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Jungtaek Lim commented on SPARK-26385: -------------------------------------- Probably you may need to share the entire log messages logged under "org.apache.spark.deploy.yarn.security.AMCredentialRenewer" (Note: it runs on AM) so that we can confirm whether the renewing is scheduled and executed properly or not. It would be also helpful if you can make clear which mode you use - yarn-client vs yarn-cluster. > YARN - Spark Stateful Structured streaming HDFS_DELEGATION_TOKEN not found in > cache > ----------------------------------------------------------------------------------- > > Key: SPARK-26385 > URL: https://issues.apache.org/jira/browse/SPARK-26385 > Project: Spark > Issue Type: Bug > Components: Structured Streaming > Affects Versions: 2.4.0 > Environment: Hadoop 2.6.0, Spark 2.4.0 > Reporter: T M > Priority: Major > > > Hello, > > I have Spark Structured Streaming job which is runnning on YARN(Hadoop 2.6.0, > Spark 2.4.0). After 25-26 hours, my job stops working with following error: > {code:java} > 2018-12-16 22:35:17 ERROR > org.apache.spark.internal.Logging$class.logError(Logging.scala:91): Query > TestQuery[id = a61ce197-1d1b-4e82-a7af-60162953488b, runId = > a56878cf-dfc7-4f6a-ad48-02cf738ccc2f] terminated with error > org.apache.hadoop.ipc.RemoteException(org.apache.hadoop.security.token.SecretManager$InvalidToken): > token (token for REMOVED: HDFS_DELEGATION_TOKEN owner=REMOVED, renewer=yarn, > realUser=, issueDate=1544903057122, maxDate=1545507857122, > sequenceNumber=10314, masterKeyId=344) can't be found in cache at > org.apache.hadoop.ipc.Client.call(Client.java:1470) at > org.apache.hadoop.ipc.Client.call(Client.java:1401) at > org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:232) > at com.sun.proxy.$Proxy9.getFileInfo(Unknown Source) at > org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolTranslatorPB.getFileInfo(ClientNamenodeProtocolTranslatorPB.java:752) > at sun.reflect.GeneratedMethodAccessor5.invoke(Unknown Source) at > sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) > at java.lang.reflect.Method.invoke(Method.java:498) at > org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:187) > at > org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:102) > at com.sun.proxy.$Proxy10.getFileInfo(Unknown Source) at > org.apache.hadoop.hdfs.DFSClient.getFileInfo(DFSClient.java:1977) at > org.apache.hadoop.fs.Hdfs.getFileStatus(Hdfs.java:133) at > org.apache.hadoop.fs.FileContext$14.next(FileContext.java:1120) at > org.apache.hadoop.fs.FileContext$14.next(FileContext.java:1116) at > org.apache.hadoop.fs.FSLinkResolver.resolve(FSLinkResolver.java:90) at > org.apache.hadoop.fs.FileContext.getFileStatus(FileContext.java:1116) at > org.apache.hadoop.fs.FileContext$Util.exists(FileContext.java:1581) at > org.apache.spark.sql.execution.streaming.FileContextBasedCheckpointFileManager.exists(CheckpointFileManager.scala:326) > at > org.apache.spark.sql.execution.streaming.HDFSMetadataLog.get(HDFSMetadataLog.scala:142) > at > org.apache.spark.sql.execution.streaming.HDFSMetadataLog.add(HDFSMetadataLog.scala:110) > at > org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$org$apache$spark$sql$execution$streaming$MicroBatchExecution$$runBatch$1.apply$mcV$sp(MicroBatchExecution.scala:544) > at > org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$org$apache$spark$sql$execution$streaming$MicroBatchExecution$$runBatch$1.apply(MicroBatchExecution.scala:542) > at > org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$org$apache$spark$sql$execution$streaming$MicroBatchExecution$$runBatch$1.apply(MicroBatchExecution.scala:542) > at > org.apache.spark.sql.execution.streaming.MicroBatchExecution.withProgressLocked(MicroBatchExecution.scala:554) > at > org.apache.spark.sql.execution.streaming.MicroBatchExecution.org$apache$spark$sql$execution$streaming$MicroBatchExecution$$runBatch(MicroBatchExecution.scala:542) > at > org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$runActivatedStream$1$$anonfun$apply$mcZ$sp$1.apply$mcV$sp(MicroBatchExecution.scala:198) > at > org.apache.spark.sql.execution.streaming.MicroBatchExecution$$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$$runStream(StreamExecution.scala:279) > at > org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.run(StreamExecution.scala:189){code} > > ^It is important to notice that I tried usual fix for this kind of problems:^ > > {code:java} > --conf "spark.hadoop.fs.hdfs.impl.disable.cache=true" > > {code} -- This message was sent by Atlassian Jira (v8.3.4#803005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org