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Posted to jira@arrow.apache.org by "Joris Van den Bossche (Jira)" <ji...@apache.org> on 2021/02/02 17:36:00 UTC
[jira] [Updated] (ARROW-11469) [Python] Performance degradation
wide dataframes
[ https://issues.apache.org/jira/browse/ARROW-11469?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Joris Van den Bossche updated ARROW-11469:
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Summary: [Python] Performance degradation wide dataframes (was: Performance degradation wide dataframes)
> [Python] Performance degradation 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: 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.
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