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From Guillermo Ortiz <konstt2...@gmail.com>
Subject Re: Uncaught exception in thread delete Spark local dirs
Date Sat, 27 Jun 2015 09:32:35 GMT
I'm checking the logs in YARN and I found this error as well

Application application_1434976209271_15614 failed 2 times due to AM
Container for appattempt_1434976209271_15614_000002 exited with exitCode:
255


Diagnostics: Exception from container-launch.
Container id: container_1434976209271_15614_02_000001
Exit code: 255
Stack trace: ExitCodeException exitCode=255:
at org.apache.hadoop.util.Shell.runCommand(Shell.java:538)
at org.apache.hadoop.util.Shell.run(Shell.java:455)
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:715)
at
org.apache.hadoop.yarn.server.nodemanager.LinuxContainerExecutor.launchContainer(LinuxContainerExecutor.java:293)
at
org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:302)
at
org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:82)
at java.util.concurrent.FutureTask.run(FutureTask.java:262)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
Shell output: Requested user hdfs is not whitelisted and has id 496,which
is below the minimum allowed 1000
Container exited with a non-zero exit code 255
Failing this attempt. Failing the application.

2015-06-27 11:25 GMT+02:00 Guillermo Ortiz <konstt2000@gmail.com>:

> Well SPARK_CLASSPATH it's just a random name, the complete script is this:
>
> export HADOOP_CONF_DIR=/etc/hadoop/conf
>
> SPARK_CLASSPATH="file:/usr/metrics/conf/elasticSearch.properties,file:/usr/metrics/conf/redis.properties,/etc/spark/conf.cloudera.spark_on_yarn/yarn-conf/"
> for lib in `ls /usr/metrics/lib/*.jar`
> do
>         if [ -z "$SPARK_CLASSPATH" ]; then
> SPARK_CLASSPATH=$lib
> else
> SPARK_CLASSPATH=$SPARK_CLASSPATH,$lib
> fi
> done
> spark-submit --name "Metrics"....
>
> I need to add all the jars as you know,, maybe it was a bad name
> SPARK_CLASSPATH
>
> The code doesn't have any stateful operation, yo I guess that it¡s okay
> doesn't have checkpoint. I have executed hundres of times thiscode in VM
> from Cloudera and never got this error.
>
> 2015-06-27 11:21 GMT+02:00 Tathagata Das <tdas@databricks.com>:
>
>> 1. you need checkpointing mostly for recovering from driver failures, and
>> in some cases also for some stateful operations.
>>
>> 2. Could you try not using the SPARK_CLASSPATH environment variable.
>>
>> TD
>>
>> On Sat, Jun 27, 2015 at 1:00 AM, Guillermo Ortiz <konstt2000@gmail.com>
>> wrote:
>>
>>> I don't have any checkpoint on my code. Really, I don't have to save any
>>> state. It's just a log processing of a PoC.
>>> I have been testing the code in a VM from Cloudera and I never got that
>>> error.. Not it's a real cluster.
>>>
>>> The command to execute Spark
>>> spark-submit --name "PoC Logs" --master yarn-client --class
>>> com.metrics.MetricsSpark --jars $SPARK_CLASSPATH --executor-memory 1g
>>> /usr/metrics/ex/metrics-spark.jar $1 $2 $3
>>>
>>>     val sparkConf = new SparkConf()
>>>     val ssc = new StreamingContext(sparkConf, Seconds(5))
>>>     val kafkaParams = Map[String, String]("metadata.broker.list" ->
>>> args(0))
>>>     val topics = args(1).split("\\,")
>>>     val directKafkaStream = KafkaUtils.createDirectStream[String,
>>> String, StringDecoder, StringDecoder](ssc, kafkaParams, topics.toSet)
>>>
>>>     directKafkaStream.foreachRDD { rdd =>
>>>       val offsets = rdd.asInstanceOf[HasOffsetRanges].offsetRanges
>>>       val documents = rdd.mapPartitionsWithIndex { (i, kafkaEvent) =>
>>>       .....
>>>    }
>>>
>>> I understand that I just need a checkpoint if I need to recover the task
>>> it something goes wrong, right?
>>>
>>>
>>> 2015-06-27 9:39 GMT+02:00 Tathagata Das <tdas@databricks.com>:
>>>
>>>> How are you trying to execute the code again? From checkpoints, or
>>>> otherwise?
>>>> Also cc'ed Hari who may have a better idea of YARN related issues.
>>>>
>>>> On Sat, Jun 27, 2015 at 12:35 AM, Guillermo Ortiz <konstt2000@gmail.com
>>>> > wrote:
>>>>
>>>>> Hi,
>>>>>
>>>>> I'm executing a SparkStreamig code with Kafka. IçThe code was working
>>>>> but today I tried to execute the code again and I got an exception, I
dn't
>>>>> know what's it happening. right now , there are no jobs executions on
YARN.
>>>>> How could it fix it?
>>>>>
>>>>> Exception in thread "main" org.apache.spark.SparkException: Yarn
>>>>> application has already ended! It might have been killed or unable to
>>>>> launch application master.
>>>>>         at
>>>>> org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.waitForApplication(YarnClientSchedulerBackend.scala:113)
>>>>>         at
>>>>> org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:59)
>>>>>         at
>>>>> org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:141)
>>>>>         at org.apache.spark.SparkContext.<init>(SparkContext.scala:379)
>>>>>         at
>>>>> org.apache.spark.streaming.StreamingContext$.createNewSparkContext(StreamingContext.scala:642)
>>>>>         at
>>>>> org.apache.spark.streaming.StreamingContext.<init>(StreamingContext.scala:75)
>>>>>         at
>>>>> com.produban.metrics.MetricsTransfInternationalSpark$.main(MetricsTransfInternationalSpark.scala:66)
>>>>>         at
>>>>> com.produban.metrics.MetricsTransfInternationalSpark.main(MetricsTransfInternationalSpark.scala)
>>>>>         at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
>>>>>         at
>>>>> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
>>>>>         at
>>>>> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
>>>>>         at java.lang.reflect.Method.invoke(Method.java:606)
>>>>>         at
>>>>> org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:569)
>>>>>         at
>>>>> org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:166)
>>>>>         at
>>>>> org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:189)
>>>>>         at
>>>>> org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:110)
>>>>>         at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
>>>>> *15/06/27 09:27:09 ERROR Utils: Uncaught exception in thread delete
>>>>> Spark local dirs*
>>>>> java.lang.NullPointerException
>>>>>         at org.apache.spark.storage.DiskBlockManager.org
>>>>> $apache$spark$storage$DiskBlockManager$$doStop(DiskBlockManager.scala:161)
>>>>>         at
>>>>> org.apache.spark.storage.DiskBlockManager$$anon$1$$anonfun$run$1.apply$mcV$sp(DiskBlockManager.scala:141)
>>>>>         at
>>>>> org.apache.spark.storage.DiskBlockManager$$anon$1$$anonfun$run$1.apply(DiskBlockManager.scala:139)
>>>>>         at
>>>>> org.apache.spark.storage.DiskBlockManager$$anon$1$$anonfun$run$1.apply(DiskBlockManager.scala:139)
>>>>>         at
>>>>> org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1617)
>>>>>         at
>>>>> org.apache.spark.storage.DiskBlockManager$$anon$1.run(DiskBlockManager.scala:139)
>>>>> Exception in thread "delete Spark local dirs"
>>>>> java.lang.NullPointerException
>>>>>         at org.apache.spark.storage.DiskBlockManager.org
>>>>> $apache$spark$storage$DiskBlockManager$$doStop(DiskBlockManager.scala:161)
>>>>>         at
>>>>> org.apache.spark.storage.DiskBlockManager$$anon$1$$anonfun$run$1.apply$mcV$sp(DiskBlockManager.scala:141)
>>>>>         at
>>>>> org.apache.spark.storage.DiskBlockManager$$anon$1$$anonfun$run$1.apply(DiskBlockManager.scala:139)
>>>>>         at
>>>>> org.apache.spark.storage.DiskBlockManager$$anon$1$$anonfun$run$1.apply(DiskBlockManager.scala:139)
>>>>>         at
>>>>> org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1617)
>>>>>         at
>>>>> org.apache.spark.storage.DiskBlockManager$$anon$1.run(DiskBlockManager.scala:139)
>>>>>
>>>>>
>>>>>
>>>>>
>>>>
>>>
>>
>

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