[jira] [Updated] (ARROW-11469) [Python] Performance degradation parquet reading of wide dataframes
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https://issues.apache.org/jira/browse/ARROW-11469?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Elena Henderson updated ARROW-11469:
Attachment: image-2021-05-03-14-31-41-260.png
> [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, 1))
> 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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[jira] [Updated] (ARROW-11469) [Python] Performance degradation parquet reading of 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 parquet reading of wide
dataframes (was: [Python] Performance degradation wide dataframes)
> [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: 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, 1))
> 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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