Cheolsoo Park created SPARK-6954:
------------------------------------

             Summary: Dynamic allocation: numExecutorsPending in 
ExecutorAllocationManager should never become negative
                 Key: SPARK-6954
                 URL: https://issues.apache.org/jira/browse/SPARK-6954
             Project: Spark
          Issue Type: Bug
          Components: YARN
    Affects Versions: 1.3.0
            Reporter: Cheolsoo Park
            Priority: Minor


I have a simple test case for dynamic allocation on YARN that fails with the 
following stack trace-
{code}
15/04/16 00:52:14 ERROR Utils: Uncaught exception in thread 
spark-dynamic-executor-allocation-0
java.lang.IllegalArgumentException: Attempted to request a negative number of 
executor(s) -21 from the cluster manager. Please specify a positive number!
        at 
org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend.requestTotalExecutors(CoarseGrainedSchedulerBackend.scala:338)
        at 
org.apache.spark.SparkContext.requestTotalExecutors(SparkContext.scala:1137)
        at 
org.apache.spark.ExecutorAllocationManager.addExecutors(ExecutorAllocationManager.scala:294)
        at 
org.apache.spark.ExecutorAllocationManager.addOrCancelExecutorRequests(ExecutorAllocationManager.scala:263)
        at 
org.apache.spark.ExecutorAllocationManager.org$apache$spark$ExecutorAllocationManager$$schedule(ExecutorAllocationManager.scala:230)
        at 
org.apache.spark.ExecutorAllocationManager$$anon$1$$anonfun$run$1.apply$mcV$sp(ExecutorAllocationManager.scala:189)
        at 
org.apache.spark.ExecutorAllocationManager$$anon$1$$anonfun$run$1.apply(ExecutorAllocationManager.scala:189)
        at 
org.apache.spark.ExecutorAllocationManager$$anon$1$$anonfun$run$1.apply(ExecutorAllocationManager.scala:189)
        at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1618)
        at 
org.apache.spark.ExecutorAllocationManager$$anon$1.run(ExecutorAllocationManager.scala:189)
        at 
java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:471)
        at java.util.concurrent.FutureTask.runAndReset(FutureTask.java:304)
        at 
java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$301(ScheduledThreadPoolExecutor.java:178)
        at 
java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:293)
        at 
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
        at 
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
        at java.lang.Thread.run(Thread.java:745)
{code}
My test is as follows-
# Start spark-shell with a single executor.
# Run a {{select count(\*)}} query. The number of executors rises as input size 
is non-trivial.
# After the job finishes, the number of  executors falls as most of them become 
idle.
# Rerun the same query again, and it fails with the following error-

In fact, this error only happens when I configure {{executorIdleTimeout}} very 
small. For eg, I can reproduce it with the following configs-
{code}
spark.dynamicAllocation.executorIdleTimeout     5
spark.dynamicAllocation.schedulerBacklogTimeout 5
{code}
Although I can simply increase {{executorIdleTimeout}} to something like 60 
secs to avoid the error, I think this is still a bug to be fixed.

The root cause seems that {{numExecutorsPending}} accidentally becomes negative 
if executors are killed too aggressively (i.e. {{executorIdleTimeout}} is too 
small) because under that circumstance, the new target # of executors can be 
smaller than the current # of executors. When that happens, 
{{ExecutorAllocationManager}} ends up trying to add a negative number of 
executors, which throws an exception.



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