Andrea Matsunaga created SPARK-18616:
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Summary: 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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