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https://issues.apache.org/jira/browse/SPARK-3550?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14148347#comment-14148347
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Aaron Staple commented on SPARK-3550:
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This has been addressed in another commit:
https://github.com/apache/spark/commit/fce5e251d636c788cda91345867e0294280c074d
See comment here:
https://github.com/apache/spark/pull/2412#issuecomment-56865408
> Disable automatic rdd caching in python api for relevant learners
> -----------------------------------------------------------------
>
> Key: SPARK-3550
> URL: https://issues.apache.org/jira/browse/SPARK-3550
> Project: Spark
> Issue Type: Improvement
> Components: MLlib, PySpark
> Reporter: Aaron Staple
>
> The python mllib api automatically caches training rdds. However, the
> NaiveBayes, ALS, and DecisionTree learners do not require external caching to
> prevent repeated RDD re-evaluation during learning. NaiveBayes only evaluates
> its input RDD once, while ALS and DecisionTree internally persist
> transformations of their input RDDs. For these learners, we should disable
> the automatic caching in the python mllib api.
> See discussion here:
> https://github.com/apache/spark/pull/2362#issuecomment-55637953
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