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https://issues.apache.org/jira/browse/SPARK-18616?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Nick Pentreath updated SPARK-18616:
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Target Version/s: (was: 2.0.2)
> Pure Python Implementation of MLWritable for use in Pipeline
> ------------------------------------------------------------
>
> Key: SPARK-18616
> URL: https://issues.apache.org/jira/browse/SPARK-18616
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Affects Versions: 2.0.2
> Environment: pyspark
> Reporter: Andrea Matsunaga
>
> When developing an estimator and model completely in python, it is possible
> to implement the save() function, and it works for a standalone model, but
> not when added to a Pipeline. The reason is that Pipeline save implementation
> forces the use of JavaMLWritable, thus also requiring the object to have
> methods that are meaningful only to Java objects. Pipelines implementation
> need to have a check for the type of writable object defined.
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