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https://issues.apache.org/jira/browse/ARROW-1974?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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ASF GitHub Bot updated ARROW-1974:
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Labels: pull-request-available (was: )
> [Python] Segfault when working with Arrow tables with duplicate columns
> -----------------------------------------------------------------------
>
> Key: ARROW-1974
> URL: https://issues.apache.org/jira/browse/ARROW-1974
> Project: Apache Arrow
> Issue Type: Bug
> Components: C++, Python
> Affects Versions: 0.8.0
> Environment: Linux Mint 18.2
> Anaconda Python distribution + pyarrow installed from the conda-forge channel
> Reporter: Alexey Strokach
> Assignee: Phillip Cloud
> Priority: Minor
> Labels: pull-request-available
> Fix For: 0.9.0
>
>
> I accidentally created a large number of Parquet files with two
> __index_level_0__ columns (through a Spark SQL query).
> PyArrow can read these files into tables, but it segfaults when converting
> the resulting tables to Pandas DataFrames or when saving the tables to
> Parquet files.
> {code:none}
> # Duplicate columns cause segmentation faults
> table = pq.read_table('/path/to/duplicate_column_file.parquet')
> table.to_pandas() # Segmentation fault
> pq.write_table(table, '/some/output.parquet') # Segmentation fault
> {code}
> If I remove the duplicate column using table.remove_column(...) everything
> works without segfaults.
> {code:none}
> # After removing duplicate columns, everything works fine
> table = pq.read_table('/path/to/duplicate_column_file.parquet')
> table.remove_column(34)
> table.to_pandas() # OK
> pq.write_table(table, '/some/output.parquet') # OK
> {code}
> For more concrete examples, see `test_segfault_1.py` and `test_segfault_2.py`
> here: https://gitlab.com/ostrokach/pyarrow_duplicate_column_errors.
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