[2022-03-08 15:23:14.742]Container exited with a non-zero exit code 50. Error file: prelaunch.err. Last 4096 bytes of prelaunch.err : Last 4096 bytes of stderr : SLF4J: Class path contains multiple SLF4J bindings. SLF4J: Found binding in [jar:file:/srv/BigData/data1/nm/localdir/filecache/10/spark-archive-2x.zip/slf4j-log4j12-1.7.30.jar!/org/slf4j/impl/StaticLoggerBinder.class] SLF4J: Found binding in [jar:file:/opt/Bigdata/FusionInsight_HD_8.1.0.1/install/FusionInsight-Hadoop-3.1.1/hadoop/share/hadoop/common/lib/slf4j-log4j12-1.7.30.jar!/org/slf4j/impl/StaticLoggerBinder.class] SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation. SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory] . Blacklisting behavior can be configured via spark.blacklist.*. at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:2027) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1972) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1971) at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1971) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:987) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:987) at scala.Option.foreach(Option.scala:257) at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:987) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doonReceive(DAGScheduler.scala:2207) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2156) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2145) at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49) at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:794) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2234) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2255) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2274) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2299) at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:979) at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:977) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112) at org.apache.spark.rdd.RDD.withScope(RDD.scala:384) at org.apache.spark.rdd.RDD.foreachPartition(RDD.scala:977) at com.ck.data.stream.spark.chat.AggregationChatStream$$anonfun$apply$1.apply(AggregationChatStream.scala:51) at com.ck.data.stream.spark.chat.AggregationChatStream$$anonfun$apply$1.apply(AggregationChatStream.scala:49) at org.apache.spark.streaming.dstream.DStream$$anonfun$foreachRDD$1$$anonfun$apply$mcV$sp$3.apply(DStream.scala:636) at org.apache.spark.streaming.dstream.DStream$$anonfun$foreachRDD$1$$anonfun$apply$mcV$sp$3.apply(DStream.scala:636) at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(ForEachDStream.scala:51) at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:51) at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:51) at org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:420) at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply$mcV$sp(ForEachDStream.scala:50) at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:50) at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:50) at scala.util.Try$.apply(Try.scala:192) at org.apache.spark.streaming.scheduler.Job.run(Job.scala:39) at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply$mcV$sp(JobScheduler.scala:259) at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:259) at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:259) at scala.util.DynamicVariable.withValue(DynamicVariable.scala:58) at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler.run(JobScheduler.scala:258) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748) | org.apache.spark.deploy.yarn.Client.logError(Logging.scala:70) Exception in thread "main" org.apache.spark.SparkException: Application application_1645201388160_2583 finished with failed status at org.apache.spark.deploy.yarn.Client.run(Client.scala:1234) at org.apache.spark.deploy.yarn.YarnClusterApplication.start(Client.scala:1611) at org.apache.spark.deploy.SparkSubmit.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:882) at org.apache.spark.deploy.SparkSubmit.doRunMain$1(SparkSubmit.scala:164) at org.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:187) at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:89) at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:957) at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:966) at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)背景
spark-streaming读取kafka的数据写入到hbase。程序执行了三天没有任何问题
