This is equivalent to
SPARK-3822 but for standalone mode.
This is actually a very tricky issue because the scheduling mechanism in the standalone Master uses different semantics. In standalone mode we allocate resources based on cores. By default, an application will grab all the cores in the cluster unless "spark.cores.max" is specified. Unfortunately, this means an application could get executors of different sizes (in terms of cores) if:
1) App 1 kills an executor
2) App 2, with "spark.cores.max" set, grabs a subset of cores on a worker
3) App 1 requests an executor
In this case, the new executor that App 1 gets back will be smaller than the rest and can execute fewer tasks in parallel. Further, standalone mode is subject to the constraint that only one executor can be allocated on each worker per application. As a result, it is rather meaningless to request new executors if the existing ones are already spread out across all nodes.