[
https://issues.apache.org/jira/browse/SPARK-25274?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Bryan Cutler resolved SPARK-25274.
----------------------------------
Resolution: Fixed
Fix Version/s: 3.0.0
Issue resolved by pull request 22275
https://github.com/apache/spark/pull/22275
> Improve toPandas with Arrow by sending out-of-order record batches
> ------------------------------------------------------------------
>
> Key: SPARK-25274
> URL: https://issues.apache.org/jira/browse/SPARK-25274
> Project: Spark
> Issue Type: Sub-task
> Components: PySpark, SQL
> Affects Versions: 2.4.0
> Reporter: Bryan Cutler
> Assignee: Bryan Cutler
> Priority: Major
> Fix For: 3.0.0
>
>
> When executing {{toPandas}} with Arrow enabled, partitions that arrive in the
> JVM out-of-order must be buffered before they can be send to Python. This
> causes an excess of memory to be used in the driver JVM and increases the
> time it takes to complete because data must sit in the JVM waiting for
> preceding partitions to come in.
> This can be improved by sending out-of-order partitions to Python as soon as
> they arrive in the JVM, followed by a list of indices so that Python can
> assemble the data in the correct order. This way, data is not buffered at the
> JVM and there is no waiting on particular partitions so performance will be
> increased.
--
This message was sent by Atlassian JIRA
(v7.6.3#76005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
