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https://issues.apache.org/jira/browse/SPARK-3488?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Aaron Staple resolved SPARK-3488.
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Resolution: Won't Fix
> cache deserialized python RDDs before iterative learning
> --------------------------------------------------------
>
> Key: SPARK-3488
> URL: https://issues.apache.org/jira/browse/SPARK-3488
> Project: Spark
> Issue Type: Improvement
> Components: MLlib, PySpark
> Reporter: Aaron Staple
>
> When running an iterative learning algorithm, it makes sense that the input
> RDD be cached for improved performance. When learning is applied to a python
> RDD, currently the python RDD is always cached, then in scala that cached RDD
> is mapped to an uncached deserialized RDD, and the uncached RDD is passed to
> the learning algorithm. Instead the deserialized RDD should be cached.
> This was originally discussed here:
> https://github.com/apache/spark/pull/2347#issuecomment-55181535
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