cchriswu commented on a change in pull request #32752:
URL: https://github.com/apache/spark/pull/32752#discussion_r645249759
##########
File path:
resource-managers/kubernetes/core/src/main/scala/org/apache/spark/scheduler/cluster/k8s/ExecutorPodsAllocator.scala
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@@ -99,6 +102,17 @@ private[spark] class ExecutorPodsAllocator(
@volatile private var deletedExecutorIds = Set.empty[Long]
def start(applicationId: String, schedulerBackend:
KubernetesClusterSchedulerBackend): Unit = {
+ // Wait until the driver pod is ready before starting executors, as the
headless service won't
+ // be resolvable by DNS until the driver pod is ready.
+ try {
+ kubernetesClient.pods()
+ .withName(kubernetesDriverPodName.get)
+ .waitUntilReady(driverPodReadinessTimeout, TimeUnit.MINUTES)
+ } catch {
+ case e: InterruptedException =>
+ logWarning(s"Timeout waiting for driver pod
${kubernetesDriverPodName.get} get ready in " +
+ s"namespace $namespace")
+ }
Review comment:
As the [JIRA issue](https://issues.apache.org/jira/browse/SPARK-32975)
describes, driver will not create new executors when this error happens.
> Once this error happens, driver doesn't restart executor.
However, other executors may be running fine. It's just that the number of
healthy executors will be less than expected. So I agree not to use
`SparkException` here.
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