Hello, has anyone found this problem before? I am sorry to insist but I can
not guess what is happening. Should I ask to the dev mailing list? Many
thanks in advance.
El 05/03/2014 23:57, "Christian" <chri...@gmail.com> escribió:

> I have deployed a Spark cluster in standalone mode with 3 machines:
>
> node1/192.168.1.2 -> master
> node2/192.168.1.3 -> worker 20 cores 12g
> node3/192.168.1.4 -> worker 20 cores 12g
>
> The web interface shows the workers correctly.
>
> When I launch the scala job (which only requires 256m of memory) these are
> the logs:
>
> 14/03/05 23:24:06 INFO scheduler.TaskSchedulerImpl: Adding task set 0.0
> with 55 tasks
> 14/03/05 23:24:21 WARN scheduler.TaskSchedulerImpl: Initial job has not
> accepted any resources; check your cluster UI to ensure that workers are
> registered and have sufficient memory
> 14/03/05 23:24:23 INFO client.AppClient$ClientActor: Connecting to master
> spark://node1:7077...
> 14/03/05 23:24:36 WARN scheduler.TaskSchedulerImpl: Initial job has not
> accepted any resources; check your cluster UI to ensure that workers are
> registered and have sufficient memory
> 14/03/05 23:24:43 INFO client.AppClient$ClientActor: Connecting to master
> spark://node1:7077...
> 14/03/05 23:24:51 WARN scheduler.TaskSchedulerImpl: Initial job has not
> accepted any resources; check your cluster UI to ensure that workers are
> registered and have sufficient memory
> 14/03/05 23:25:03 ERROR client.AppClient$ClientActor: All masters are
> unresponsive! Giving up.
> 14/03/05 23:25:03 ERROR cluster.SparkDeploySchedulerBackend: Spark cluster
> looks dead, giving up.
> 14/03/05 23:25:03 INFO scheduler.TaskSchedulerImpl: Remove TaskSet 0.0
> from pool
> 14/03/05 23:25:03 INFO scheduler.DAGScheduler: Failed to run
> saveAsNewAPIHadoopFile at CondelCalc.scala:146
> Exception in thread "main" org.apache.spark.SparkException: Job aborted:
> Spark cluster looks down
>         at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$org$apache$spark$scheduler$DAGScheduler$$abortStage$1.apply(DAGScheduler.scala:1028)
> ...
>
> The generated logs by the master and the 2 workers are attached, but I
> found something weird in the master logs:
>
> 14/03/05 23:37:43 INFO master.Master: Registering worker *node1:57297*with 20 
> cores, 12.0 GB RAM
> 14/03/05 23:37:43 INFO master.Master: Registering worker *node1:34188*with 20 
> cores, 12.0 GB RAM
>
> It reports that the two workers are node1:57297 and node1:34188 instead of
> node3 and node2 respectively.
>
> $ cat /etc/hosts
> ...
> 192.168.1.2 node1
> 192.168.1.3 node2
> 192.168.1.4 node3
> ...
>
> $ nslookup node2
> Server:         192.168.1.1
> Address:        192.168.1.1#53
>
> Name:   node2.cluster.local
> Address: 192.168.1.3
>
> $ nslookup node3
> Server:         192.168.1.1
> Address:        192.168.1.1#53
>
> Name:   node3.cluster.local
> Address: 192.168.1.4
>
> $ ssh node1 "ps aux | grep spark"
> cperez   17023  1.4  0.1 4691944 154532 pts/3  Sl   23:37   0:15
> /data/users/cperez/opt/jdk/bin/java -cp
> :/data/users/cperez/opt/spark-0.9.0-incubating-bin-hadoop2/conf:/data/users/cperez/opt/spark-0.9.0-incubating-bin-hadoop2/assembly/target/scala-2.10/spark-assembly-0.9.0-incubating-hadoop2.2.0.jar:/data/users/cperez/opt/hadoop-2.2.0/etc/hadoop
> -Dspark.akka.logLifecycleEvents=true -Djava.library.path= -Xms512m -Xmx512m
> org.apache.spark.deploy.master.Master --ip node1 --port 7077 --webui-port
> 8080
>
> $ ssh node2 "ps aux | grep spark"
> cperez   17511  2.7  0.1 4625248 156304 ?      Sl   23:37   0:07
> /data/users/cperez/opt/jdk/bin/java -cp
> :/data/users/cperez/opt/spark-0.9.0-incubating-bin-hadoop2/conf:/data/users/cperez/opt/spark-0.9.0-incubating-bin-hadoop2/assembly/target/scala-2.10/spark-assembly-0.9.0-incubating-hadoop2.2.0.jar:/data/users/cperez/opt/hadoop-2.2.0/etc/hadoop
> -Dspark.akka.logLifecycleEvents=true -Djava.library.path= -Xms512m -Xmx512m
> org.apache.spark.deploy.worker.Worker spark://node1:7077
>
> $ ssh node2 "netstat -lptun | grep 17511"
> tcp        0      0 :::8081                     :::*
>  LISTEN      17511/java
> tcp        0      0 ::ffff:192.168.1.3:34188    :::*
>    LISTEN      17511/java
>
> $ ssh node3 "ps aux | grep spark"
> cperez    7543  1.9  0.1 4625248 158600 ?      Sl   23:37   0:09
> /data/users/cperez/opt/jdk/bin/java -cp
> :/data/users/cperez/opt/spark-0.9.0-incubating-bin-hadoop2/conf:/data/users/cperez/opt/spark-0.9.0-incubating-bin-hadoop2/assembly/target/scala-2.10/spark-assembly-0.9.0-incubating-hadoop2.2.0.jar:/data/users/cperez/opt/hadoop-2.2.0/etc/hadoop
> -Dspark.akka.logLifecycleEvents=true -Djava.library.path= -Xms512m -Xmx512m
> org.apache.spark.deploy.worker.Worker spark://node1:7077
>
> $ ssh node3 "netstat -lptun | grep 7543"
> tcp        0      0 :::8081                     :::*
>  LISTEN      7543/java
> tcp        0      0 ::ffff:192.168.1.4:57297    :::*
>    LISTEN      7543/java
>
> I am completely blocked at this, any help would be very helpful to me.
> Many thanks in advance.
> Christian
>

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