Hello Dev community, I have created the initial API design documentation around building storm topologies around a set of machine learning streaming algorithms here: https://docs.google.com/document/d/1LrO7XRcMxJoMM83wjRd-Ov74VAaomA_mXOAhCStgGng/edit?usp=sharing, this is very much a work in progress but I wanted to start getting early feedback from the community as its a lot of complex operations representing a streaming ml pipeline using heron. This design leverages apache samoa to figure out which algorithms to focus on in bringing into heron.
Thank you Karthik Ramasamy for your mentoring on this, the goal will be to represent all the algorithms in phase 1 as storm topologies and then to evolve this to building a streamlet based architecture would really appreciate some feedback from the community While you guys are commenting on the initial approach I will : 1) finish the design for the rest of the algorithms for phase 1 2) start the design for building out a heron streamlet based architecture to run on top of the storm based topologies. Look forward to a productive discussion around the design
