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Posted to jira@arrow.apache.org by "Weston Pace (Jira)" <ji...@apache.org> on 2022/01/14 23:21:00 UTC

[jira] [Comment Edited] (ARROW-12358) [C++][Python][R][Dataset] Control overwriting vs appending when writing to existing dataset

    [ https://issues.apache.org/jira/browse/ARROW-12358?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17476470#comment-17476470 ] 

Weston Pace edited comment on ARROW-12358 at 1/14/22, 11:20 PM:
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The "not found" error is thrown from python and then I'd be catching it in {{C++}}.  I'm not sure how well that would work.  I don't think we have a specific NotFoundError in {{C++}} so I'd need to examine the message content which is a little icky.


was (Author: westonpace):
The "not found" error is thrown from python and then I'd be catching it in C++.  I'm not sure how well that would work.  I don't think we have a specific NotFoundError in C++ so I'd need to examine the message content which is a little icky.

> [C++][Python][R][Dataset] Control overwriting vs appending when writing to existing dataset
> -------------------------------------------------------------------------------------------
>
>                 Key: ARROW-12358
>                 URL: https://issues.apache.org/jira/browse/ARROW-12358
>             Project: Apache Arrow
>          Issue Type: Improvement
>          Components: C++
>            Reporter: Joris Van den Bossche
>            Priority: Major
>              Labels: dataset
>             Fix For: 8.0.0
>
>
> Currently, the dataset writing (eg with {{pyarrow.dataset.write_dataset}}) uses a fixed filename template ({{"part\{i\}.ext"}}). This means that when you are writing to an existing dataset, you de facto overwrite previous data when using this default template.
> There is some discussion in ARROW-10695 about how the user can avoid this by ensuring the file names are unique (the user can specify the {{basename_template}} to be something unique). There is also ARROW-7706 about silently doubling data (so _not_ overwriting existing data) with the legacy {{parquet.write_to_dataset}} implementation. 
> It could be good to have a "mode" when writing datasets that controls the different possible behaviours. And erroring when there is pre-existing data in the target directory is maybe the safest default, because both appending vs overwriting silently can be surprising behaviour depending on your expectations.



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