You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "yangping wu (JIRA)" <ji...@apache.org> on 2015/04/14 05:17:12 UTC

[jira] [Created] (SPARK-6892) Recovery from checkpoint will also reuse the application id when write eventLog in yarn-cluster mode

yangping wu created SPARK-6892:
----------------------------------

             Summary: Recovery from checkpoint will also reuse the application id when write eventLog in yarn-cluster mode
                 Key: SPARK-6892
                 URL: https://issues.apache.org/jira/browse/SPARK-6892
             Project: Spark
          Issue Type: Bug
          Components: Streaming
    Affects Versions: 1.3.0
            Reporter: yangping wu
            Priority: Critical


When I recovery from checkpoint  in yarn-cluster mode using Spark Streaming,  I found it will reuse the application id (In my case is application_1428664056212_0016) before falid to write spark eventLog, But now my application id is application_1428664056212_0017,then spark write eventLog will falid, the stacktrace as follow:
{code}
15/04/14 10:14:01 WARN util.ShutdownHookManager: ShutdownHook '$anon$3' failed, java.io.IOException: Target log file already exists (hdfs://mycluster/spark-logs/eventLog/application_1428664056212_0016)
java.io.IOException: Target log file already exists (hdfs://mycluster/spark-logs/eventLog/application_1428664056212_0016)
	at org.apache.spark.scheduler.EventLoggingListener.stop(EventLoggingListener.scala:201)
	at org.apache.spark.SparkContext$$anonfun$stop$4.apply(SparkContext.scala:1388)
	at org.apache.spark.SparkContext$$anonfun$stop$4.apply(SparkContext.scala:1388)
	at scala.Option.foreach(Option.scala:236)
	at org.apache.spark.SparkContext.stop(SparkContext.scala:1388)
	at org.apache.spark.deploy.yarn.ApplicationMaster$$anon$3.run(ApplicationMaster.scala:107)
	at org.apache.hadoop.util.ShutdownHookManager$1.run(ShutdownHookManager.java:54)
{code}



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org