Spark + EMR using Amazon's “maximizeResourceAllocation” setting does not use all cores/vcores

Question

I\'m running an EMR cluster (version emr-4.2.0) for Spark using the Amazon specific maximizeResourceAllocation flag as documented here. According to those docs, \"

Answer 1

With this setting you should get 1 executor on each instance (except the master), each with 8 cores and about 30GB of RAM.

Is the Spark UI at http://:8088/ not showing that allocation?

I'm not sure that setting is really a lot of value compared to the other one mentioned on that page, "Enabling Dynamic Allocation of Executors". That'll let Spark manage it's own number of instances for a job, and if you launch a task with 2 CPU cores and 3G of RAM per executor you'll get a pretty good ratio of CPU to memory for EMR's instance sizes.