[
https://issues.apache.org/jira/browse/SPARK-23030?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16320942#comment-16320942
]
Bryan Cutler commented on SPARK-23030:
--------------------------------------
I'm looking into this, will submit a WIP PR if I see an improvement
> 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
>
> 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.
--
This message was sent by Atlassian JIRA
(v6.4.14#64029)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
