[
https://issues.apache.org/jira/browse/PARQUET-1100?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16165652#comment-16165652
]
Wes McKinney commented on PARQUET-1100:
---------------------------------------
[~jseppanen] I have this fixed in
https://github.com/apache/parquet-cpp/pull/398 and am working on finalizing the
patch so it can go in. Will make sure that conda/pip wheels for Arrow 0.7.0
include this bug fix
> [C++] Reading repeated types should decode number of records rather than
> number of values
> -----------------------------------------------------------------------------------------
>
> Key: PARQUET-1100
> URL: https://issues.apache.org/jira/browse/PARQUET-1100
> Project: Parquet
> Issue Type: Bug
> Components: parquet-cpp
> Affects Versions: cpp-1.2.0
> Reporter: Jarno Seppanen
> Assignee: Wes McKinney
> Fix For: cpp-1.3.0
>
> Attachments:
> part-00000-6570e34b-b42c-4a39-8adf-21d3a97fb87d.snappy.parquet
>
>
> Reading the attached parquet file into pandas dataframe and then using the
> dataframe segfaults.
> {noformat}
> Python 3.5.3 |Continuum Analytics, Inc.| (default, Mar 6 2017, 11:58:13)
> [GCC 4.4.7 20120313 (Red Hat 4.4.7-1)] on linux
> Type "help", "copyright", "credits" or "license" for more information.
> >>>
> >>> import pyarrow
> >>> import pyarrow.parquet as pq
> >>> pyarrow.__version__
> '0.6.0'
> >>> import pandas as pd
> >>> pd.__version__
> '0.19.0'
> >>> df =
> >>> pq.read_table('part-00000-6570e34b-b42c-4a39-8adf-21d3a97fb87d.snappy.parquet')
> >>> \
> ... .to_pandas()
> >>> len(df)
> 69
> >>> df.info()
> <class 'pandas.core.frame.DataFrame'>
> RangeIndex: 69 entries, 0 to 68
> Data columns (total 6 columns):
> label 69 non-null int32
> account_meta 69 non-null object
> features_type 69 non-null int32
> features_size 69 non-null int32
> features_indices 1 non-null object
> features_values 1 non-null object
> dtypes: int32(3), object(3)
> memory usage: 2.5+ KB
> >>>
> >>> pd.concat([df, df])
> Segmentation fault (core dumped)
> {noformat}
> Actually just print(df) is enough to trigger the segfault
--
This message was sent by Atlassian JIRA
(v6.4.14#64029)
