[jira] [Assigned] (FLINK-7153) Eager Scheduling can't allocate source for ExecutionGraph correctly

["Stephan Ewen (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/FLINK-7153?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Stephan Ewen reassigned FLINK-7153:
-----------------------------------

    Assignee: Stephan Ewen

> 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: Stephan Ewen
>             Fix For: 1.3.2
>
>
> 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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