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https://issues.apache.org/jira/browse/ARROW-6876?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16951168#comment-16951168
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Bob commented on ARROW-6876:
----------------------------
[~jorisvandenbossche] sorry I cannot share the data with you because they
contain our IP. Something I can share with is:
In [6]: df.shape
Out[6]: (61, 31835)
All fields are just pain floats, I believe you can create a dataframe just like
this with no difficulties?
One thing to note is that in our dataframe we use multilevel columns. But I
suppose that is not an issue?
> Reading parquet file becomes really slow for 0.15.0
> ---------------------------------------------------
>
> Key: ARROW-6876
> URL: https://issues.apache.org/jira/browse/ARROW-6876
> Project: Apache Arrow
> Issue Type: Bug
> Components: Python
> Affects Versions: 0.15.0
> Environment: python3.7
> Reporter: Bob
> Priority: Major
> Attachments: image-2019-10-14-18-10-42-850.png,
> image-2019-10-14-18-12-07-652.png
>
>
> Hi,
>
> I just noticed that reading a parquet file becomes really slow after I
> upgraded to 0.15.0 when using pandas.
>
> Example:
> *With 0.14.1*
> In [4]: %timeit df = pd.read_parquet(path)
> 2.02 s ± 47.5 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)
> *With 0.15.0*
> In [5]: %timeit df = pd.read_parquet(path)
> 22.9 s ± 478 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)
>
> The file is about 15MB in size. I am testing on the same machine using the
> same version of python and pandas.
>
> Have you received similar complain? What could be the issue here?
>
> Thanks a lot.
>
>
> Edit1:
> Some profiling I did:
> 0.14.1:
> !image-2019-10-14-18-12-07-652.png!
>
> 0.15.0:
> !image-2019-10-14-18-10-42-850.png!
>
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