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https://issues.apache.org/jira/browse/ARROW-1974?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16392841#comment-16392841
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ASF GitHub Bot commented on ARROW-1974:
---------------------------------------

cpcloud commented on a change in pull request #447: ARROW-1974: Fix creating 
Arrow table with duplicate column names
URL: https://github.com/apache/parquet-cpp/pull/447#discussion_r173441381
 
 

 ##########
 File path: src/parquet/schema.h
 ##########
 @@ -264,8 +264,11 @@ class PARQUET_EXPORT GroupNode : public Node {
   bool Equals(const Node* other) const override;
 
   NodePtr field(int i) const { return fields_[i]; }
+  // Get the index of a field by its name, or negative value if not found
+  // If several fields share the same name, the smallest index is returned
 
 Review comment:
   I meant that before your change, the index returned was always valid?

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> [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: Antoine Pitrou
>            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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