Revisit and Improve Spark Standalone Cluster

Spark Standalone Cluster has been supported for a long time as one of the resource managers.

As a part of Apache Spark 4.0.0, we revisit all layers of `Spark Standalone Cluster` as a long running subsystem inside K8s environment.

1. Spark Master, Worker, History Server Web UI Layer
2. Spark Master HA and Recovery Layer
3. Spark Master REST API Layer (including Cluster Utilization monitoring)
4. Spark Job Scheduling Layer
5. Spark Worker Management by exposing Cluster Utilization monitoring for Elastic Cluster Management
6. Spark Master/Worker dependency and classpath audit
7. Documentation