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https://issues.apache.org/jira/browse/SPARK-1418?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Xiangrui Meng closed SPARK-1418.
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Resolution: Implemented
Fix Version/s: 1.2.0
> Python MLlib's _get_unmangled_rdd should uncache RDDs when training is done
> ---------------------------------------------------------------------------
>
> Key: SPARK-1418
> URL: https://issues.apache.org/jira/browse/SPARK-1418
> Project: Spark
> Issue Type: Improvement
> Components: MLlib, PySpark
> Reporter: Matei Zaharia
> Fix For: 1.2.0
>
>
> Right now when PySpark converts a Python RDD of NumPy vectors to a Java one,
> it caches the Java one, since many of the algorithms are iterative. We should
> call unpersist() at the end of the algorithm though to free cache space. In
> addition it may be good to persist the Java RDD with
> StorageLevel.MEMORY_AND_DISK instead of going back through the NumPy
> conversion.. it will almost certainly be faster.
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