Hello folks! I’m trying to get a deeper understanding of how Cloud Dataflow runs our Beam programs.
I worked with Spark a few months and I understood that you have some kind of cluster topology with a driver program which creates the SparkContext, some worker nodes and a cluster manager. Also, I know that Spark is very fast via it’s in-memory computing. Is it the same case for Cloud Dataflow? What are the big differences between them?
