dongjoon-hyun commented on a change in pull request #32752:
URL: https://github.com/apache/spark/pull/32752#discussion_r645257919
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File path:
resource-managers/kubernetes/core/src/main/scala/org/apache/spark/scheduler/cluster/k8s/ExecutorPodsAllocator.scala
##########
@@ -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:
I don't think the error report is correct because Apache Spark doesn't
use `restart` executor at all. The driver will keep creating new executors
because the executors with `UnknownHostException` will be dead on the failure.
I'm currently describing the Apache Spark behavior, not 3rd party operator
behavior.
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