Machine Learning If you mean, how do you distribute a new model in your application, then there's no magic to it. Just reference the new model in the functions you're executing in your driver.
If you implemented some other manual way of deploying model info, just do that again. There's no special thing to know. On Fri, Jul 22, 2016 at 11:39 AM, Jacek Laskowski <ja...@japila.pl> wrote: > Hi, > > What's a ML model? > > (I'm sure once we found out the answer you'd know the answer for your > question :)) > > Pozdrawiam, > Jacek Laskowski > ---- > https://medium.com/@jaceklaskowski/ > Mastering Apache Spark http://bit.ly/mastering-apache-spark > Follow me at https://twitter.com/jaceklaskowski > > > On Fri, Jul 22, 2016 at 11:49 AM, Sergio Fernández <wik...@apache.org> wrote: >> Hi, >> >> I have one question: >> >> How is the ML models distribution done across all nodes of a Spark cluster? >> >> I'm thinking about scenarios where the pipeline implementation does not >> necessary need to change, but the models have been upgraded. >> >> Thanks in advance. >> >> Best regards, >> >> -- >> Sergio Fernández >> Partner Technology Manager >> Redlink GmbH >> m: +43 6602747925 >> e: sergio.fernan...@redlink.co >> w: http://redlink.co > > --------------------------------------------------------------------- > To unsubscribe e-mail: user-unsubscr...@spark.apache.org > --------------------------------------------------------------------- To unsubscribe e-mail: user-unsubscr...@spark.apache.org
