It should be a problem of my data quality. It's curious why the driver-side exception stack has no specific exception information.
Edgardo Szrajber <szraj...@yahoo.com> 于2020年4月28日周二 下午3:32写道： > The exception occured while aborting the stage. It might be interesting to > try to understand the reason for the abortion. > Maybe timeout? How long the query run? > Bentzi > > Sent from Yahoo Mail on Android > <https://go.onelink.me/107872968?pid=InProduct&c=Global_Internal_YGrowth_AndroidEmailSig__AndroidUsers&af_wl=ym&af_sub1=Internal&af_sub2=Global_YGrowth&af_sub3=EmailSignature> > > On Tue, Apr 28, 2020 at 9:25, Jungtaek Lim > <kabhwan.opensou...@gmail.com> wrote: > The root cause of exception is occurred in executor side "Lost task 10.3 > in stage 1.0 (TID 81, spark6, executor 1)" so you may need to check there. > > On Tue, Apr 28, 2020 at 2:52 PM lec ssmi <shicheng31...@gmail.com> wrote: > > Hi： > One of my long-running queries occasionally encountered the following > exception: > > > Caused by: org.apache.spark.SparkException: Job aborted due to stage > failure: Task 10 in stage 1.0 failed 4 times, most recent failure: Lost > task 10.3 in stage 1.0 (TID 81, spark6, executor 1): > java.lang.NullPointerException > Driver stacktrace: > at org.apache.spark.scheduler.DAGScheduler.org > $apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1602) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1590) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1589) > at > scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) > at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) > at > org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1589) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831) > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831) > at scala.Option.foreach(Option.scala:257) > at > org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:831) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1823) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1772) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1761) > at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) > at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:642) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:2034) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:2055) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:2074) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:2099) > at > org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:929) > at > org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:927) > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112) > at org.apache.spark.rdd.RDD.withScope(RDD.scala:363) > at org.apache.spark.rdd.RDD.foreachPartition(RDD.scala:927) > at > org.apache.spark.sql.execution.streaming.ForeachSink.addBatch(ForeachSink.scala:49) > at > org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$org$apache$spark$sql$execution$streaming$MicroBatchExecution$$runBatch$3$$anonfun$apply$16.apply(MicroBatchExecution.scala:475) > at > org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:77) > at > org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$org$apache$spark$sql$execution$streaming$MicroBatchExecution$$runBatch$3.apply(MicroBatchExecution.scala:473) > at > org.apache.spark.sql.execution.streaming.ProgressReporter$class.reportTimeTaken(ProgressReporter.scala:271) > at > org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:58) > at org.apache.spark.sql.execution.streaming.MicroBatchExecution.org > $apache$spark$sql$execution$streaming$MicroBatchExecution$$runBatch(MicroBatchExecution.scala:472) > at > org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$runActivatedStream$1$$anonfun$apply$mcZ$sp$1.apply$mcV$sp(MicroBatchExecution.scala:133) > at > org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$runActivatedStream$1$$anonfun$apply$mcZ$sp$1.apply(MicroBatchExecution.scala:121) > at > org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$runActivatedStream$1$$anonfun$apply$mcZ$sp$1.apply(MicroBatchExecution.scala:121) > at > org.apache.spark.sql.execution.streaming.ProgressReporter$class.reportTimeTaken(ProgressReporter.scala:271) > at > org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:58) > at > org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$runActivatedStream$1.apply$mcZ$sp(MicroBatchExecution.scala:121) > at > org.apache.spark.sql.execution.streaming.ProcessingTimeExecutor.execute(TriggerExecutor.scala:56) > at > org.apache.spark.sql.execution.streaming.MicroBatchExecution.runActivatedStream(MicroBatchExecution.scala:117) > at org.apache.spark.sql.execution.streaming.StreamExecution.org > $apache$spark$sql$execution$streaming$StreamExecution$$runStream(StreamExecution.scala:279) > ... 1 more > > > > According to the exception stack, it seems to have nothing to do with the > logic of my code.Is this a spark bug or something? The version of spark is > 2.3.1. > > Best > Lec Ssmi > >
