Actually if you are using the Universal Recommender you only need to deploy once as long as the engine.json does not change. The hot swap happens as @Digambar says and there is literally no downtime. If you are using any of the other recommenders you do have to re-deploy after every train but the deploy happens very quickly, a ms or 2 as I recall.
From: Digambar Bhat <digambarbha...@gmail.com> Reply: user@predictionio.apache.org <user@predictionio.apache.org> Date: June 11, 2018 at 9:38:15 AM To: user@predictionio.apache.org <user@predictionio.apache.org> Subject: Re: Regarding Real-Time Prediction You don't need to deploy same engine again and again. You just deploy once and train whenever you want. Deployed instance will automatically point to newly trained model as hot swap happens. Regards, Digambar On Mon 11 Jun, 2018, 10:02 PM KRISH MEHTA, <krish14011...@gmail.com> wrote: Hi, I have just started using PredictionIO and according to the documentation I have to always run the Train and Deploy Command to get the prediction. I am working on predicting videos for recommendation and I want to know if there is any other way possible so that I can predict the results on the Fly with no Downtime. Please help me with the same. Yours Sincerely, Krish
