Hi All,

Is there any way I can save Input schema along with ml PipelineModel object?
This feature will be really helpful while loading the model and running
transform, as user can get back the schema , prepare the dataset for
model.transform and don't need to remember it.

I see below jira talks about this as one of the update, but I am not able
to get any sub-task for the same(also it is marked as resolved).
https://issues.apache.org/jira/browse/SPARK-6725


"*UPDATE*: In spark.ml, we could save feature metadata using DataFrames.
Other libraries and formats can support this, and it would be great if we
could too. We could do either of the following:

   - save() optionally takes a dataset (or schema), and load will return a
   (model, schema) pair.
   - Models themselves save the input schema.

Both options would mean inheriting from new Saveable, Loadable types."

Please let me know if any update or jira on this.


Thanks,
Satya




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