Building C4 takes forever
Hi @StellaAthena, thanks for reporting.

Please note, that our `datasets` library performs several operations in order to load a dataset, among them:
- it downloads all the required files: for C4 "en", 378.69 GB of JSON GZIPped files
- it parses their content to generate the dataset
- it caches the dataset in an Arrow file: for C4 "en", this file size is 1.87 TB
- it memory-maps the Arrow file

If it suits your use case, you might load this dataset in streaming mode:
- no Arrow file is generated
- you can iterate over elements immediately (no need to wait to download all the entire files)

```python
In [45]: from datasets import load_dataset
    ...: ds = load_dataset("c4", "en", split="train", streaming=True)
    ...: for item in ds:
    ...:     print(item)
    ...:     break
    ...: 
{'text': 'Beginners BBQ Class Taking Place in Missoula!\nDo you want to get better at making delicious BBQ? You will have the opportunity, put this on your calendar now. Thursday, September 22nd join World Class BBQ Champion, Tony Balay from Lonestar Smoke Rangers. He will be teaching a beginner level class for everyone who wants to get better with their culinary skills.\nHe will teach you everything you need to know to compete in a KCBS BBQ competition, including techniques, recipes, timelines, meat selection and trimming, plus smoker and fire information.\nThe cost to be in the class is $35 per person, and for spectators it is free. Included in the cost will be either a t-shirt or apron and you will be tasting samples of each meat that is prepared.', 'timestamp': '2019-04-25T12:57:54Z', 'url': 'https://klyq.com/beginners-bbq-class-taking-place-in-missoula/'}
```
I hope this is useful for your use case.
## Describe the bug
C4-en is a 300 GB dataset. However, when I try to download it through the hub it takes over _six hours_ to generate the train/test split from the downloaded files. This is an absurd amount of time and an unnecessary waste of resources.

## Steps to reproduce the bug
```python
c4 = datasets.load("c4", "en")
```

## Expected results
I would like to be able to download pre-split data.

## Environment info
- `datasets` version: 2.0.0
- Platform: Linux-5.13.0-35-generic-x86_64-with-glibc2.29
- Python version: 3.8.10
- PyArrow version: 7.0.0
- Pandas version: 1.4.1
