[SPARK-3150] Fix NullPointerException in in Spark recovery: Add initializing default values in DriverInfo.init()

The issue happens when Spark is run standalone on a cluster.
When master and driver fall simultaneously on one node in a cluster, master tries to recover its state and restart spark driver.
While restarting driver, it falls with NPE exception (stacktrace is below).
After falling, it restarts and tries to recover its state and restart Spark driver again. It happens over and over in an infinite cycle.
Namely, Spark tries to read DriverInfo state from zookeeper, but after reading it happens to be null in DriverInfo.worker.

https://issues.apache.org/jira/browse/SPARK-3150

Author: Tatiana Borisova <tanyatik@yandex.ru>

Closes #2062 from tanyatik/spark-3150 and squashes the following commits:

9936043 [Tatiana Borisova] Add initializing default values in DriverInfo.init()

(cherry picked from commit 70d814665baa8b8ca868d3126452105ecfa5cbff)
Signed-off-by: Josh Rosen <joshrosen@apache.org>
[SPARK-3264] Allow users to set executor Spark home in Mesos

The executors and the driver may not share the same Spark home. There is currently one way to set the executor side Spark home in Mesos, through setting `spark.home`. However, this is neither documented nor intuitive. This PR adds a more specific config `spark.mesos.executor.home` and exposes this to the user.

liancheng tnachen

Author: Andrew Or <andrewor14@gmail.com>

Closes #2166 from andrewor14/mesos-spark-home and squashes the following commits:

b87965e [Andrew Or] Merge branch 'master' of github.com:apache/spark into mesos-spark-home
f6abb2e [Andrew Or] Document spark.mesos.executor.home
ca7846d [Andrew Or] Add more specific configuration for executor Spark home in Mesos

(cherry picked from commit 41dc5987d9abeca6fc0f5935c780d48f517cdf95)
Signed-off-by: Andrew Or <andrewor14@gmail.com>
[SPARK-3190] Avoid overflow in VertexRDD.count()

VertexRDDs with more than 4 billion elements are counted incorrectly due to integer overflow when summing partition sizes. This PR fixes the issue by converting partition sizes to Longs before summing them.

The following code previously returned -10000000. After applying this PR, it returns the correct answer of 5000000000 (5 billion).

```scala
val pairs = sc.parallelize(0L until 500L).map(_ * 10000000)
  .flatMap(start => start until (start + 10000000)).map(x => (x, x))
VertexRDD(pairs).count()
```

Author: Ankur Dave <ankurdave@gmail.com>

Closes #2106 from ankurdave/SPARK-3190 and squashes the following commits:

641f468 [Ankur Dave] Avoid overflow in VertexRDD.count()

(cherry picked from commit 96df92906978c5f58e0cc8ff5eebe5b35a08be3b)
Signed-off-by: Josh Rosen <joshrosen@apache.org>