hive查询报错:java.io.IOException:org.apache.parquet.io.ParquetDecodingException spark-submit报错:Application application_1529650293575_0148 finished with failed status 2、 spark.executor.memoryOverhead 堆外内存(默认是executor内存的10%),当数据量比较大的时候,如果按默认的就会有下面的异常,导致程序崩溃 异常 ...
FINISHED) { // 将当前task从taskSet中正在执行的task列表中移除 taskSet.removeRunningTask(tid) //成功执行时,在线程池中处理任务的结果 taskResultGetter.enqueueSuccessfulTask(taskSet, tid, serializedData) //处理失败的情况 } else if (Set(TaskState.FAILED, TaskState.KILLED, TaskState.LOST).contains(...
Exception in thread "main" org.apache.spark.SparkException: Application finished with failed status at org.apache.spark.deploy.yarn.Client.run(Client.scala:622) at org.apache.spark.deploy.yarn.Client$.main(Client.scala:647) at org.apache.spark.deploy.yarn.Client.main(Client.scala) at sun.refl...
}// 任务运行结束,包括这几种状态FINISHED, FAILED, KILLED, LOSTif(TaskState.isFinished(state)) {// 清除关于这个task的一些簿记量cleanupTaskState(tid)// 将这个task从正在运行的task集合中移除taskSet.removeRunningTask(tid)if(state == TaskState.FINISHED) {// 启动一个线程,用来异步地处理任务成功的情...
2023-01-06 15:45:39,276 | INFO | [task-result-getter-2] | Finished task 0.0 in stage 1544.0 (TID 1702) in 48020 ms onZNFWZX-nodeHPgV0001.mrs-fzqf.com(executor 1) (2/3) | org.apache.spark.scheduler.TaskSetManager.logInfo(Logging.scala:54) ...
execBackend.statusUpdate(taskId,TaskState.FINISHED,serializedResult) 在CoarseGrainedExecutorBackend中会向driver发送StatusUpdate状态变更信息; 代码语言:javascript 复制 override defstatusUpdate(taskId:Long,state:TaskState,data:ByteBuffer){val msg=StatusUpdate(executorId,taskId,state,data)driver match{caseSome(...
Exception in thread "main" org.apache.spark.SparkException: Application application_1505642385307_0002 finished with failed status at org.apache.spark.deploy.yarn.Client.run(Client.scala:1104) at org.apache.spark.deploy.yarn.Client$.main(Client.scala:1150) ...
execBackend.statusUpdate(taskId, TaskState.FINISHED, serializedResult) 在CoarseGrainedExecutorBackend中会向driver发送StatusUpdate状态变更信息; override def statusUpdate(taskId: Long, state: TaskState, data: ByteBuffer) { val msg = StatusUpdate(executorId, taskId, state, data) ...
2) finishedTasks自增,当完成任务数finishedTasks等于全部任务数totalTasks时,标记job完成,并且唤醒等待的线程,即执行代码清单5-22中调用awaitResult方法的线程。 2. ShuffleMapTask任务的结果处理 如果是ShuffleMapTask,那么将执行下述代码所示的代码分支,其处理步骤如下: ...
Result=sparkEnv.blockManager.getRemoteBytes(blockId)//从远程获取计算结果if(!serializedTaskResult.isDefined){//若在任务执行结束后与我们去获取结果之间机器出现故障了//或者block manager 不得不刷新结果了//那么我们将不能够获取到结果scheduler.handleFailedTask(taskSetManager,tid,TaskState.FINISHED,TaskResult...