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https://issues.apache.org/jira/browse/SPARK-30580?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon resolved SPARK-30580.
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Resolution: Invalid
> Why can PySpark persist data only in serialised format?
> -------------------------------------------------------
>
> Key: SPARK-30580
> URL: https://issues.apache.org/jira/browse/SPARK-30580
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 2.4.0
> Reporter: Francesco Cavrini
> Priority: Minor
> Labels: performance
>
> The storage levels in PySpark allow to persist data only in serialised
> format. There is also [a
> comment|[https://github.com/apache/spark/blob/master/python/pyspark/storagelevel.py#L28]]
> explicitly stating that "Since the data is always serialized on the Python
> side, all the constants use the serialized formats." While that makes totally
> sense for RDDs, it is not clear to me why it is not possible to persist data
> without serialisation when using the dataframe/dataset APIs. In theory, in
> such cases, the persist would only be a directive and data would never leave
> the JVM, thus allowing for un-serialised persistence, correct? Many thanks
> for the feedback!
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