Add PyCapsule support for Arrow import and export #825
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You can see my casting implementation here. But note that's slightly different as I'm using an |
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Ok, added the requested schema and unit tests for export. All that I think is left is unit tests on the import. I'm not sure if I should keep the nanoarrow in the unit test. If so I need to add it to the requirements files. |
docs/source/user-guide/io/arrow.rst
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| important to note that this will cause the DataFrame execution to happen, which may be | ||
| a time consuming task. That is, you will cause a :py:func:`datafusion.dataframe.DataFrame.collect` | ||
| operation call to occur. |
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I'd suggest putting this into an "admonition" box with a warning color to make this clearer. I'm not sure how to do that in sphinx, but this is what I'm referring to in mkdocs-material: https://squidfunk.github.io/mkdocs-material/reference/admonitions/#supported-types
| ``__arrow_c_stream__`` or ``__arrow_c_array__``. For the latter, it must return | ||
| a struct array. Common examples of sources from pyarrow include |
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For both they must emit a struct array. Any Arrow array can be passed through an __arrow_c_stream__. Canonically, to transfer a DataFrame you have a stream of struct arrays where each one is unpacked to be the columns of a RecordBatch. But it doesn't have to a struct array: you can also transfer a Series through an __arrow_c_stream__, where each batch in the stream iterator is just a primitive array.
| merged_schema.project(&project_indices) | ||
| } | ||
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| fn record_batch_into_schema( |
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I am surprised that arrow-rs nor datafusion have such a utility for converting a record-batch, but I did take a quick look around and didn't find anything.
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Well there is cast. Cast works on struct arrays, so you could make a simple wrapper around cast to work on RecordBatch by creating a struct array from the record batch. This is what I do in pyo3-arrow.
The main difference is that cast doesn't also project. It's not clear to me whether the PyCapsule Interface intends to support projection or not. I don't think anyone has asked.
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Since the user isn't calling the pycapsule interface directly, it's also not clear how the user API would look to ask for a projection via pycapsules.
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I applied your suggestions. Do either of you want a re-review before we ask to merge? |
…g much over pyarrow
Co-authored-by: Michael J Ward <[email protected]>
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Which issue does this PR close?
Closes #752
Rationale for this change
User requested.
What changes are included in this PR?
With this change you can import any arrow table that implements the PyCapsule Interface using the
SessionContext.from_arrow_tablefunction. Additionally, PyCapsule export of DataFrame is added. Now any python based project that uses python arrow with the pycapsule interface can directly consume a datafusion dataframe.The DataFrame will be executed at the point of export.
You can see a minimal example in the issue ticket.
Are there any user-facing changes?
This PR adds
SessionContext.from_arrowwhich served the same purpose asfrom_arrow_tableexcept that it now takes any object that implements the required PyCapsule functions.from_arrow_tableis now an alias tofrom_arrow.Still to do: