Hi, I’m currently experimenting with models in Metron and came across this link https://hortonworks.com/blog/model-service-modern-streaming-data-science-apache-metron/ The linked presentation shows how to use a python/rest service to deploy models that are invoked internally via steller. I looked around for more documentation/examples but couldn’t really find anything. I was wondering if:
1. It is possible to use spark context from a model e.g. via pyspark or something similar? 2. One of the “future” points mentioned in the blog is “Automatic construction of REST endpoints for models that conform to certain specifications (e.g., Spark-ML models, PMML, sci-kit learn exported pickle files)”. Is this something that is being actively worked at or something that will be available in near future? 3. If not, is there a standard pattern to deploy a spark streaming model to metron? 4. Lastly, is there a way to expose the model service URL to external clients (e.g. outside metron to other applications)? A use cased could be call the service to get a score, pretty much like how enrichment bolt does it. Any feedback/code samples will be greatly appreciated. Best regards, Sanket
