[WIP][SPARK-3795] Heuristics for dynamically scaling executors

This is part of a bigger effort to provide elastic scaling of executors within a Spark application ([SPARK-3174](https://issues.apache.org/jira/browse/SPARK-3174)). This PR does not provide any functionality by itself; it is a skeleton that is missing a mechanism to be added later in [SPARK-3822](https://issues.apache.org/jira/browse/SPARK-3822).

The design doc can be found at [SPARK-3174](https://issues.apache.org/jira/browse/SPARK-3174) (under "Heuristics for Scaling Executors". This deviates from the design in two ways: (1) the remove policy is significantly simplified by cutting out the exponential increase logic that mirrors the add policy, and (2) the configuration of the add policy is split up into `addExecutorThreshold` and `addExecutorInterval`. The main reason for this is that the user may want to configure how quickly executors are added, but want to keep the trigger condition the same.

Comments and feedback are most welcome, but please keep in mind that this is still WIP! For those of you reviewing this in detail, I highly recommend doing it through your favorite IDE instead of through the diff here.
Any particular rationale for these defaults?  My intuition would be that the addThreshold should be something close to how long it takes for a new executor to launch and drain its capacity in tasks from the queue.  This shouldn't take more than a couple seconds.

A remove threshold of 10 minutes also seems high to me. The threshold should be something like a standard deviation up from the typical amount of time that a user would wait before running another query / job after one completes.  I'd imagine a minute or so would suffice.