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https://issues.apache.org/jira/browse/SPARK-5535?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15796294#comment-15796294
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Joseph K. Bradley edited comment on SPARK-5535 at 1/3/17 10:02 PM:
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This issue came up in [SPARK-19007], so I'd like to pick it up again. I'd like
people's thoughts on two questions:
* Should we add a special parameter value which matches in the input
DataFrame's storage level?
* What should the default value be?
** Maintain current behavior: MEMORY_ONLY
** (Probably) optimize for most use cases: Match input storage level
was (Author: josephkb):
This issue came up in [SPARK-19007], so I'd like to pick it up again. I'd like
people's thoughts on one question:
Should we add a special parameter value which matches in the input DataFrame's
storage level? It might be reasonable to use that as the default.
> Add parameter for storage levels
> --------------------------------
>
> Key: SPARK-5535
> URL: https://issues.apache.org/jira/browse/SPARK-5535
> Project: Spark
> Issue Type: New Feature
> Components: ML
> Reporter: Xiangrui Meng
>
> Add a special parameter type for storage levels that takes the string
> representation of StorageLevels.
> This value can be used when ML algorithms persist data internally.
> Specifically, add a new {{Param[String]}} which takes the storage level.
> This can go in sharedParams. It should be added to algorithms individually
> in subtasks.
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