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https://issues.apache.org/jira/browse/SPARK-23030?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon resolved SPARK-23030.
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Resolution: Fixed
Fix Version/s: 2.4.0
Issue resolved by pull request 21546
[https://github.com/apache/spark/pull/21546]
> Decrease memory consumption with toPandas() collection using Arrow
> ------------------------------------------------------------------
>
> Key: SPARK-23030
> URL: https://issues.apache.org/jira/browse/SPARK-23030
> Project: Spark
> Issue Type: Sub-task
> Components: PySpark, SQL
> Affects Versions: 2.3.0
> Reporter: Bryan Cutler
> Assignee: Bryan Cutler
> Priority: Major
> Fix For: 2.4.0
>
>
> Currently with Arrow enabled, calling {{toPandas()}} results in a collection
> of all partitions in the JVM in the form of batches of Arrow file format.
> Once collected in the JVM, they are served to the Python driver process.
> I believe using the Arrow stream format can help to optimize this and reduce
> memory consumption in the JVM by only loading one record batch at a time
> before sending it to Python. This might also reduce the latency between
> making the initial call in Python and receiving the first batch of records.
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