huggingface / huggingface/datatrove

question about hypothetical SQL datasources

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Dominant language
Python
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Description

Hello,
I wonder if somebody has tried to create a pipeline on data retrieved by an SQL query (for example via duckdb, or similar tools).

The question starts from a relatively simple use-case: I'd like to be able to run a simple query with joins (for example with duckddb, but ideally even using a virtualizer, a query engine such as apache drill, etc) over two datasets (that usually are composed by different large files), and consume the results as a stream, inside ad specific Reader for the datatrove pipeline.

If I'm not wrong, it should be possible to implement something like that, extending the class `BaseReader`, and creating a `Generator[Document]...` for each row from the results...

Did anyone already tried something similar? Do you see any drawbacks in that approach?

Thank you in advance for any suggestion, and for developing this very useful framework! :-)

Alfredo

Contributor guide

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Research direction

The issue mentions extending BaseReader and producing a Generator[Document] for SQL query rows. Start by reading the BaseReader entry point and clarify which query engines, joins, and streaming behavior should be supported. Done is not defined in the issue and would require an agreed scope plus validation for the selected data sources.

Written by the indexing model from the issue text.

Assessment

Tech stack
python, sql
Domain
data-engineering
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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