[jira] [Commented] (FLINK-3020) Local execution: set number of task manager slots to the maximum parallelism

["Maximilian Michels (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/FLINK-3020?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15007003#comment-15007003 ] 

Maximilian Michels commented on FLINK-3020:
-------------------------------------------

Just saw, this is already the case for the batch API. We should change this for the streaming API then..

> 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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