❓ Sharing ElasticSearch indexed dataset 
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Hello @pietrolesci , I am not sure to understand what you are trying to do here.

If you're looking for ways to save a dataset on disk, you can you the `save_to_disk` method:
```python
>>> import datasets
>>> loaded_dataset = datasets.load("dataset_name")
>>> loaded_dataset.save_to_disk("/path/on/your/disk")
```

The saved dataset can later be retrieved using:
```python
>>> loaded_dataset = datasets.Dataset.load_from_disk("/path/on/your/disk")
```

Also, I'd recommend posting your question directly in the issue section of the [elasticsearch repo](https://github.com/elastic/elasticsearch) Hi @SBrandeis,

Thanks a lot for picking up my request. 

Maybe I can clarify my use-case with a bit of context. Say I have the IMDb dataset. I create an ES index on it. Now I can save and reload the dataset from disk normally. Once I reload the dataset, it is easy to retrieve the ES index on my machine. I was wondering: is there a way I can share the (now) indexed version of the IMDb dataset with my colleagues without requiring them to re-index it?

Thanks a lot in advance for your consideration.

Best,

Pietro Thanks for the clarification.

I am not familiar with ElasticSearch, but if I understand well you're trying to migrate your data along with the ES index.
My advice would be to check out ES documentation, for instance, this might help you: https://www.elastic.co/guide/en/cloud/current/ec-migrate-data.html

Let me know if it helps
Hi there,

First of all, thank you very much for this amazing library. Datasets have become my preferred data structure for basically everything I am currently doing.

**Question:** I'm working with a dataset and I have an elasticsearch container running at localhost:9200. I added an elasticsearch index and I was wondering

- how can I know where it has been saved?

- how can I share the indexed dataset with others?

I tried to dig into the docs, but could not find anything about that.

Thank you very much for your help.

Best,
Pietro

Edit: apologies for the wrong label
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