problem with increase job parallelism

[Lei Chen <le...@gmail.com>]

Hi,

We're trying to implement some module to help autoscale our pipeline which
is built  with Flink on YARN. According to the document, the suggested
procedure seems to be:

1. cancel job with savepoint
2. start new job with increased YARN TM number and parallelism.

However, step 2 always gave error

Caused by: java.lang.IllegalStateException: Failed to rollback to savepoint
hdfs://10.106.238.14:/tmp/savepoint-767421-20907d234655. Cannot map
savepoint state for operator 37dfe905df17858e07858039ce3d8ae1 to the new
program, because the operator is not available in the new program. If you
want to allow to skip this, you can set the --allowNonRestoredState option
on the CLI.
at org.apache.flink.runtime.checkpoint.savepoint.SavepointLoade
r.loadAndValidateSavepoint(SavepointLoader.java:130)
at org.apache.flink.runtime.checkpoint.CheckpointCoordinator.re
storeSavepoint(CheckpointCoordinator.java:1140)
at org.apache.flink.runtime.jobmanager.JobManager$$anonfun$org$
apache$flink$runtime$jobmanager$JobManager$$submitJob$1.apply$mcV$sp(JobMa
nager.scala:1386)
at org.apache.flink.runtime.jobmanager.JobManager$$anonfun$org$
apache$flink$runtime$jobmanager$JobManager$$submitJob$1.apply(JobManager.s
cala:1372)
at org.apache.flink.runtime.jobmanager.JobManager$$anonfun$org$
apache$flink$runtime$jobmanager$JobManager$$submitJob$1.apply(JobManager.s
cala:1372)
at scala.concurrent.impl.Future$PromiseCompletingRunnable.lifte
dTree1$1(Future.scala:24)
at scala.concurrent.impl.Future$PromiseCompletingRunnable.run(F
uture.scala:24)
at akka.dispatch.TaskInvocation.run(AbstractDispatcher.scala:40)
at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.
exec(AbstractDispatcher.scala:397)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(
ForkJoinPool.java:1339)
at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinW
orkerThread.java:107)

The procedure worked fine if parallelism was not changed.

Also want to mention that I didn't manually specify OperatorID in my job. The
document does mentioned manually OperatorID assignment is suggested, just
curious is that mandatory in my case to fix the problem I'm seeing, given
that my program doesn't change at all so the autogenerated operatorID
should be unchanged after parallelism increase?

thanks,
Lei

Re: problem with increase job parallelism

[Fabian Hueske <fh...@gmail.com>]

Hi Lei,

setting explicit operator ID should solve this issue.
As far as I know, the auto-generated operator id also depended on the
operator parallelism in previous versions of Flink (not sure until which
point).

Which version are you running?

Best, Fabian


2017-10-17 3:15 GMT+02:00 Lei Chen <le...@gmail.com>:

> Hi,
>
> We're trying to implement some module to help autoscale our pipeline which
> is built  with Flink on YARN. According to the document, the suggested
> procedure seems to be:
>
> 1. cancel job with savepoint
> 2. start new job with increased YARN TM number and parallelism.
>
> However, step 2 always gave error
>
> Caused by: java.lang.IllegalStateException: Failed to rollback to
> savepoint hdfs://10.106.238.14:/tmp/savepoint-767421-20907d234655. Cannot
> map savepoint state for operator 37dfe905df17858e07858039ce3d8ae1 to the
> new program, because the operator is not available in the new program. If
> you want to allow to skip this, you can set the --allowNonRestoredState
> option on the CLI.
> at org.apache.flink.runtime.checkpoint.savepoint.SavepointLoade
> r.loadAndValidateSavepoint(SavepointLoader.java:130)
> at org.apache.flink.runtime.checkpoint.CheckpointCoordinator.re
> storeSavepoint(CheckpointCoordinator.java:1140)
> at org.apache.flink.runtime.jobmanager.JobManager$$anonfun$org$
> apache$flink$runtime$jobmanager$JobManager$$submitJob$1.
> apply$mcV$sp(JobManager.scala:1386)
> at org.apache.flink.runtime.jobmanager.JobManager$$anonfun$org$
> apache$flink$runtime$jobmanager$JobManager$$submitJob$1.
> apply(JobManager.scala:1372)
> at org.apache.flink.runtime.jobmanager.JobManager$$anonfun$org$
> apache$flink$runtime$jobmanager$JobManager$$submitJob$1.
> apply(JobManager.scala:1372)
> at scala.concurrent.impl.Future$PromiseCompletingRunnable.lifte
> dTree1$1(Future.scala:24)
> at scala.concurrent.impl.Future$PromiseCompletingRunnable.run(F
> uture.scala:24)
> at akka.dispatch.TaskInvocation.run(AbstractDispatcher.scala:40)
> at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.
> exec(AbstractDispatcher.scala:397)
> at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
> at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(For
> kJoinPool.java:1339)
> at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPoo
> l.java:1979)
> at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinW
> orkerThread.java:107)
>
> The procedure worked fine if parallelism was not changed.
>
> Also want to mention that I didn't manually specify OperatorID in my job. The
> document does mentioned manually OperatorID assignment is suggested, just
> curious is that mandatory in my case to fix the problem I'm seeing, given
> that my program doesn't change at all so the autogenerated operatorID
> should be unchanged after parallelism increase?
>
> thanks,
> Lei
>