[jira] [Updated] (ARROW-7706) [Python] saving a dataframe to the same partitioned location silently doubles the data

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

     [ https://issues.apache.org/jira/browse/ARROW-7706?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Joris Van den Bossche updated ARROW-7706:
-----------------------------------------
    Labels: dataset dataset-parquet-write parquet  (was: dataset parquet)

> [Python] saving a dataframe to the same partitioned location silently doubles the data
> --------------------------------------------------------------------------------------
>
>                 Key: ARROW-7706
>                 URL: https://issues.apache.org/jira/browse/ARROW-7706
>             Project: Apache Arrow
>          Issue Type: Bug
>          Components: Python
>    Affects Versions: 0.15.1
>            Reporter: Tsvika Shapira
>            Priority: Major
>              Labels: dataset, dataset-parquet-write, parquet
>
> When a user saves a dataframe:
> {code:python}
> df1.to_parquet('/tmp/table', partition_cols=['col_a'], engine='pyarrow')
> {code}
> it will create sub-directories named "{{a=val1}}", "{{a=val2}}" in {{/tmp/table}}. Each of them will contain one (or more?) parquet files with random filenames.
> If a user runs the same command again, the code will use the existing sub-directories, but with different (random) filenames. As a result, any data loaded from this folder will be wrong - each row will be present twice.
> For example, when using
> {code:python}
> df1.to_parquet('/tmp/table', partition_cols=['col_a'], engine='pyarrow')  # second time
> df2 = pd.read_parquet('/tmp/table', engine='pyarrow')
> assert len(df1) == len(df2)  # raise an error{code}
> This is a subtle change in the data that can pass unnoticed.
>  
> I would expect that the code will prevent the user from using an non-empty destination as partitioned target. an overwrite flag can also be useful.



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