[
https://issues.apache.org/jira/browse/SPARK-6954?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Cheolsoo Park updated SPARK-6954:
---------------------------------
Description:
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 the request to add executors fails with the
above error. In fact, the job itself continues to run with whatever executors
it already has, but it never gets more executors unless the shell is closed and
restarted.
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.
was:
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 above 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.
> 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
> Labels: yarn
>
> 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 the request to add executors fails with the
> above error. In fact, the job itself continues to run with whatever executors
> it already has, but it never gets more executors unless the shell is closed
> and restarted.
> 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.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
