Hi All, I spent a lot of time at Spark Summit East this year talking with Spark developers and committers about challenges with productizing Spark. One of the biggest shortcomings I've encountered in Spark ML pipelines is the lack of a way to serve single requests with any reasonable performance. SPARK-10413 explores adding methods for single item prediction, but I'd like to explore a more holistic approach - a separate local api, with models that support transformations without depending on Spark at all.
I've written up a doc <https://docs.google.com/document/d/1Ha4DRMio5A7LjPqiHUnwVzbaxbev6ys04myyz6nDgI4/edit?usp=sharing> detailing the approach, and I'm happy to discuss alternatives. If this gains traction, I can create a branch with a minimal example on a simple transformer (probably something like CountVectorizerModel) so we have something concrete to continue the discussion on. Thanks, Asher Krim Senior Software Engineer
