(b)
  File "/usr/lib/python3.8/ssl.py", line 1241, in recv_into
    return self.read(nbytes, buffer)
  File "/usr/lib/python3.8/ssl.py", line 1099, in read
    return self._sslobj.read(len, buffer)
ConnectionResetError: [Errno 104] Connection reset by peer

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/usr/local/lib/python3.8/dist-packages/requests/models.py", line 816, in generate
    yield from self.raw.stream(chunk_size, decode_content=True)
  File "/usr/local/lib/python3.8/dist-packages/urllib3/response.py", line 628, in stream
    data = self.read(amt=amt, decode_content=decode_content)
  File "/usr/local/lib/python3.8/dist-packages/urllib3/response.py", line 593, in read
    raise IncompleteRead(self._fp_bytes_read, self.length_remaining)
  File "/usr/lib/python3.8/contextlib.py", line 131, in __exit__
    self.gen.throw(type, value, traceback)
  File "/usr/local/lib/python3.8/dist-packages/urllib3/response.py", line 461, in _error_catcher
    raise ProtocolError("Connection broken: %r" % e, e)
urllib3.exceptions.ProtocolError: ("Connection broken: ConnectionResetError(104, 'Connection reset by peer')", ConnectionResetError(104, 'Connection reset by peer'))

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "download_pile.py", line 6, in <module>
    dataset = load_dataset('the_pile', split='train', cache_dir='datasets', download_config=DownloadConfig(resume_download=True))
  File "/usr/local/lib/python3.8/dist-packages/datasets/load.py", line 1782, in load_dataset
    builder_instance.download_and_prepare(
  File "/usr/local/lib/python3.8/dist-packages/datasets/builder.py", line 872, in download_and_prepare
    self._download_and_prepare(
  File "/usr/local/lib/python3.8/dist-packages/datasets/builder.py", line 1649, in _download_and_prepare
    super()._download_and_prepare(
  File "/usr/local/lib/python3.8/dist-packages/datasets/builder.py", line 945, in _download_and_prepare
    split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
  File "/root/.cache/huggingface/modules/datasets_modules/datasets/the_pile/6fadc480ecb32470826cbf5900a9558b791ce55d5e9a0fdc8ad653e7b64bb349/the_pile.py", line 192, in _split_generators
    data_dir = dl_manager.download(_DATA_URLS[self.config.name])
  File "/usr/local/lib/python3.8/dist-packages/datasets/download/download_manager.py", line 427, in download
    downloaded_path_or_paths = map_nested(
  File "/usr/local/lib/python3.8/dist-packages/datasets/utils/py_utils.py", line 443, in map_nested
    mapped = [
  File "/usr/local/lib/python3.8/dist-packages/datasets/utils/py_utils.py", line 444, in <listcomp>
    _single_map_nested((function, obj, types, None, True, None))
  File "/usr/local/lib/python3.8/dist-packages/datasets/utils/py_utils.py", line 363, in _single_map_nested
    mapped = [_single_map_nested((function, v, types, None, True, None)) for v in pbar]
  File "/usr/local/lib/python3.8/dist-packages/datasets/utils/py_utils.py", line 363, in <listcomp>
    mapped = [_single_map_nested((function, v, types, None, True, None)) for v in pbar]
  File "/usr/local/lib/python3.8/dist-packages/datasets/utils/py_utils.py", line 346, in _single_map_nested
    return function(data_struct)
  File "/usr/local/lib/python3.8/dist-packages/datasets/download/download_manager.py", line 453, in _download
    return cached_path(url_or_filename, download_config=download_config)
  File "/usr/local/lib/python3.8/dist-packages/datasets/utils/file_utils.py", line 182, in cached_path
    output_path = get_from_cache(
  File "/usr/local/lib/python3.8/dist-packages/datasets/utils/file_utils.py", line 575, in get_from_cache
    http_get(
  File "/usr/local/lib/python3.8/dist-packages/datasets/utils/file_utils.py", line 379, in http_get
    for chunk in response.iter_content(chunk_size=1024):
  File "/usr/local/lib/python3.8/dist-packages/requests/models.py", line 818, in generate
    raise ChunkedEncodingError(e)
requests.exceptions.ChunkedEncodingError: ("Connection broken: ConnectionResetError(104, 'Connection reset by peer')", ConnectionResetError(104, 'Connection reset by peer'))
```


Users with slow internet speed are doomed (4MB/s). The dataset downloads fine at minimum speed 10MB/s.

Also, when the train splits were generated and then I removed the downloads folder to save up disk space, it started redownloading the whole dataset. Is there any way to use the already generated splits instead?

@sentialx @mariosasko , anytime on my above script , am I downloading and saving dataset correctly . Please suggest :)

@sentialx probably worth noting that `resume_download=True` doesn't directly save the dataset to disk, but instead just helps in resuming the dataset resume on interruption as @mariosasko mentions. resolving resumptions after a crash is [an open issue](https://github.com/huggingface/datasets/issues/5380) at the moment.