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我使用以下代码通过 pyspark Insertinto 函数将数据帧写入配置单元分区表。
spark.conf.set("spark.sql.sources.partitionOverwriteMode", "DYNAMIC")
df.write.mode("overwrite").insertInto(table, overwrite=True)
当集群正在运行一些其他繁重的作业时。它有 1/3 的错误概率。
我认为这可能发生在任务似乎失败但实际上并没有失败并且 yarn 启动另一个任务来运行该作业时。因此两个任务发生冲突。
Traceback (most recent call last):
File "dataframe.py", line 39, in save
df.write.mode("overwrite").insertInto(table, overwrite=True)
File "/opt/cloudera/parcels/SPARK2-2.4.0.cloudera2-1.cdh5.13.3.p0.1041012/lib/spark2/python/lib/pyspark.zip/pyspark/sql/readwriter.py", line 745, in insertInto
File "/opt/cloudera/parcels/SPARK2-2.4.0.cloudera2-1.cdh5.13.3.p0.1041012/lib/spark2/python/lib/py4j-0.10.7-src.zip/py4j/java_gateway.py", line 1257, in __call__
File "/opt/cloudera/parcels/SPARK2-2.4.0.cloudera2-1.cdh5.13.3.p0.1041012/lib/spark2/python/lib/pyspark.zip/pyspark/sql/utils.py", line 63, in deco
File "/opt/cloudera/parcels/SPARK2-2.4.0.cloudera2-1.cdh5.13.3.p0.1041012/lib/spark2/python/lib/py4j-0.10.7-src.zip/py4j/protocol.py", line 328, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o2575.insertInto.
: org.apache.spark.SparkException: Job aborted.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:198)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:159)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:104)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:102)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.doExecute(commands.scala:122)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:80)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:80)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:676)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:676)
at org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:78)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:73)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:676)
at org.apache.spark.sql.DataFrameWriter.insertInto(DataFrameWriter.scala:334)
at org.apache.spark.sql.DataFrameWriter.insertInto(DataFrameWriter.scala:320)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.lang.Thread.run(Thread.java:748)
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 53 in stage 535.0 failed 4 times, most recent failure: Lost task 53.4 in stage 535.0 (TID 137333, hadoop138, executor 3401): org.apache.spark.SparkException: Task failed while writing rows.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:257)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:170)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:169)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:121)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1405)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: org.apache.hadoop.fs.FileAlreadyExistsException: /user/hive/warehouse/test.db/test/.spark-staging-77bf12fc-6606-4b84-8c89-81ec7431c729/dt=20200214/part-00053-77bf12fc-6606-4b84-8c89-81ec7431c729.c000.snappy.parquet for client 192.168.1.1 already exists
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.startFileInternal(FSNamesystem.java:2935)
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.startFileInt(FSNamesystem.java:2824)
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.startFile(FSNamesystem.java:2709)
at org.apache.hadoop.hdfs.server.namenode.NameNodeRpcServer.create(NameNodeRpcServer.java:602)
at org.apache.hadoop.hdfs.server.namenode.AuthorizationProviderProxyClientProtocol.create(AuthorizationProviderProxyClientProtocol.java:115)
at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolServerSideTranslatorPB.create(ClientNamenodeProtocolServerSideTranslatorPB.java:412)
at org.apache.hadoop.hdfs.protocol.proto.ClientNamenodeProtocolProtos$ClientNamenodeProtocol$2.callBlockingMethod(ClientNamenodeProtocolProtos.java)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:617)
at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:1073)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2226)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2222)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1917)
at org.apache.hadoop.ipc.Server$Handler.run(Server.java:2220)
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.ipc.RemoteException.instantiateException(RemoteException.java:106)
at org.apache.hadoop.ipc.RemoteException.unwrapRemoteException(RemoteException.java:73)
at org.apache.hadoop.hdfs.DFSOutputStream.newStreamForCreate(DFSOutputStream.java:2105)
at org.apache.hadoop.hdfs.DFSClient.create(DFSClient.java:1767)
at org.apache.hadoop.hdfs.DFSClient.create(DFSClient.java:1691)
at org.apache.hadoop.hdfs.DistributedFileSystem$7.doCall(DistributedFileSystem.java:437)
at org.apache.hadoop.hdfs.DistributedFileSystem$7.doCall(DistributedFileSystem.java:433)
at org.apache.hadoop.fs.FileSystemLinkResolver.resolve(FileSystemLinkResolver.java:81)
at org.apache.hadoop.hdfs.DistributedFileSystem.create(DistributedFileSystem.java:433)
at org.apache.hadoop.hdfs.DistributedFileSystem.create(DistributedFileSystem.java:374)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:926)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:907)
at parquet.hadoop.ParquetFileWriter.<init>(ParquetFileWriter.java:220)
at parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:311)
at parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:282)
at org.apache.spark.sql.execution.datasources.parquet.ParquetOutputWriter.<init>(ParquetOutputWriter.scala:37)
at org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat$$anon$1.newInstance(ParquetFileFormat.scala:150)
at org.apache.spark.sql.execution.datasources.DynamicPartitionDataWriter.newOutputWriter(FileFormatDataWriter.scala:236)
at org.apache.spark.sql.execution.datasources.DynamicPartitionDataWriter.write(FileFormatDataWriter.scala:260)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:245)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:242)
at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1439)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:248)
... 10 more
Caused by: org.apache.hadoop.ipc.RemoteException(org.apache.hadoop.fs.FileAlreadyExistsException): /user/hive/warehouse/test.db/test/.spark-staging-77bf12fc-6606-4b84-8c89-81ec7431c729/dt=20200214/part-00053-77bf12fc-6606-4b84-8c89-81ec7431c729.c000.snappy.parquet for client 192.168.1.1 already exists
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.startFileInternal(FSNamesystem.java:2935)
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.startFileInt(FSNamesystem.java:2824)
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.startFile(FSNamesystem.java:2709)
at org.apache.hadoop.hdfs.server.namenode.NameNodeRpcServer.create(NameNodeRpcServer.java:602)
at org.apache.hadoop.hdfs.server.namenode.AuthorizationProviderProxyClientProtocol.create(AuthorizationProviderProxyClientProtocol.java:115)
at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolServerSideTranslatorPB.create(ClientNamenodeProtocolServerSideTranslatorPB.java:412)
at org.apache.hadoop.hdfs.protocol.proto.ClientNamenodeProtocolProtos$ClientNamenodeProtocol$2.callBlockingMethod(ClientNamenodeProtocolProtos.java)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:617)
at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:1073)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2226)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2222)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1917)
at org.apache.hadoop.ipc.Server$Handler.run(Server.java:2220)
at org.apache.hadoop.ipc.Client.call(Client.java:1504)
at org.apache.hadoop.ipc.Client.call(Client.java:1441)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:230)
at com.sun.proxy.$Proxy17.create(Unknown Source)
at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolTranslatorPB.create(ClientNamenodeProtocolTranslatorPB.java:311)
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:260)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:104)
at com.sun.proxy.$Proxy18.create(Unknown Source)
at org.apache.hadoop.hdfs.DFSOutputStream.newStreamForCreate(DFSOutputStream.java:2100)
... 30 more
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1889)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1877)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1876)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1876)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:926)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2110)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2059)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2048)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:737)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2061)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:167)
... 31 more
Caused by: org.apache.spark.SparkException: Task failed while writing rows.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:257)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:170)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:169)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:121)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1405)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
... 1 more
Caused by: org.apache.hadoop.fs.FileAlreadyExistsException: /user/hive/warehouse/test.db/test/.spark-staging-77bf12fc-6606-4b84-8c89-81ec7431c729/dt=20200214/part-00053-77bf12fc-6606-4b84-8c89-81ec7431c729.c000.snappy.parquet for client 192.168.1.1 already exists
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.startFileInternal(FSNamesystem.java:2935)
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.startFileInt(FSNamesystem.java:2824)
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.startFile(FSNamesystem.java:2709)
at org.apache.hadoop.hdfs.server.namenode.NameNodeRpcServer.create(NameNodeRpcServer.java:602)
at org.apache.hadoop.hdfs.server.namenode.AuthorizationProviderProxyClientProtocol.create(AuthorizationProviderProxyClientProtocol.java:115)
at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolServerSideTranslatorPB.create(ClientNamenodeProtocolServerSideTranslatorPB.java:412)
at org.apache.hadoop.hdfs.protocol.proto.ClientNamenodeProtocolProtos$ClientNamenodeProtocol$2.callBlockingMethod(ClientNamenodeProtocolProtos.java)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:617)
at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:1073)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2226)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2222)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1917)
at org.apache.hadoop.ipc.Server$Handler.run(Server.java:2220)
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.ipc.RemoteException.instantiateException(RemoteException.java:106)
at org.apache.hadoop.ipc.RemoteException.unwrapRemoteException(RemoteException.java:73)
at org.apache.hadoop.hdfs.DFSOutputStream.newStreamForCreate(DFSOutputStream.java:2105)
at org.apache.hadoop.hdfs.DFSClient.create(DFSClient.java:1767)
at org.apache.hadoop.hdfs.DFSClient.create(DFSClient.java:1691)
at org.apache.hadoop.hdfs.DistributedFileSystem$7.doCall(DistributedFileSystem.java:437)
at org.apache.hadoop.hdfs.DistributedFileSystem$7.doCall(DistributedFileSystem.java:433)
at org.apache.hadoop.fs.FileSystemLinkResolver.resolve(FileSystemLinkResolver.java:81)
at org.apache.hadoop.hdfs.DistributedFileSystem.create(DistributedFileSystem.java:433)
at org.apache.hadoop.hdfs.DistributedFileSystem.create(DistributedFileSystem.java:374)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:926)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:907)
at parquet.hadoop.ParquetFileWriter.<init>(ParquetFileWriter.java:220)
at parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:311)
at parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:282)
at org.apache.spark.sql.execution.datasources.parquet.ParquetOutputWriter.<init>(ParquetOutputWriter.scala:37)
at org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat$$anon$1.newInstance(ParquetFileFormat.scala:150)
at org.apache.spark.sql.execution.datasources.DynamicPartitionDataWriter.newOutputWriter(FileFormatDataWriter.scala:236)
at org.apache.spark.sql.execution.datasources.DynamicPartitionDataWriter.write(FileFormatDataWriter.scala:260)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:245)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:242)
at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1439)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:248)
... 10 more
Caused by: org.apache.hadoop.ipc.RemoteException(org.apache.hadoop.fs.FileAlreadyExistsException): /user/hive/warehouse/test.db/test/.spark-staging-77bf12fc-6606-4b84-8c89-81ec7431c729/dt=20200214/part-00053-77bf12fc-6606-4b84-8c89-81ec7431c729.c000.snappy.parquet for client 192.168.1.1 already exists
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.startFileInternal(FSNamesystem.java:2935)
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.startFileInt(FSNamesystem.java:2824)
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.startFile(FSNamesystem.java:2709)
at org.apache.hadoop.hdfs.server.namenode.NameNodeRpcServer.create(NameNodeRpcServer.java:602)
at org.apache.hadoop.hdfs.server.namenode.AuthorizationProviderProxyClientProtocol.create(AuthorizationProviderProxyClientProtocol.java:115)
at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolServerSideTranslatorPB.create(ClientNamenodeProtocolServerSideTranslatorPB.java:412)
at org.apache.hadoop.hdfs.protocol.proto.ClientNamenodeProtocolProtos$ClientNamenodeProtocol$2.callBlockingMethod(ClientNamenodeProtocolProtos.java)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:617)
at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:1073)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2226)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2222)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1917)
at org.apache.hadoop.ipc.Server$Handler.run(Server.java:2220)
at org.apache.hadoop.ipc.Client.call(Client.java:1504)
at org.apache.hadoop.ipc.Client.call(Client.java:1441)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:230)
at com.sun.proxy.$Proxy17.create(Unknown Source)
at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolTranslatorPB.create(ClientNamenodeProtocolTranslatorPB.java:311)
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:260)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:104)
at com.sun.proxy.$Proxy18.create(Unknown Source)
at org.apache.hadoop.hdfs.DFSOutputStream.newStreamForCreate(DFSOutputStream.java:2100)
... 30 more
最佳答案
此问题已在 Spark 3.1.0 中修复。
引用:
关于apache-spark - 使用 Spark insertInto 时出现 FileAlreadyExistsException,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/63948379/
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我将用户输入的时间和日期作为: DatePicker dp = (DatePicker) findViewById(R.id.datePicker); TimePicker tp = (TimePic
放宽“邻居”的标准是否足够,或者是否有其他标准行动可以采取? 最佳答案 如果所有相邻解决方案都是 Tabu,则听起来您的 Tabu 列表的大小太长或您的释放策略太严格。一个好的 Tabu 列表长度是
我正在阅读来自 cppreference 的代码示例: #include #include #include #include template void print_queue(T& q)
我快疯了,我试图理解工具提示的行为,但没有成功。 1. 第一个问题是当我尝试通过插件(按钮 1)在点击事件中使用它时 -> 如果您转到 Fiddle,您会在“内容”内看到该函数' 每次点击都会调用该属
我在功能组件中有以下代码: const [ folder, setFolder ] = useState([]); const folderData = useContext(FolderContex
我在使用预签名网址和 AFNetworking 3.0 从 S3 获取图像时遇到问题。我可以使用 NSMutableURLRequest 和 NSURLSession 获取图像,但是当我使用 AFHT
我正在使用 Oracle ojdbc 12 和 Java 8 处理 Oracle UCP 管理器的问题。当 UCP 池启动失败时,我希望关闭它创建的连接。 当池初始化期间遇到 ORA-02391:超过
关闭。此题需要details or clarity 。目前不接受答案。 想要改进这个问题吗?通过 editing this post 添加详细信息并澄清问题. 已关闭 9 年前。 Improve
引用这个plunker: https://plnkr.co/edit/GWsbdDWVvBYNMqyxzlLY?p=preview 我在 styles.css 文件和 src/app.ts 文件中指定
为什么我的条形这么细?我尝试将宽度设置为 1,它们变得非常厚。我不知道还能尝试什么。默认厚度为 0.8,这是应该的样子吗? import matplotlib.pyplot as plt import
当我编写时,查询按预期执行: SELECT id, day2.count - day1.count AS diff FROM day1 NATURAL JOIN day2; 但我真正想要的是右连接。当
我有以下时间数据: 0 08/01/16 13:07:46,335437 1 18/02/16 08:40:40,565575 2 14/01/16 22:2
一些背景知识 -我的 NodeJS 服务器在端口 3001 上运行,我的 React 应用程序在端口 3000 上运行。我在 React 应用程序 package.json 中设置了一个代理来代理对端
我面临着一个愚蠢的问题。我试图在我的 Angular 应用程序中延迟加载我的图像,我已经尝试过这个2: 但是他们都设置了 src attr 而不是 data-src,我在这里遗漏了什么吗?保留 d
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