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https://issues.apache.org/jira/browse/ARROW-7706?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Joris Van den Bossche updated ARROW-7706:
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Summary: [Python] saving a dataframe to the same partitioned location
silently doubles the data (was: saving a dataframe to the same partitioned
location silently doubles the data)
> [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
>
> 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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