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
