[jira] [Assigned] (PARQUET-1245) [C++] Segfault when writing Arrow table with duplicate columns

["Wes McKinney (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/PARQUET-1245?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Wes McKinney reassigned PARQUET-1245:
-------------------------------------

    Assignee: Antoine Pitrou

> [C++] Segfault when writing Arrow table with duplicate columns
> --------------------------------------------------------------
>
>                 Key: PARQUET-1245
>                 URL: https://issues.apache.org/jira/browse/PARQUET-1245
>             Project: Parquet
>          Issue Type: Bug
>         Environment: Linux Mint 18.2
> Anaconda Python distribution + pyarrow installed from the conda-forge channel
>            Reporter: Alexey Strokach
>            Assignee: Antoine Pitrou
>            Priority: Minor
>              Labels: pull-request-available
>             Fix For: cpp-1.5.0
>
>
> 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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