[jira] [Commented] (ARROW-11469) [Python] Performance degradation parquet reading of wide dataframes

["Elena Henderson (Jira)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/ARROW-11469?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17338622#comment-17338622 ] 

Elena Henderson commented on ARROW-11469:
-----------------------------------------

Performance of reading wide dataframes degraded farther in pyarrow 4.0.0:

[https://conbench.ursa.dev/compare/runs/afbbfc387b314fb6886168225c29d3af...c30d6d188bc24aa2b319808446b8d0aa/]

baseline = pyarrow 3.0.0 and contender = pyarrow 4.0.0

 

!image-2021-05-03-14-31-41-260.png|width=942,height=501!
h1.  

> [Python] Performance degradation parquet reading of wide dataframes
> -------------------------------------------------------------------
>
>                 Key: ARROW-11469
>                 URL: https://issues.apache.org/jira/browse/ARROW-11469
>             Project: Apache Arrow
>          Issue Type: Bug
>          Components: Python
>    Affects Versions: 1.0.0, 1.0.1, 2.0.0, 3.0.0
>            Reporter: Axel G
>            Priority: Minor
>         Attachments: image-2021-05-03-14-31-41-260.png, profile_wide300.svg
>
>
> I noticed a relatively big performance degradation in version 1.0.0+ when trying to load wide dataframes.
> For example you should be able to reproduce by doing:
> {code:java}
> import numpy as np
> import pandas as pd
> import pyarrow as pa
> import pyarrow.parquet as pq
> df = pd.DataFrame(np.random.rand(100, 10000))
> table = pa.Table.from_pandas(df)
> pq.write_table(table, "temp.parquet")
> %timeit pd.read_parquet("temp.parquet"){code}
> In version 0.17.0, this takes about 300-400 ms and for anything above and including 1.0.0, this suddenly takes around 2 seconds.
>  
> Thanks for looking into this.



--
This message was sent by Atlassian Jira
(v8.3.4#803005)