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https://issues.apache.org/jira/browse/ARROW-12631?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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David Li resolved ARROW-12631.
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Fix Version/s: 5.0.0
Resolution: Fixed
Issue resolved by pull request 10224
[https://github.com/apache/arrow/pull/10224]
> [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
> Assignee: Joris Van den Bossche
> Priority: Major
> Labels: dataset, pull-request-available
> Fix For: 5.0.0
>
> Time Spent: 1h 10m
> Remaining Estimate: 0h
>
> 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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