[
https://issues.apache.org/jira/browse/SPARK-23258?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Hyukjin Kwon resolved SPARK-23258.
----------------------------------
Resolution: Incomplete
> Should not split Arrow record batches based on row count
> --------------------------------------------------------
>
> Key: SPARK-23258
> URL: https://issues.apache.org/jira/browse/SPARK-23258
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 2.3.0
> Reporter: Bryan Cutler
> Priority: Major
> Labels: bulk-closed
>
> Currently when executing scalar {{pandas_udf}} or using {{toPandas()}} the
> Arrow record batches are split up once the record count reaches a max value,
> which is configured with "spark.sql.execution.arrow.maxRecordsPerBatch".
> This is not ideal because the number of columns is not taken into account and
> if there are many columns, then OOMs can occur. An alternative approach
> could be to look at the size of the Arrow buffers being used and cap it at a
> certain size.
--
This message was sent by Atlassian Jira
(v8.3.4#803005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
