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https://issues.apache.org/jira/browse/FLINK-7153?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16235477#comment-16235477
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ASF GitHub Bot commented on FLINK-7153:
---------------------------------------

Github user tillrohrmann commented on the issue:

    https://github.com/apache/flink/pull/4916
  
    Thanks a lot for your review @StephanEwen and @sihuazhou. I've addressed 
all your comments @StephanEwen. 
    
    Next thing I'll do is to rebase onto the latest master and if Travis gives 
green light and you have no further objections, then I would like to merge it.


> Eager Scheduling can't allocate source for ExecutionGraph correctly
> -------------------------------------------------------------------
>
>                 Key: FLINK-7153
>                 URL: https://issues.apache.org/jira/browse/FLINK-7153
>             Project: Flink
>          Issue Type: Bug
>          Components: JobManager
>    Affects Versions: 1.3.1
>            Reporter: Sihua Zhou
>            Assignee: Till Rohrmann
>            Priority: Critical
>             Fix For: 1.4.0, 1.3.3
>
>
> The ExecutionGraph.scheduleEager() function allocate for ExecutionJobVertex 
> one by one via calling ExecutionJobVertex.allocateResourcesForAll(), here is 
> two problem about it:
> 1. The ExecutionVertex.getPreferredLocationsBasedOnInputs will always return 
> empty, cause `sourceSlot` always be null until `ExectionVertex` has been 
> deployed via 'Execution.deployToSlot()'. So allocate resource base on 
> prefered location can't work correctly, we need to set the slot info for 
> `Execution` as soon as Execution.allocateSlotForExecution() called 
> successfully?
> 2. Current allocate strategy can't allocate the slot optimize.  Here is the 
> test case:
> {code}
> JobVertex v1 = new JobVertex("v1", jid1);
> JobVertex v2 = new JobVertex("v2", jid2);
> SlotSharingGroup group = new SlotSharingGroup();
> v1.setSlotSharingGroup(group);
> v2.setSlotSharingGroup(group);
> v1.setParallelism(2);
> v2.setParallelism(4);
> v1.setInvokableClass(BatchTask.class);
> v2.setInvokableClass(BatchTask.class);
> v2.connectNewDataSetAsInput(v1, DistributionPattern.POINTWISE, 
> ResultPartitionType.PIPELINED_BOUNDED);
> {code}
> Currently, after allocate for v1,v2, we got a local partition and three 
> remote partition. But actually, it should be 2 local partition and 2 remote 
> partition. 
> The causes of the above problems is becuase that the current allocate 
> strategy is allocate the resource for execution one by one(if the execution 
> can allocate from SlotGroup than get it, Otherwise ask for a new one for it). 
> If we change the allocate strategy to two step will solve this problem, below 
> is the Pseudo code:
> {code}
> for (ExecutionJobVertex ejv: getVerticesTopologically) {
> //step 1: try to allocate from SlothGroup base on inputs one by one (which 
> only allocate resource base on location).
> //step 2: allocate for the remain execution.
> }
> {code}



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