Thanks you.   I am going to try the first option for now, but I do need to 
figure out why deployment takes so long.
Are there any metrics or log patterns that would indicate which task is waiting 
and which task is being waited on?


From: Chesnay Schepler <ches...@apache.org>
Sent: Thursday, August 19, 2021 2:23 PM
To: Colletta, Edward <edward.colle...@fmr.com>; user@flink.apache.org
Subject: Re: failures during job start

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This exception means that a task was deployed, but the task that produces the 
data it wants to consume was not available yet (even after waiting for a while).

Your case sounds similar to https://issues.apache.org/jira/browse/FLINK-9413, 
where this happens because the deployment of the producing task takes too long.

You have 2 options to solve this:
a) Have Flink wait longer for the partition to be created by increasing 
taskmanager.network.request-backoff.max
b) Speed up the deployment; for this you'd naturally have to investigate why 
the deployment takes so long in the first place.

On 19/08/2021 07:15, Colletta, Edward wrote:
Any help with this would be appreciated.   Is it possible that this is a 
data/application issue or a flink config/resource issue?

Using flink 11.2, java 11, session cluster, 5 nodes 32 cores each node.

I have an issue where starting a job takes a long time, and sometimes fails 
with PartitionNotFoundException, but succeeds on restart.   The job has 10 
kafka sources (10 partitions for each topic) and parallelism 5.
The failure does not happen when the kafka logs are empty.

Note during below scenario, cpu usage on task manager and job managers is low 
(below 30%)

The scenario we see

  1.  run request to load and run a jar, job appears on dashboard with all 160 
subtasks in Deploying state
  2.  after 2 minutes some subtasks start transitioning to running.
  3.  after another 30 seconds failure occurs and job goes into Restarting state
  4.  after another minute, restart completes all nodes running.

Exception history shows
2021-08-15 07:55:02
org.apache.flink.runtime.io.network.partition.PartitionNotFoundException: 
Partition 205a0867c6ef540009acd962d556f981#0@a6b547c5096f3c33eb9059cfe767a2ec 
not found.
        at 
org.apache.flink.runtime.io.network.partition.consumer.RemoteInputChannel.failPartitionRequest(RemoteInputChannel.java:267)
        at 
org.apache.flink.runtime.io.network.partition.consumer.RemoteInputChannel.retriggerSubpartitionRequest(RemoteInputChannel.java:166)
        at 
org.apache.flink.runtime.io.network.partition.consumer.SingleInputGate.retriggerPartitionRequest(SingleInputGate.java:521)
        at 
org.apache.flink.runtime.io.network.partition.consumer.SingleInputGate.lambda$triggerPartitionStateCheck$1(SingleInputGate.java:765)
        at 
java.base/java.util.concurrent.CompletableFuture$UniAccept.tryFire(CompletableFuture.java:714)
        at 
java.base/java.util.concurrent.CompletableFuture$Completion.run(CompletableFuture.java:478)
        at akka.dispatch.TaskInvocation.run(AbstractDispatcher.scala:40)
        at 
akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(ForkJoinExecutorConfigurator.scala:44)
        at akka.dispatch.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
        at 
akka.dispatch.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
        at akka.dispatch.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
        at 
akka.dispatch.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)






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