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 <konstt2...@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 $3
>
> val sparkConf = new SparkConf()
> val ssc = new StreamingContext(sparkConf, Seconds(5))
> val kafkaParams = Map[String, String]("metadata.broker.list" ->
> args(0))
> val topics = args(1).split("\\,")
> val directKafkaStream = KafkaUtils.createDirectStream[String, String,
> StringDecoder, StringDecoder](ssc, kafkaParams, topics.toSet)
>
> directKafkaStream.foreachRDD { rdd =>
> val offsets = rdd.asInstanceOf[HasOffsetRanges].offsetRanges
> val documents = rdd.mapPartitionsWithIndex { (i, kafkaEvent) =>
> .....
> }
>
> I understand that I just need a checkpoint if I need to recover the task
> it something goes wrong, right?
>
>
> 2015-06-27 9:39 GMT+02:00 Tathagata Das <t...@databricks.com>:
>
>> How are you trying to execute the code again? From checkpoints, or
>> otherwise?
>> Also cc'ed Hari who may have a better idea of YARN related issues.
>>
>> On Sat, Jun 27, 2015 at 12:35 AM, Guillermo Ortiz <konstt2...@gmail.com>
>> wrote:
>>
>>> Hi,
>>>
>>> I'm executing a SparkStreamig code with Kafka. IçThe code was working
>>> but today I tried to execute the code again and I got an exception, I dn't
>>> know what's it happening. right now , there are no jobs executions on YARN.
>>> How could it fix it?
>>>
>>> Exception in thread "main" org.apache.spark.SparkException: Yarn
>>> application has already ended! It might have been killed or unable to
>>> launch application master.
>>> at
>>> org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.waitForApplication(YarnClientSchedulerBackend.scala:113)
>>> at
>>> org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:59)
>>> at
>>> org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:141)
>>> at org.apache.spark.SparkContext.<init>(SparkContext.scala:379)
>>> at
>>> org.apache.spark.streaming.StreamingContext$.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)
>>>
>>>
>>>
>>>
>>
>
