set RestartPolicy=Never for executor (#367)

* set RestartPolicy=Never for executor

As for current implementation the RestartPolicy of executor pod is
not set, so the default value "OnFailure" is in effect. But this
causes problem.

If an executor is terminated unexpectedly, for example, exit by
java.lang.OutOfMemoryError,  it'll be restarted by k8s with the
same executor ID.  When the new executor tries to fetch a block hold by
the last executor, ShuffleBlockFetcherIterator.splitLocalRemoteBlocks()
think it's a **local** block and tries to read it from it's local dir.
But the executor's local dir is changed because random generated ID is
part of local dir. FetchFailedException will raise and the stage will
fail.

The rolling Error message:

17/06/29 01:54:56 WARN KubernetesTaskSetManager: Lost task 0.1 in stage
2.0 (TID 7, 172.16.75.92, executor 1): FetchFailed(BlockManagerId(1,
172.16.75.92, 40539, None), shuffleId=2, mapId=0, reduceId=0, message=
org.apache.spark.shuffle.FetchFailedException:
/data2/spark/blockmgr-0e228d3c-8727-422e-aa97-2841a877c42a/32/shuffle_2_0_0.index
(No such file or directory)
        at
org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:357)
        at
org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:332)
        at
org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:54)
        at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)

* Update KubernetesClusterSchedulerBackend.scala

resource-managers/kubernetes/core/src/main/scala/org/apache/spark/scheduler/cluster/kubernetes/KubernetesClusterSchedulerBackend.scala

@@ -454,6 +454,7 @@ private[spark] class KubernetesClusterSchedulerBackend(
       .endMetadata()
       .withNewSpec()
         .withHostname(hostname)
+        .withRestartPolicy("Never")
         .withNodeSelector(nodeSelector.asJava)
       .endSpec()
       .build()