Hi, I have a periodic retraining of a long running job (a decision tree trained on a large amount of historical data) that needs retrained on a daily/weekly/long period basis.
These models are used in spark streaming to score incoming data, I would like to understand what is best practice for triggering the retrain. > Should the spark batch job live in complete isolation from the streaming one? > Should the streaming job some how trigger the running of the long running batch job, if so how would you recommend? Does anyone know or a good blog post or article giving heads up on what system design for this might look like? Thanks a Million, Anthony -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Mixing-Long-Run-Periodic-Update-Jobs-With-Streaming-Scoring-tp25705.html Sent from the Apache Spark User List mailing list archive at Nabble.com. --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org