Optimize streaming from TAR archives
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Closed by: 
- #3066
2022-09-21T14:08:39Z
https://github.com/huggingface/datasets/issues/2829#issuecomment-1253767058
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2022-09-21T14:29:46Z
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Hi ! As you know TAR has some constraints for data streaming. While it is optimized for buffering, the files in the TAR archive **need to be streamed in order**. It means that we can't choose which file to stream from, and this notation is to be avoided for TAR archives:
```
tar://books_large_p1.txt::https://storage.googleapis.com/huggingface-nlp/datasets/bookcorpus/bookcorpus.tar.bz2
```
Instead, I suggest we implement `iter_archive` for the `StreamingDownloadManager`.
The regular `DownloadManager` already has it.

Then we will have to update the json/txt/csv/etc. loaders to make them use `iter_archive` on TAR archives.

That's also what Tensorflow Datasets is doing in this case.
See this [dataset](https://github.com/tensorflow/datasets/blob/93895059c80a9e05805e8f32a2e310f66a23fc98/tensorflow_datasets/image_classification/flowers.py) for example.

Therefore instead of doing
```python
uncompressed = dl_manager.extract(tar_archive)
filename = "books_large_p1.txt"
with open(os.path.join(uncompressed, filename)) as f:
    for line in f:
        ...
```
we'll do
```python
for filename, f in dl_manager.iter_archive(tar_archive):
    for line in f:
        ...
```