Then it looks like something wrong with the python process. Do you run it in yarn-cluster mode or yarn-client mode ? Try to add the following line to log4j.properties for yarn-client mode or log4j_yarn_cluster.properties for yarn-cluster mode
log4j.logger.org.apache.zeppelin.interpreter=DEBUG And try it again, this time you will get more log info, I suspect the python process fail to start Manuel Sopena Ballesteros <manuel...@garvan.org.au> 于2019年10月4日周五 上午9:09写道： > Sorry for the late response, > > > > Yes, I have successfully ran few simple scala codes using %spark > interpreter in zeppelin. > > > > What should I do next? > > > > Manuel > > > > *From:* Jeff Zhang [mailto:zjf...@gmail.com] > *Sent:* Tuesday, October 1, 2019 5:44 PM > *To:* users > *Subject:* Re: thrift.transport.TTransportException > > > > It looks like you are using pyspark, could you try just start scala spark > interpreter via `%spark` ? First let's figure out whether it is related > with pyspark. > > > > > > > > Manuel Sopena Ballesteros <manuel...@garvan.org.au> 于2019年10月1日周二 下午3:29 > 写道： > > Dear Zeppelin community, > > > > I would like to ask for advice in regards an error I am having with thrift. > > > > I am getting quite a lot of these errors while running my notebooks > > > > org.apache.thrift.transport.TTransportException at > org.apache.thrift.transport.TIOStreamTransport.read(TIOStreamTransport.java:132) > at org.apache.thrift.transport.TTransport.readAll(TTransport.java:86) at > org.apache.thrift.protocol.TBinaryProtocol.readAll(TBinaryProtocol.java:429) > at > org.apache.thrift.protocol.TBinaryProtocol.readI32(TBinaryProtocol.java:318) > at > org.apache.thrift.protocol.TBinaryProtocol.readMessageBegin(TBinaryProtocol.java:219) > at org.apache.thrift.TServiceClient.receiveBase(TServiceClient.java:77) at > org.apache.zeppelin.interpreter.thrift.RemoteInterpreterService$Client.recv_interpret(RemoteInterpreterService.java:274) > at > org.apache.zeppelin.interpreter.thrift.RemoteInterpreterService$Client.interpret(RemoteInterpreterService.java:258) > at > org.apache.zeppelin.interpreter.remote.RemoteInterpreter$4.call(RemoteInterpreter.java:233) > at > org.apache.zeppelin.interpreter.remote.RemoteInterpreter$4.call(RemoteInterpreter.java:229) > at > org.apache.zeppelin.interpreter.remote.RemoteInterpreterProcess.callRemoteFunction(RemoteInterpreterProcess.java:135) > at > org.apache.zeppelin.interpreter.remote.RemoteInterpreter.interpret(RemoteInterpreter.java:228) > at org.apache.zeppelin.notebook.Paragraph.jobRun(Paragraph.java:437) at > org.apache.zeppelin.scheduler.Job.run(Job.java:188) at > org.apache.zeppelin.scheduler.RemoteScheduler$JobRunner.run(RemoteScheduler.java:307) > at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511) > at java.util.concurrent.FutureTask.run(FutureTask.java:266) at > java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$201(ScheduledThreadPoolExecutor.java:180) > at > java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:293) > at > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) > at > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) > at java.lang.Thread.run(Thread.java:745) > > > > And this is the Spark driver application logs: > > … > > > =============================================================================== > > YARN executor launch context: > > env: > > CLASSPATH -> > {{PWD}}<CPS>{{PWD}}/__spark_conf__<CPS>{{PWD}}/__spark_libs__/*<CPS>$HADOOP_CONF_DIR<CPS>/usr/hdp/3.1.0.0-78/hadoop/*<CPS>/usr/hdp/3.1.0.0-78/hadoop/lib/*<CPS>/usr/hdp/current/hadoop-hdfs-client/*<CPS>/usr/hdp/current/hadoop-hdfs-client/lib/*<CPS>/usr/hdp/current/hadoop-yarn-client/*<CPS>/usr/hdp/current/hadoop-yarn-client/lib/*<CPS>$PWD/mr-framework/hadoop/share/hadoop/mapreduce/*:$PWD/mr-framework/hadoop/share/hadoop/mapreduce/lib/*:$PWD/mr-framework/hadoop/share/hadoop/common/*:$PWD/mr-framework/hadoop/share/hadoop/common/lib/*:$PWD/mr-framework/hadoop/share/hadoop/yarn/*:$PWD/mr-framework/hadoop/share/hadoop/yarn/lib/*:$PWD/mr-framework/hadoop/share/hadoop/hdfs/*:$PWD/mr-framework/hadoop/share/hadoop/hdfs/lib/*:$PWD/mr-framework/hadoop/share/hadoop/tools/lib/*:/usr/hdp/3.1.0.0-78/hadoop/lib/hadoop-lzo-0.6.0.3.1.0.0-78.jar:/etc/hadoop/conf/secure<CPS>{{PWD}}/__spark_conf__/__hadoop_conf__ > > SPARK_YARN_STAGING_DIR -> > hdfs://gl-hdp-ctrl01-mlx.mlx:8020/user/mansop/.sparkStaging/application_1568954689585_0052 > > SPARK_USER -> mansop > > PYTHONPATH -> > /usr/hdp/current/spark2-client/python/lib/py4j-0.10.7-src.zip:/usr/hdp/current/spark2-client/python/:<CPS>{{PWD}}/pyspark.zip<CPS>{{PWD}}/py4j-0.10.7-src.zip > > > > command: > > > LD_LIBRARY_PATH="/usr/hdp/current/hadoop-client/lib/native:/usr/hdp/current/hadoop-client/lib/native/Linux-amd64-64:$LD_LIBRARY_PATH" > \ > > {{JAVA_HOME}}/bin/java \ > > -server \ > > -Xmx1024m \ > > '-XX:+UseNUMA' \ > > -Djava.io.tmpdir={{PWD}}/tmp \ > > '-Dspark.history.ui.port=18081' \ > > -Dspark.yarn.app.container.log.dir=<LOG_DIR> \ > > -XX:OnOutOfMemoryError='kill %p' \ > > org.apache.spark.executor.CoarseGrainedExecutorBackend \ > > --driver-url \ > > spark://coarsegrainedschedu...@r640-1-12-mlx.mlx:35602 \ > > --executor-id \ > > <executorId> \ > > --hostname \ > > <hostname> \ > > --cores \ > > 1 \ > > --app-id \ > > application_1568954689585_0052 \ > > --user-class-path \ > > file:$PWD/__app__.jar \ > > 1><LOG_DIR>/stdout \ > > 2><LOG_DIR>/stderr > > > > resources: > > __app__.jar -> resource { scheme: "hdfs" host: "gl-hdp-ctrl01-mlx.mlx" > port: 8020 file: > "/user/mansop/.sparkStaging/application_1568954689585_0052/spark-interpreter-0.8.0.3.1.0.0-78.jar" > } size: 20433040 timestamp: 1569804142906 type: FILE visibility: PRIVATE > > __spark_conf__ -> resource { scheme: "hdfs" host: > "gl-hdp-ctrl01-mlx.mlx" port: 8020 file: > "/user/mansop/.sparkStaging/application_1568954689585_0052/__spark_conf__.zip" > } size: 277725 timestamp: 1569804143239 type: ARCHIVE visibility: PRIVATE > > sparkr -> resource { scheme: "hdfs" host: "gl-hdp-ctrl01-mlx.mlx" > port: 8020 file: > "/user/mansop/.sparkStaging/application_1568954689585_0052/sparkr.zip" } > size: 688255 timestamp: 1569804142991 type: ARCHIVE visibility: PRIVATE > > log4j_yarn_cluster.properties -> resource { scheme: "hdfs" host: > "gl-hdp-ctrl01-mlx.mlx" port: 8020 file: > "/user/mansop/.sparkStaging/application_1568954689585_0052/log4j_yarn_cluster.properties" > } size: 1018 timestamp: 1569804142955 type: FILE visibility: PRIVATE > > pyspark.zip -> resource { scheme: "hdfs" host: "gl-hdp-ctrl01-mlx.mlx" > port: 8020 file: > "/user/mansop/.sparkStaging/application_1568954689585_0052/pyspark.zip" } > size: 550570 timestamp: 1569804143018 type: FILE visibility: PRIVATE > > __spark_libs__ -> resource { scheme: "hdfs" host: > "gl-hdp-ctrl01-mlx.mlx" port: 8020 file: > "/hdp/apps/3.1.0.0-78/spark2/spark2-hdp-yarn-archive.tar.gz" } size: > 280293050 timestamp: 1568938921259 type: ARCHIVE visibility: PUBLIC > > py4j-0.10.7-src.zip -> resource { scheme: "hdfs" host: > "gl-hdp-ctrl01-mlx.mlx" port: 8020 file: > "/user/mansop/.sparkStaging/application_1568954689585_0052/py4j-0.10.7-src.zip" > } size: 42437 timestamp: 1569804143043 type: FILE visibility: PRIVATE > > __hive_libs__ -> resource { scheme: "hdfs" host: > "gl-hdp-ctrl01-mlx.mlx" port: 8020 file: > "/hdp/apps/3.1.0.0-78/spark2/spark2-hdp-hive-archive.tar.gz" } size: > 43807162 timestamp: 1568938925069 type: ARCHIVE visibility: PUBLIC > > > > > =============================================================================== > > INFO [2019-09-30 10:42:37,303] ({main} RMProxy.java[newProxyInstance]:133) > - Connecting to ResourceManager at gl-hdp-ctrl03-mlx.mlx/10.0.1.248:8030 > > INFO [2019-09-30 10:42:37,324] ({main} Logging.scala[logInfo]:54) - > Registering the ApplicationMaster > > INFO [2019-09-30 10:42:37,454] ({main} > Configuration.java[getConfResourceAsInputStream]:2756) - found resource > resource-types.xml at file:/etc/hadoop/3.1.0.0-78/0/resource-types.xml > > INFO [2019-09-30 10:42:37,470] ({main} Logging.scala[logInfo]:54) - Will > request 2 executor container(s), each with 1 core(s) and 1408 MB memory > (including 384 MB of overhead) > > INFO [2019-09-30 10:42:37,474] ({dispatcher-event-loop-14} > Logging.scala[logInfo]:54) - ApplicationMaster registered as > NettyRpcEndpointRef(spark://yar...@r640-1-12-mlx.mlx:35602) > > INFO [2019-09-30 10:42:37,485] ({main} Logging.scala[logInfo]:54) - > Submitted 2 unlocalized container requests. > > INFO [2019-09-30 10:42:37,518] ({main} Logging.scala[logInfo]:54) - > Started progress reporter thread with (heartbeat : 3000, initial allocation > : 200) intervals > > INFO [2019-09-30 10:42:37,619] ({Reporter} Logging.scala[logInfo]:54) - > Launching container container_e01_1568954689585_0052_01_000002 on host > r640-1-12-mlx.mlx for executor with ID 1 > > INFO [2019-09-30 10:42:37,621] ({Reporter} Logging.scala[logInfo]:54) - > Launching container container_e01_1568954689585_0052_01_000003 on host > r640-1-13-mlx.mlx for executor with ID 2 > > INFO [2019-09-30 10:42:37,623] ({Reporter} Logging.scala[logInfo]:54) - > Received 2 containers from YARN, launching executors on 2 of them. > > INFO [2019-09-30 10:42:39,481] ({dispatcher-event-loop-51} > Logging.scala[logInfo]:54) - Registered executor > NettyRpcEndpointRef(spark-client://Executor) (10.0.1.12:54340) with ID 1 > > INFO [2019-09-30 10:42:39,553] ({dispatcher-event-loop-62} > Logging.scala[logInfo]:54) - Registering block manager > r640-1-12-mlx.mlx:33043 with 408.9 MB RAM, BlockManagerId(1, > r640-1-12-mlx.mlx, 33043, None) > > INFO [2019-09-30 10:42:40,003] ({dispatcher-event-loop-9} > Logging.scala[logInfo]:54) - Registered executor > NettyRpcEndpointRef(spark-client://Executor) (10.0.1.13:33812) with ID 2 > > INFO [2019-09-30 10:42:40,023] ({pool-6-thread-2} > Logging.scala[logInfo]:54) - SchedulerBackend is ready for scheduling > beginning after reached minRegisteredResourcesRatio: 0.8 > > INFO [2019-09-30 10:42:40,025] ({pool-6-thread-2} > Logging.scala[logInfo]:54) - YarnClusterScheduler.postStartHook done > > INFO [2019-09-30 10:42:40,072] ({dispatcher-event-loop-11} > Logging.scala[logInfo]:54) - Registering block manager > r640-1-13-mlx.mlx:34105 with 408.9 MB RAM, BlockManagerId(2, > r640-1-13-mlx.mlx, 34105, None) > > INFO [2019-09-30 10:42:41,779] ({pool-6-thread-2} > SparkShims.java[loadShims]:54) - Initializing shims for Spark 2.x > > INFO [2019-09-30 10:42:41,840] ({pool-6-thread-2} > Py4JUtils.java[createGatewayServer]:44) - Launching GatewayServer at > 127.0.0.1:36897 > > INFO [2019-09-30 10:42:41,852] ({pool-6-thread-2} > PySparkInterpreter.java[createGatewayServerAndStartScript]:265) - > pythonExec: /home/mansop/anaconda2/bin/python > > INFO [2019-09-30 10:42:41,862] ({pool-6-thread-2} > PySparkInterpreter.java[setupPySparkEnv]:236) - PYTHONPATH: > /usr/hdp/current/spark2-client/python/lib/py4j-0.10.7-src.zip:/usr/hdp/current/spark2-client/python/::/d1/hadoop/yarn/local/usercache/mansop/appcache/application_1568954689585_0052/container_e01_1568954689585_0052_01_000001/pyspark.zip:/d1/hadoop/yarn/local/usercache/mansop/appcache/application_1568954689585_0052/container_e01_1568954689585_0052_01_000001/py4j-0.10.7-src.zip > > ERROR [2019-09-30 10:43:09,061] ({SIGTERM handler} > SignalUtils.scala[apply$mcZ$sp]:43) - RECEIVED SIGNAL TERM > > INFO [2019-09-30 10:43:09,068] ({shutdown-hook-0} > Logging.scala[logInfo]:54) - Invoking stop() from shutdown hook > > INFO [2019-09-30 10:43:09,082] ({shutdown-hook-0} > AbstractConnector.java[doStop]:318) - Stopped Spark@505439b3 > {HTTP/1.1,[http/1.1]}{0.0.0.0:0} > > INFO [2019-09-30 10:43:09,085] ({shutdown-hook-0} > Logging.scala[logInfo]:54) - Stopped Spark web UI at > http://r640-1-12-mlx.mlx:42446 > > INFO [2019-09-30 10:43:09,140] ({dispatcher-event-loop-52} > Logging.scala[logInfo]:54) - Driver requested a total number of 0 > executor(s). > > INFO [2019-09-30 10:43:09,142] ({shutdown-hook-0} > Logging.scala[logInfo]:54) - Shutting down all executors > > INFO [2019-09-30 10:43:09,144] ({dispatcher-event-loop-51} > Logging.scala[logInfo]:54) - Asking each executor to shut down > > INFO [2019-09-30 10:43:09,151] ({shutdown-hook-0} > Logging.scala[logInfo]:54) - Stopping SchedulerExtensionServices > > (serviceOption=None, > > services=List(), > > started=false) > > ERROR [2019-09-30 10:43:09,155] ({Reporter} Logging.scala[logError]:91) - > Exception from Reporter thread. > > org.apache.hadoop.yarn.exceptions.ApplicationAttemptNotFoundException: > Application attempt appattempt_1568954689585_0052_000001 doesn't exist in > ApplicationMasterService cache. > > at > org.apache.hadoop.yarn.server.resourcemanager.ApplicationMasterService.allocate(ApplicationMasterService.java:404) > > at > org.apache.hadoop.yarn.api.impl.pb.service.ApplicationMasterProtocolPBServiceImpl.allocate(ApplicationMasterProtocolPBServiceImpl.java:60) > > at > org.apache.hadoop.yarn.proto.ApplicationMasterProtocol$ApplicationMasterProtocolService$2.callBlockingMethod(ApplicationMasterProtocol.java:99) > > at > org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:524) > > at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:1025) > > at org.apache.hadoop.ipc.Server$RpcCall.run(Server.java:876) > > at org.apache.hadoop.ipc.Server$RpcCall.run(Server.java:822) > > at java.security.AccessController.doPrivileged(Native > Method) > > at javax.security.auth.Subject.doAs(Subject.java:422) > > at > org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1730) > > at > org.apache.hadoop.ipc.Server$Handler.run(Server.java:2682) > > > > at > sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method) > > at > sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62) > > at > sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45) > > at > java.lang.reflect.Constructor.newInstance(Constructor.java:423) > > at > org.apache.hadoop.yarn.ipc.RPCUtil.instantiateException(RPCUtil.java:53) > > at > org.apache.hadoop.yarn.ipc.RPCUtil.instantiateYarnException(RPCUtil.java:75) > > at > org.apache.hadoop.yarn.ipc.RPCUtil.unwrapAndThrowException(RPCUtil.java:116) > > at > org.apache.hadoop.yarn.api.impl.pb.client.ApplicationMasterProtocolPBClientImpl.allocate(ApplicationMasterProtocolPBClientImpl.java:79) > > at sun.reflect.NativeMethodAccessorImpl.invoke0(Native > Method) > > at > sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) > > at > sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) > > at java.lang.reflect.Method.invoke(Method.java:498) > > at > org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:422) > > at > org.apache.hadoop.io.retry.RetryInvocationHandler$Call.invokeMethod(RetryInvocationHandler.java:165) > > at > org.apache.hadoop.io.retry.RetryInvocationHandler$Call.invoke(RetryInvocationHandler.java:157) > > at > org.apache.hadoop.io.retry.RetryInvocationHandler$Call.invokeOnce(RetryInvocationHandler.java:95) > > at > org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:359) > > at com.sun.proxy.$Proxy21.allocate(Unknown Source) > > at > org.apache.hadoop.yarn.client.api.impl.AMRMClientImpl.allocate(AMRMClientImpl.java:320) > > at > org.apache.spark.deploy.yarn.YarnAllocator.allocateResources(YarnAllocator.scala:268) > > at > org.apache.spark.deploy.yarn.ApplicationMaster$$anon$3.run(ApplicationMaster.scala:556) > > Caused by: > org.apache.hadoop.ipc.RemoteException(org.apache.hadoop.yarn.exceptions.ApplicationAttemptNotFoundException): > Application attempt appattempt_1568954689585_0052_000001 doesn't exist in > ApplicationMasterService cache. > > at > org.apache.hadoop.yarn.server.resourcemanager.ApplicationMasterService.allocate(ApplicationMasterService.java:404) > > at > org.apache.hadoop.yarn.api.impl.pb.service.ApplicationMasterProtocolPBServiceImpl.allocate(ApplicationMasterProtocolPBServiceImpl.java:60) > > at > org.apache.hadoop.yarn.proto.ApplicationMasterProtocol$ApplicationMasterProtocolService$2.callBlockingMethod(ApplicationMasterProtocol.java:99) > > at > org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:524) > > at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:1025) > > at org.apache.hadoop.ipc.Server$RpcCall.run(Server.java:876) > > at org.apache.hadoop.ipc.Server$RpcCall.run(Server.java:822) > > at java.security.AccessController.doPrivileged(Native > Method) > > at javax.security.auth.Subject.doAs(Subject.java:422) > > at > org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1730) > > at > org.apache.hadoop.ipc.Server$Handler.run(Server.java:2682) > > > > at > org.apache.hadoop.ipc.Client.getRpcResponse(Client.java:1497) > > at org.apache.hadoop.ipc.Client.call(Client.java:1443) > > at org.apache.hadoop.ipc.Client.call(Client.java:1353) > > at > org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:228) > > at > org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:116) > > at com.sun.proxy.$Proxy20.allocate(Unknown Source) > > at > org.apache.hadoop.yarn.api.impl.pb.client.ApplicationMasterProtocolPBClientImpl.allocate(ApplicationMasterProtocolPBClientImpl.java:77) > > ... 13 more > > INFO [2019-09-30 10:43:09,164] ({Reporter} Logging.scala[logInfo]:54) - > Final app status: FAILED, exitCode: 12, (reason: Application attempt > appattempt_1568954689585_0052_000001 doesn't exist in > ApplicationMasterService cache. > > at > org.apache.hadoop.yarn.server.resourcemanager.ApplicationMasterService.allocate(ApplicationMasterService.java:404) > > at > org.apache.hadoop.yarn.api.impl.pb.service.ApplicationMasterProtocolPBServiceImpl.allocate(ApplicationMasterProtocolPBServiceImpl.java:60) > > at > org.apache.hadoop.yarn.proto.ApplicationMasterProtocol$ApplicationMasterProtocolService$2.callBlockingMethod(ApplicationMasterProtocol.java:99) > > at > org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:524) > > at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:1025) > > at org.apache.hadoop.ipc.Server$RpcCall.run(Server.java:876) > > at org.apache.hadoop.ipc.Server$RpcCall.run(Server.java:822) > > at java.security.AccessController.doPrivileged(Native > Method) > > at javax.security.auth.Subject.doAs(Subject.java:422) > > at > org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1730) > > at > org.apache.hadoop.ipc.Server$Handler.run(Server.java:2682) > > ) > > INFO [2019-09-30 10:43:09,166] ({dispatcher-event-loop-54} > Logging.scala[logInfo]:54) - MapOutputTrackerMasterEndpoint stopped! > > INFO [2019-09-30 10:43:09,236] ({shutdown-hook-0} > Logging.scala[logInfo]:54) - MemoryStore cleared > > INFO [2019-09-30 10:43:09,237] ({shutdown-hook-0} > Logging.scala[logInfo]:54) - BlockManager stopped > > INFO [2019-09-30 10:43:09,237] ({shutdown-hook-0} > Logging.scala[logInfo]:54) - BlockManagerMaster stopped > > INFO [2019-09-30 10:43:09,241] ({dispatcher-event-loop-73} > Logging.scala[logInfo]:54) - OutputCommitCoordinator stopped! > > INFO [2019-09-30 10:43:09,252] ({shutdown-hook-0} > Logging.scala[logInfo]:54) - Successfully stopped SparkContext > > INFO [2019-09-30 10:43:09,253] ({shutdown-hook-0} > Logging.scala[logInfo]:54) - Shutdown hook called > > INFO [2019-09-30 10:43:09,254] ({shutdown-hook-0} > Logging.scala[logInfo]:54) - Deleting directory > /d1/hadoop/yarn/local/usercache/mansop/appcache/application_1568954689585_0052/spark-ba80cda3-812a-4cf0-b1f6-6e9eb52952b2 > > INFO [2019-09-30 10:43:09,254] ({shutdown-hook-0} > Logging.scala[logInfo]:54) - Deleting directory > /d0/hadoop/yarn/local/usercache/mansop/appcache/application_1568954689585_0052/spark-43078781-8f1c-4cd6-a8da-e81b32892cf8 > > INFO [2019-09-30 10:43:09,255] ({shutdown-hook-0} > Logging.scala[logInfo]:54) - Deleting directory > /d0/hadoop/yarn/local/usercache/mansop/appcache/application_1568954689585_0052/spark-43078781-8f1c-4cd6-a8da-e81b32892cf8/pyspark-9138f7ad-3f15-42c6-9bf3-e3e72d5d4086 > > > > How can I continue troubleshooting in order to find out what this error > means? > > > > Thank you very much > > > > NOTICE > > Please consider the environment before printing this email. This message > and any attachments are intended for the addressee named and may contain > legally privileged/confidential/copyright information. If you are not the > intended recipient, you should not read, use, disclose, copy or distribute > this communication. If you have received this message in error please > notify us at once by return email and then delete both messages. We accept > no liability for the distribution of viruses or similar in electronic > communications. This notice should not be removed. > > > > > -- > > Best Regards > > Jeff Zhang > NOTICE > Please consider the environment before printing this email. This message > and any attachments are intended for the addressee named and may contain > legally privileged/confidential/copyright information. If you are not the > intended recipient, you should not read, use, disclose, copy or distribute > this communication. If you have received this message in error please > notify us at once by return email and then delete both messages. We accept > no liability for the distribution of viruses or similar in electronic > communications. This notice should not be removed. > -- Best Regards Jeff Zhang
