[jira] [Updated] (ARROW-12631) [Python] pyarrow.dataset.write_table should accept a Scanner to write

["Joris Van den Bossche (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/ARROW-12631?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Joris Van den Bossche updated ARROW-12631:
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    Summary: [Python] pyarrow.dataset.write_table should accept a Scanner to write  (was: [Python] Should dataset.write_table accept a Scanner?)

> [Python] pyarrow.dataset.write_table should accept a Scanner to write
> ---------------------------------------------------------------------
>
>                 Key: ARROW-12631
>                 URL: https://issues.apache.org/jira/browse/ARROW-12631
>             Project: Apache Arrow
>          Issue Type: Improvement
>          Components: Python
>            Reporter: Joris Van den Bossche
>            Priority: Major
>              Labels: dataset
>
> Assume you open a dataset and want to write it back with some projected columns. Currently you need to actually materialize it to a Table or convert it to an iterator of batches, for being able to write the dataset:
> {code:python}
> import pyarrow.dataset as ds
> dataset = ds.dataset(pa.table({'a': [1, 2, 3]}))
> # write with projected columns
> projection = {'b': ds.field('a')}
> # this works but materializes full table
> ds.write_dataset(dataset.to_table(columns=projection), "test.parquet", format="parquet")
> # this requires the exact schema, which is a bit annoying as you need to construct that manually
> ds.write_dataset(dataset.to_batches(columns=projection), "test.parquet", format="parquet", schema=...<projected schema>...)
> {code}
> You could expect to do the following?
> {code}
> ds.write_dataset(dataset.scanner(columns=projection), "test.parquet", format="parquet")
> {code}
> cc [~lidavidm] do you think this logic is correct?
> (encountered this while trying to reproduce ARROW-12620 in Python)



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