问题描述
我在Hortonworks（2.6.4）上执行过Spark（2.4.4）结构流作业，在架构验证流作业将这些消息存储到HBASE和HIVE中之后，我正在从kafka主题中读取消息。
在执行6-7小时后，作业因 STATUS_INVALID_HANDLE 而死亡。 如果我删除了Hive Details，则此过程中不会出现此类异常。
HDFS中已经存在以下提到的路径。
有关解决此问题的任何帮助？
Caused by: org.apache.hadoop.ipc.remoteexception(java.io.IOException): Unexpected error: STATUS_INVALID_HANDLE with path="/dev/projects/spark-checkpoint/hive/BLR_TOPIC_1-cash_blr_db_cash_streax_blr_table/offsets/.287.b53c5d5e-7f59-4aec-a6a7-015813d44b43.tmp",permission=666,clientname=DFSClient_NONMAPREDUCE_237312562_34
at org.apache.hadoop.ipc.Client.call(Client.java:1475)
at org.apache.hadoop.ipc.Client.call(Client.java:1412)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:229)
at com.sun.proxy.$Proxy10.create(UnkNown Source)
at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolTranslatorPB.create(ClientNamenodeProtocolTranslatorPB.java:296)
at sun.reflect.GeneratedMethodAccessor147.invoke(UnkNown Source)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:497)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:191)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:102)
at com.sun.proxy.$Proxy11.create(UnkNown Source)
at org.apache.hadoop.hdfs.DFSOutputStream.newStreamForCreate(DFSOutputStream.java:1648)
at org.apache.hadoop.hdfs.DFSClient.primitiveCreate(DFSClient.java:1750)
at org.apache.hadoop.fs.Hdfs.createInternal(Hdfs.java:102)
at org.apache.hadoop.fs.Hdfs.createInternal(Hdfs.java:58)
at org.apache.hadoop.fs.AbstractFileSystem.create(AbstractFileSystem.java:584)
at org.apache.hadoop.fs.FileContext$3.next(FileContext.java:686)
at org.apache.hadoop.fs.FileContext$3.next(FileContext.java:682)
at org.apache.hadoop.fs.FSLinkResolver.resolve(FSLinkResolver.java:90)
at org.apache.hadoop.fs.FileContext.create(FileContext.java:688)
at org.apache.spark.sql.execution.streaming.FileContextBasedCheckpointFileManager.createTempFile(CheckpointFileManager.scala:311)
at org.apache.spark.sql.execution.streaming.CheckpointFileManager$RenameBasedFSDataOutputStream.<init>(CheckpointFileManager.scala:133)
at org.apache.spark.sql.execution.streaming.CheckpointFileManager$RenameBasedFSDataOutputStream.<init>(CheckpointFileManager.scala:136)
at org.apache.spark.sql.execution.streaming.FileContextBasedCheckpointFileManager.createAtomic(CheckpointFileManager.scala:318)
at org.apache.spark.sql.execution.streaming.HDFSMetadataLog.org$apache$spark$sql$execution$streaming$HDFSMetadataLog$$writeBatchToFile(HDFSMetadataLog.scala:123)
at org.apache.spark.sql.execution.streaming.HDFSMetadataLog$$anonfun$add$1.apply$mcZ$sp(HDFSMetadataLog.scala:112)
at org.apache.spark.sql.execution.streaming.HDFSMetadataLog$$anonfun$add$1.apply(HDFSMetadataLog.scala:110)
at org.apache.spark.sql.execution.streaming.HDFSMetadataLog$$anonfun$add$1.apply(HDFSMetadataLog.scala:110)
at scala.Option.getorElse(Option.scala:121)
at org.apache.spark.sql.execution.streaming.HDFSMetadataLog.add(HDFSMetadataLog.scala:110)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$org$apache$spark$sql$execution$streaming$MicroBatchExecution$$constructNextBatch$1$$anonfun$apply$mcZ$sp$3.apply$mcV$sp(MicroBatchExecution.scala:382)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$org$apache$spark$sql$execution$streaming$MicroBatchExecution$$constructNextBatch$1$$anonfun$apply$mcZ$sp$3.apply(MicroBatchExecution.scala:381)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$org$apache$spark$sql$execution$streaming$MicroBatchExecution$$constructNextBatch$1$$anonfun$apply$mcZ$sp$3.apply(MicroBatchExecution.scala:381)
at org.apache.spark.sql.execution.streaming.ProgressReporter$class.reportTiMetaken(ProgressReporter.scala:351)
at org.apache.spark.sql.execution.streaming.StreamExecution.reportTiMetaken(StreamExecution.scala:58)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$org$apache$spark$sql$execution$streaming$MicroBatchExecution$$constructNextBatch$1.apply$mcZ$sp(MicroBatchExecution.scala:381)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$org$apache$spark$sql$execution$streaming$MicroBatchExecution$$constructNextBatch$1.apply(MicroBatchExecution.scala:337)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$org$apache$spark$sql$execution$streaming$MicroBatchExecution$$constructNextBatch$1.apply(MicroBatchExecution.scala:337)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution.withProgressLocked(MicroBatchExecution.scala:557)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution.org$apache$spark$sql$execution$streaming$MicroBatchExecution$$constructNextBatch(MicroBatchExecution.scala:337)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$runActivatedStream$1$$anonfun$apply$mcZ$sp$1.apply$mcV$sp(MicroBatchExecution.scala:183)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$runActivatedStream$1$$anonfun$apply$mcZ$sp$1.apply(MicroBatchExecution.scala:166)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$runActivatedStream$1$$anonfun$apply$mcZ$sp$1.apply(MicroBatchExecution.scala:166)
at org.apache.spark.sql.execution.streaming.ProgressReporter$class.reportTiMetaken(ProgressReporter.scala:351)
at org.apache.spark.sql.execution.streaming.StreamExecution.reportTiMetaken(StreamExecution.scala:58)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$runActivatedStream$1.apply$mcZ$sp(MicroBatchExecution.scala:166)
at org.apache.spark.sql.execution.streaming.ProcessingTimeExecutor.execute(TriggerExecutor.scala:56)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution.runActivatedStream(MicroBatchExecution.scala:160)
at org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runStream(StreamExecution.scala:281) ```
解决方法
我们尝试在2.2.0，2.4.0和2.4.6的两个Spark版本上运行相同的代码。
Spark 2.4.6达到了我的目的，我没有看到 STATUS_INVALID_HANDLE 例外。