[
https://issues.apache.org/jira/browse/SPARK-3467?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Davies Liu resolved SPARK-3467.
-------------------------------
Resolution: Fixed
Fix Version/s: 1.2.0
This is fixed by https://github.com/apache/spark/pull/2740
> Python BatchedSerializer should dynamically lower batch size for large objects
> ------------------------------------------------------------------------------
>
> Key: SPARK-3467
> URL: https://issues.apache.org/jira/browse/SPARK-3467
> Project: Spark
> Issue Type: Improvement
> Components: PySpark
> Reporter: Matei Zaharia
> Fix For: 1.2.0
>
>
> If you try caching largish objects in Python, you will get a crash sooner
> than you would in Scala / Java because Python automatically batches them. I
> believe the default batch size is 10, though it may be 1024. But maybe we can
> start by pickling the first object and using a smaller batch size if it is
> large.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
