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https://issues.apache.org/jira/browse/SPARK-12554?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Lijie Xu updated SPARK-12554:
-----------------------------
    Description: 
In scheduleExecutorsOnWorker() in Master.scala,
*val keepScheduling = coresToAssign >= minCoresPerExecutor* should be changed 
to *val keepScheduling = coresToAssign > 0*

Suppose that an app's requested cores is 10 (i.e., spark.cores.max = 10) and 
app.coresPerExecutor is 4 (i.e., spark.executor.cores = 4). 

After allocating two executors (each has 4 cores) to this app, the 
*coresToAssign = 2* and *minCoresPerExecutor = coresPerExecutor = 4*, so 
*keepScheduling = false* and no extra executor will be allocated to the app. If 
*spark.scheduler.minRegisteredResourcesRatio* is set to a large number (e.g., > 
0.8 in this case), the app will hang and never finish.

Another case: if a small app's coresPerExecutor is larger than its requested 
cores (e.g., spark.cores.max = 10, spark.executor.cores = 16), *val 
keepScheduling = coresToAssign >= minCoresPerExecutor* is always FALSE. As a 
result, this app will hang and never finish.



  was:
In scheduleExecutorsOnWorker() in Master.scala,
*val keepScheduling = coresToAssign >= minCoresPerExecutor* should be changed 
to *val keepScheduling = coresToAssign > 0*

Suppose that an app's requested cores is 10 (i.e., spark.cores.max = 10) and 
app.coresPerExecutor is 4 (i.e., spark.executor.cores = 4). 

After allocating two executors (each has 4 cores) to this app, the 
*coresToAssign = 2* and *minCoresPerExecutor = coresPerExecutor = 4*, so 
*keepScheduling = false* and no extra executor will be allocated to the app. If 
*spark.scheduler.minRegisteredResourcesRatio* is set to a large number (e.g., > 
0.8 in this case), the app will hang and never finish.

In particular, if a small app's coresPerExecutor is larger than its requested 
cores (e.g., spark.cores.max = 10, spark.executor.cores = 16), *val 
keepScheduling = coresToAssign >= minCoresPerExecutor* is always FALSE. As a 
result, this app will hang and never finish.




> Standalone app scheduler will hang when app.coreToAssign < minCoresPerExecutor
> ------------------------------------------------------------------------------
>
>                 Key: SPARK-12554
>                 URL: https://issues.apache.org/jira/browse/SPARK-12554
>             Project: Spark
>          Issue Type: Bug
>          Components: Deploy, Scheduler
>    Affects Versions: 1.5.2
>            Reporter: Lijie Xu
>            Priority: Critical
>
> In scheduleExecutorsOnWorker() in Master.scala,
> *val keepScheduling = coresToAssign >= minCoresPerExecutor* should be changed 
> to *val keepScheduling = coresToAssign > 0*
> Suppose that an app's requested cores is 10 (i.e., spark.cores.max = 10) and 
> app.coresPerExecutor is 4 (i.e., spark.executor.cores = 4). 
> After allocating two executors (each has 4 cores) to this app, the 
> *coresToAssign = 2* and *minCoresPerExecutor = coresPerExecutor = 4*, so 
> *keepScheduling = false* and no extra executor will be allocated to the app. 
> If *spark.scheduler.minRegisteredResourcesRatio* is set to a large number 
> (e.g., > 0.8 in this case), the app will hang and never finish.
> Another case: if a small app's coresPerExecutor is larger than its requested 
> cores (e.g., spark.cores.max = 10, spark.executor.cores = 16), *val 
> keepScheduling = coresToAssign >= minCoresPerExecutor* is always FALSE. As a 
> result, this app will hang and never finish.



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