[
https://issues.apache.org/jira/browse/SPARK-54901?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Fangchen Li resolved SPARK-54901.
---------------------------------
Resolution: Invalid
Proposed improvement was already in place.
> Selective column conversion for scalar Pandas UDFs
> --------------------------------------------------
>
> Key: SPARK-54901
> URL: https://issues.apache.org/jira/browse/SPARK-54901
> Project: Spark
> Issue Type: Improvement
> Components: PySpark
> Affects Versions: 4.2.0
> Reporter: Fangchen Li
> Priority: Minor
> Labels: pull-request-available
>
> When executing a scalar Pandas UDF, PySpark currently converts all Arrow
> columns to Pandas Series, even if the UDF only uses a subset of columns. This
> is wasteful when working with wide DataFrames, where the UDF needs only a few
> columns.
> We could convert Arrow columns that are actually used by the UDF(s).
>
>
--
This message was sent by Atlassian Jira
(v8.20.10#820010)
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
