spark WARN scheduler.TaskSetManager: Lost task报错

spark提交代码发生以下错误

WARN scheduler.TaskSetManager: Lost task 224.0 in stage 0.0 (TID 224, zdbdsps025.iccc.com): 
ExecutorLostFailure (executor 2 exited caused by one of the running tasks) Reason:
 Container marked as failed: container_e55_1478671093534_0624_01_000003 on host: 
 zdbdsps025.iccc.com. Exit status: 143. Diagnostics: Container killed on request. 
 Exit code is 143

是因为yarn管理的某个节点掉了,所以spark将任务移至其他节点执行:
中间又报错:

16/11/15 14:30:43 WARN spark.HeartbeatReceiver: Removing executor 6 with no recent heartbeats: 133569 ms exceeds timeout 120000 ms

16/11/15 14:30:43 ERROR cluster.YarnScheduler: Lost executor 6 on zdbdsps027.iccc.com: Executor heartbeat timed out after 133569 ms

每个task 都超时了

16/11/15 14:30:43 WARN scheduler.TaskSetManager: Lost task 329.0 in stage 0.0 (TID 382, zdbdsps027.iccc.com): ExecutorLostFailure (executor 6 exited caused by one of the running tasks) Reason: Executor heartbeat timed out after 133569 ms

 

DAGScheduler发现Executor 6 也挂了,于是将executor移除

16/11/15 14:30:43 INFO scheduler.DAGScheduler: Executor lost: 6 (epoch 1)

16/11/15 14:30:43 INFO storage.BlockManagerMasterEndpoint: Trying to remove executor 6 from BlockManagerMaster.

16/11/15 14:30:43 INFO storage.BlockManagerMasterEndpoint: Removing block manager BlockManagerId(6, zdbdsps027.iccc.com, 38641)

16/11/15 14:30:43 INFO storage.BlockManagerMaster: Removed 6 successfully in removeExecutor

16/11/15 14:30:43 INFO cluster.YarnClientSchedulerBackend: Requesting to kill executor(s) 6

然后移至其他节点,随后又发现RPC出现问题

16/11/15 14:32:58 ERROR server.TransportRequestHandler: Error sending result RpcResponse{requestId=4735002570883429008, body=NioManagedBuffer{buf=java.nio.HeapByteBuffer[pos=0 lim=47 cap=47]}} to zdbdsps027.iccc.com/172.19.189.53:51057; closing connection

java.io.IOException: 断开的管道

    at sun.nio.ch.FileDispatcherImpl.write0(Native Method)

    at sun.nio.ch.SocketDispatcher.write(SocketDispatcher.java:47)

    at sun.nio.ch.IOUtil.writeFromNativeBuffer(IOUtil.java:93)

你可能感兴趣的:(Spark)