Maximilian Michels created FLINK-3020:
-----------------------------------------
Summary: Local execution: set number of task manager slots to the
maximum parallelism
Key: FLINK-3020
URL: https://issues.apache.org/jira/browse/FLINK-3020
Project: Flink
Issue Type: Bug
Components: Local Runtime
Affects Versions: 0.10.0
Reporter: Maximilian Michels
Assignee: Maximilian Michels
Priority: Minor
Fix For: 1.0.0, 0.10.1
Quite an inconvenience is the local execution configuration behavior. It sets
the number of task slots of the mini cluster to the default parallelism. This
causes problem if you use {{setParallelism(parallelism)}} on an operator and
set a parallelism larger than the default parallelism.
{noformat}
Caused by:
org.apache.flink.runtime.jobmanager.scheduler.NoResourceAvailableException: Not
enough free slots available to run the job. You can decrease the operator
parallelism or increase the number of slots per TaskManager in the
configuration. Task to schedule: < Attempt #0 (Flat Map (9/100)) @ (unassigned)
- [SCHEDULED] > with groupID < fa7240ee1fed08bd7e6278899db3e838 > in sharing
group < SlotSharingGroup [f3d578e9819be9c39ceee86cf5eb8c08,
8fa330746efa1d034558146e4604d0b4, fa7240ee1fed08bd7e6278899db3e838] >.
Resources available to scheduler: Number of instances=1, total number of
slots=8, available slots=0
at
org.apache.flink.runtime.jobmanager.scheduler.Scheduler.scheduleTask(Scheduler.java:256)
at
org.apache.flink.runtime.jobmanager.scheduler.Scheduler.scheduleImmediately(Scheduler.java:131)
at
org.apache.flink.runtime.executiongraph.Execution.scheduleForExecution(Execution.java:298)
at
org.apache.flink.runtime.executiongraph.ExecutionVertex.scheduleForExecution(ExecutionVertex.java:458)
at
org.apache.flink.runtime.executiongraph.ExecutionJobVertex.scheduleAll(ExecutionJobVertex.java:322)
at
org.apache.flink.runtime.executiongraph.ExecutionGraph.scheduleForExecution(ExecutionGraph.java:686)
at
org.apache.flink.runtime.jobmanager.JobManager$$anonfun$org$apache$flink$runtime$jobmanager$JobManager$$submitJob$1.apply$mcV$sp(JobManager.scala:982)
at
org.apache.flink.runtime.jobmanager.JobManager$$anonfun$org$apache$flink$runtime$jobmanager$JobManager$$submitJob$1.apply(JobManager.scala:962)
at
org.apache.flink.runtime.jobmanager.JobManager$$anonfun$org$apache$flink$runtime$jobmanager$JobManager$$submitJob$1.apply(JobManager.scala:962)
at
scala.concurrent.impl.Future$PromiseCompletingRunnable.liftedTree1$1(Future.scala:24)
at
scala.concurrent.impl.Future$PromiseCompletingRunnable.run(Future.scala:24)
at akka.dispatch.TaskInvocation.run(AbstractDispatcher.scala:41)
at
akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:401)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at
scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
... 2 more
{noformat}
I propose to change this behavior to setting the number of task slots to the
maximum parallelism present in the user program.
What do you think?
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