[SPARK-3619] Upgrade to Mesos 0.21 to work around MESOS-1688

- Removed 'Known issues' section

Author: jongyoul

docs/running-on-mesos.md

@@ -167,9 +167,6 @@ acquire. By default, it will acquire *all* cores in the cluster (that get offere
 only makes sense if you run just one application at a time. You can cap the maximum number of cores
 using `conf.set("spark.cores.max", "10")` (for example).
 
-# Known issues
-- When using the "fine-grained" mode, make sure that your executors always leave 32 MB free on the slaves. Otherwise it can happen that your Spark job does not proceed anymore. Currently, Apache Mesos only offers resources if there are at least 32 MB memory allocatable. But as Spark allocates memory only for the executor and cpu only for tasks, it can happen on high slave memory usage that no new tasks will be started anymore. More details can be found in [MESOS-1688](https://issues.apache.org/jira/browse/MESOS-1688). Alternatively use the "coarse-gained" mode, which is not affected by this issue.
-
 # Running Alongside Hadoop
 
 You can run Spark and Mesos alongside your existing Hadoop cluster by just launching them as a