[
https://issues.apache.org/jira/browse/SPARK-43188?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Nicolas PHUNG updated SPARK-43188:
----------------------------------
Description:
Hello,
I have an issue with Spark 3.3.2 & Spark 3.4.0 to write into Azure Data Lake
Storage Gen2 (abfs/abfss scheme). I've got the following errors:
{code:java}
warn 13:12:47.554: StdErr from Kernel Process 23/04/19 13:12:47 ERROR
FileFormatWriter: Aborting job
6a75949c-1473-4445-b8ab-d125be3f0f21.org.apache.spark.SparkException: Job
aborted due to stage failure: Task 1 in stage 0.0 failed 1 times, most recent
failure: Lost task 1.0 in stage 0.0 (TID 1) (myhost executor driver):
org.apache.hadoop.util.DiskChecker$DiskErrorException: Could not find any valid
local directory for datablock-0001- at
org.apache.hadoop.fs.LocalDirAllocator$AllocatorPerContext.getLocalPathForWrite(LocalDirAllocator.java:462)
at
org.apache.hadoop.fs.LocalDirAllocator.getLocalPathForWrite(LocalDirAllocator.java:165)
at
org.apache.hadoop.fs.LocalDirAllocator.getLocalPathForWrite(LocalDirAllocator.java:146)
at
org.apache.hadoop.fs.store.DataBlocks$DiskBlockFactory.createTmpFileForWrite(DataBlocks.java:980)
at
org.apache.hadoop.fs.store.DataBlocks$DiskBlockFactory.create(DataBlocks.java:960)
at
org.apache.hadoop.fs.azurebfs.services.AbfsOutputStream.createBlockIfNeeded(AbfsOutputStream.java:262)
at
org.apache.hadoop.fs.azurebfs.services.AbfsOutputStream.<init>(AbfsOutputStream.java:173)
at
org.apache.hadoop.fs.azurebfs.AzureBlobFileSystemStore.createFile(AzureBlobFileSystemStore.java:580)
at
org.apache.hadoop.fs.azurebfs.AzureBlobFileSystem.create(AzureBlobFileSystem.java:301)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:1195) at
org.apache.hadoop.fs.FileSystem.create(FileSystem.java:1175) at
org.apache.parquet.hadoop.util.HadoopOutputFile.create(HadoopOutputFile.java:74)
at
org.apache.parquet.hadoop.ParquetFileWriter.<init>(ParquetFileWriter.java:347)
at
org.apache.parquet.hadoop.ParquetFileWriter.<init>(ParquetFileWriter.java:314)
at
org.apache.parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:480)
at
org.apache.parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:420)
at
org.apache.parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:409)
at
org.apache.spark.sql.execution.datasources.parquet.ParquetOutputWriter.<init>(ParquetOutputWriter.scala:36)
at
org.apache.spark.sql.execution.datasources.parquet.ParquetUtils$$anon$1.newInstance(ParquetUtils.scala:490)
at
org.apache.spark.sql.execution.datasources.SingleDirectoryDataWriter.newOutputWriter(FileFormatDataWriter.scala:161)
at
org.apache.spark.sql.execution.datasources.SingleDirectoryDataWriter.<init>(FileFormatDataWriter.scala:146)
at
org.apache.spark.sql.execution.datasources.FileFormatWriter$.executeTask(FileFormatWriter.scala:389)
at
org.apache.spark.sql.execution.datasources.WriteFilesExec.$anonfun$doExecuteWrite$1(WriteFiles.scala:100)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:888)
at
org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:888)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:364) at
org.apache.spark.rdd.RDD.iterator(RDD.scala:328) at
org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:92) at
org.apache.spark.TaskContext.runTaskWithListeners(TaskContext.scala:161) at
org.apache.spark.scheduler.Task.run(Task.scala:139) at
org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:554)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1529) at
org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:557) 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)
Driver stacktrace: at
org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2785)
at
org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2721)
at
org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2720)
at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49) at
org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2720)
at
org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1206)
at
org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1206)
at scala.Option.foreach(Option.scala:407) at
org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1206)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2984)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2923)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2912)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49) at
org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:971) at
org.apache.spark.SparkContext.runJob(SparkContext.scala:2263) at
org.apache.spark.sql.execution.datasources.FileFormatWriter$.$anonfun$executeWrite$4(FileFormatWriter.scala:307)
at
org.apache.spark.sql.execution.datasources.FileFormatWriter$.writeAndCommit(FileFormatWriter.scala:271)
at
org.apache.spark.sql.execution.datasources.FileFormatWriter$.executeWrite(FileFormatWriter.scala:304)
at
org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:190)
at
org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:190)
at
org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:113)
at
org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:111)
at
org.apache.spark.sql.execution.command.DataWritingCommandExec.executeCollect(commands.scala:125)
at
org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.$anonfun$applyOrElse$1(QueryExecution.scala:98)
at
org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$6(SQLExecution.scala:118)
at
org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:195)
at
org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:103)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:827)
at
org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:65)
at
org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:98)
at
org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:94)
at
org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$1(TreeNode.scala:512)
at
org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:104)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformDownWithPruning(TreeNode.scala:512)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDownWithPruning(LogicalPlan.scala:31)
at
org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning(AnalysisHelper.scala:267)
at
org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning$(AnalysisHelper.scala:263)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:31)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:31)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:488)
at
org.apache.spark.sql.execution.QueryExecution.eagerlyExecuteCommands(QueryExecution.scala:94)
at
org.apache.spark.sql.execution.QueryExecution.commandExecuted$lzycompute(QueryExecution.scala:81)
at
org.apache.spark.sql.execution.QueryExecution.commandExecuted(QueryExecution.scala:79)
at
org.apache.spark.sql.execution.QueryExecution.assertCommandExecuted(QueryExecution.scala:133)
at
org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:856)
at
org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:387)
at
org.apache.spark.sql.DataFrameWriter.saveInternal(DataFrameWriter.scala:360)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:239) at
org.apache.spark.sql.DataFrameWriter.parquet(DataFrameWriter.scala:789) at
sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498) at
py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244) at
py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:374) at
py4j.Gateway.invoke(Gateway.java:282) at
py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132) at
py4j.commands.CallCommand.execute(CallCommand.java:79) at
py4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:182)
at py4j.ClientServerConnection.run(ClientServerConnection.java:106) at
java.lang.Thread.run(Thread.java:748)Caused by:
org.apache.hadoop.util.DiskChecker$DiskErrorException: Could not find any valid
local directory for datablock-0001- at
org.apache.hadoop.fs.LocalDirAllocator$AllocatorPerContext.getLocalPathForWrite(LocalDirAllocator.java:462)
at
org.apache.hadoop.fs.LocalDirAllocator.getLocalPathForWrite(LocalDirAllocator.java:165)
at
org.apache.hadoop.fs.LocalDirAllocator.getLocalPathForWrite(LocalDirAllocator.java:146)
at
org.apache.hadoop.fs.store.DataBlocks$DiskBlockFactory.createTmpFileForWrite(DataBlocks.java:980)
at
org.apache.hadoop.fs.store.DataBlocks$DiskBlockFactory.create(DataBlocks.java:960)
at
org.apache.hadoop.fs.azurebfs.services.AbfsOutputStream.createBlockIfNeeded(AbfsOutputStream.java:262)
at
org.apache.hadoop.fs.azurebfs.services.AbfsOutputStream.<init>(AbfsOutputStream.java:173)
at
org.apache.hadoop.fs.azurebfs.AzureBlobFileSystemStore.createFile(AzureBlobFileSystemStore.java:580)
at
org.apache.hadoop.fs.azurebfs.AzureBlobFileSystem.create(AzureBlobFileSystem.java:301)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:1195) at
org.apache.hadoop.fs.FileSystem.create(FileSystem.java:1175) at
org.apache.parquet.hadoop.util.HadoopOutputFile.create(HadoopOutputFile.java:74)
at
org.apache.parquet.hadoop.ParquetFileWriter.<init>(ParquetFileWriter.java:347)
at
org.apache.parquet.hadoop.ParquetFileWriter.<init>(ParquetFileWriter.java:314)
at
org.apache.parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:480)
at
org.apache.parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:420)
at
org.apache.parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:409)
at
org.apache.spark.sql.execution.datasources.parquet.ParquetOutputWriter.<init>(ParquetOutputWriter.scala:36)
at
org.apache.spark.sql.execution.datasources.parquet.ParquetUtils$$anon$1.newInstance(ParquetUtils.scala:490)
at
org.apache.spark.sql.execution.datasources.SingleDirectoryDataWriter.newOutputWriter(FileFormatDataWriter.scala:161)
at
org.apache.spark.sql.execution.datasources.SingleDirectoryDataWriter.<init>(FileFormatDataWriter.scala:146)
at
org.apache.spark.sql.execution.datasources.FileFormatWriter$.executeTask(FileFormatWriter.scala:389)
at
org.apache.spark.sql.execution.datasources.WriteFilesExec.$anonfun$doExecuteWrite$1(WriteFiles.scala:100)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:888)
at
org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:888)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:364) at
org.apache.spark.rdd.RDD.iterator(RDD.scala:328) at
org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:92) at
org.apache.spark.TaskContext.runTaskWithListeners(TaskContext.scala:161) at
org.apache.spark.scheduler.Task.run(Task.scala:139) at
org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:554)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1529) at
org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:557) at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
... 1 more {code}
Before that, I was able to write into Azure Data Lake Storage with Spark 3.1.2
with hadoop-azure 3.2.1 without encountering this error.
Here's what I have tried but with no success:
* Spark 3.3.2 with hadoop-azure 3.3.2
* Spark 3.3.2 with hadoop-azure 3.3.5
* Spark 3.4.0 with hadoop-azure 3.3.4
* Spark 3.4.0 with hadoop-azure 3.3.5
Regards,
was:
Hello,
I have an issue with Spark 3.3.2 & Spark 3.4.0 to write into Azure Data Lake
Storage Gen2 (abfs/abfss scheme). I've got the following errors:
{code:java}
warn 13:12:47.554: StdErr from Kernel Process 23/04/19 13:12:47 ERROR
FileFormatWriter: Aborting job
6a75949c-1473-4445-b8ab-d125be3f0f21.org.apache.spark.SparkException: Job
aborted due to stage failure: Task 1 in stage 0.0 failed 1 times, most recent
failure: Lost task 1.0 in stage 0.0 (TID 1)
(FR07258024L.dsk.eur.msd.world.socgen executor driver):
org.apache.hadoop.util.DiskChecker$DiskErrorException: Could not find any valid
local directory for datablock-0001- at
org.apache.hadoop.fs.LocalDirAllocator$AllocatorPerContext.getLocalPathForWrite(LocalDirAllocator.java:462)
at
org.apache.hadoop.fs.LocalDirAllocator.getLocalPathForWrite(LocalDirAllocator.java:165)
at
org.apache.hadoop.fs.LocalDirAllocator.getLocalPathForWrite(LocalDirAllocator.java:146)
at
org.apache.hadoop.fs.store.DataBlocks$DiskBlockFactory.createTmpFileForWrite(DataBlocks.java:980)
at
org.apache.hadoop.fs.store.DataBlocks$DiskBlockFactory.create(DataBlocks.java:960)
at
org.apache.hadoop.fs.azurebfs.services.AbfsOutputStream.createBlockIfNeeded(AbfsOutputStream.java:262)
at
org.apache.hadoop.fs.azurebfs.services.AbfsOutputStream.<init>(AbfsOutputStream.java:173)
at
org.apache.hadoop.fs.azurebfs.AzureBlobFileSystemStore.createFile(AzureBlobFileSystemStore.java:580)
at
org.apache.hadoop.fs.azurebfs.AzureBlobFileSystem.create(AzureBlobFileSystem.java:301)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:1195) at
org.apache.hadoop.fs.FileSystem.create(FileSystem.java:1175) at
org.apache.parquet.hadoop.util.HadoopOutputFile.create(HadoopOutputFile.java:74)
at
org.apache.parquet.hadoop.ParquetFileWriter.<init>(ParquetFileWriter.java:347)
at
org.apache.parquet.hadoop.ParquetFileWriter.<init>(ParquetFileWriter.java:314)
at
org.apache.parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:480)
at
org.apache.parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:420)
at
org.apache.parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:409)
at
org.apache.spark.sql.execution.datasources.parquet.ParquetOutputWriter.<init>(ParquetOutputWriter.scala:36)
at
org.apache.spark.sql.execution.datasources.parquet.ParquetUtils$$anon$1.newInstance(ParquetUtils.scala:490)
at
org.apache.spark.sql.execution.datasources.SingleDirectoryDataWriter.newOutputWriter(FileFormatDataWriter.scala:161)
at
org.apache.spark.sql.execution.datasources.SingleDirectoryDataWriter.<init>(FileFormatDataWriter.scala:146)
at
org.apache.spark.sql.execution.datasources.FileFormatWriter$.executeTask(FileFormatWriter.scala:389)
at
org.apache.spark.sql.execution.datasources.WriteFilesExec.$anonfun$doExecuteWrite$1(WriteFiles.scala:100)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:888)
at
org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:888)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:364) at
org.apache.spark.rdd.RDD.iterator(RDD.scala:328) at
org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:92) at
org.apache.spark.TaskContext.runTaskWithListeners(TaskContext.scala:161) at
org.apache.spark.scheduler.Task.run(Task.scala:139) at
org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:554)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1529) at
org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:557) at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Driver stacktrace: at
org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2785)
at
org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2721)
at
org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2720)
at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49) at
org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2720)
at
org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1206)
at
org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1206)
at scala.Option.foreach(Option.scala:407) at
org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1206)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2984)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2923)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2912)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49) at
org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:971) at
org.apache.spark.SparkContext.runJob(SparkContext.scala:2263) at
org.apache.spark.sql.execution.datasources.FileFormatWriter$.$anonfun$executeWrite$4(FileFormatWriter.scala:307)
at
org.apache.spark.sql.execution.datasources.FileFormatWriter$.writeAndCommit(FileFormatWriter.scala:271)
at
org.apache.spark.sql.execution.datasources.FileFormatWriter$.executeWrite(FileFormatWriter.scala:304)
at
org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:190)
at
org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:190)
at
org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:113)
at
org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:111)
at
org.apache.spark.sql.execution.command.DataWritingCommandExec.executeCollect(commands.scala:125)
at
org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.$anonfun$applyOrElse$1(QueryExecution.scala:98)
at
org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$6(SQLExecution.scala:118)
at
org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:195)
at
org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:103)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:827)
at
org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:65)
at
org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:98)
at
org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:94)
at
org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$1(TreeNode.scala:512)
at
org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:104)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformDownWithPruning(TreeNode.scala:512)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDownWithPruning(LogicalPlan.scala:31)
at
org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning(AnalysisHelper.scala:267)
at
org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning$(AnalysisHelper.scala:263)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:31)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:31)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:488)
at
org.apache.spark.sql.execution.QueryExecution.eagerlyExecuteCommands(QueryExecution.scala:94)
at
org.apache.spark.sql.execution.QueryExecution.commandExecuted$lzycompute(QueryExecution.scala:81)
at
org.apache.spark.sql.execution.QueryExecution.commandExecuted(QueryExecution.scala:79)
at
org.apache.spark.sql.execution.QueryExecution.assertCommandExecuted(QueryExecution.scala:133)
at
org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:856)
at
org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:387)
at
org.apache.spark.sql.DataFrameWriter.saveInternal(DataFrameWriter.scala:360)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:239) at
org.apache.spark.sql.DataFrameWriter.parquet(DataFrameWriter.scala:789) 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:374) 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.ClientServerConnection.waitForCommands(ClientServerConnection.java:182)
at py4j.ClientServerConnection.run(ClientServerConnection.java:106) at
java.lang.Thread.run(Thread.java:748)Caused by:
org.apache.hadoop.util.DiskChecker$DiskErrorException: Could not find any valid
local directory for datablock-0001- at
org.apache.hadoop.fs.LocalDirAllocator$AllocatorPerContext.getLocalPathForWrite(LocalDirAllocator.java:462)
at
org.apache.hadoop.fs.LocalDirAllocator.getLocalPathForWrite(LocalDirAllocator.java:165)
at
org.apache.hadoop.fs.LocalDirAllocator.getLocalPathForWrite(LocalDirAllocator.java:146)
at
org.apache.hadoop.fs.store.DataBlocks$DiskBlockFactory.createTmpFileForWrite(DataBlocks.java:980)
at
org.apache.hadoop.fs.store.DataBlocks$DiskBlockFactory.create(DataBlocks.java:960)
at
org.apache.hadoop.fs.azurebfs.services.AbfsOutputStream.createBlockIfNeeded(AbfsOutputStream.java:262)
at
org.apache.hadoop.fs.azurebfs.services.AbfsOutputStream.<init>(AbfsOutputStream.java:173)
at
org.apache.hadoop.fs.azurebfs.AzureBlobFileSystemStore.createFile(AzureBlobFileSystemStore.java:580)
at
org.apache.hadoop.fs.azurebfs.AzureBlobFileSystem.create(AzureBlobFileSystem.java:301)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:1195) at
org.apache.hadoop.fs.FileSystem.create(FileSystem.java:1175) at
org.apache.parquet.hadoop.util.HadoopOutputFile.create(HadoopOutputFile.java:74)
at
org.apache.parquet.hadoop.ParquetFileWriter.<init>(ParquetFileWriter.java:347)
at
org.apache.parquet.hadoop.ParquetFileWriter.<init>(ParquetFileWriter.java:314)
at
org.apache.parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:480)
at
org.apache.parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:420)
at
org.apache.parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:409)
at
org.apache.spark.sql.execution.datasources.parquet.ParquetOutputWriter.<init>(ParquetOutputWriter.scala:36)
at
org.apache.spark.sql.execution.datasources.parquet.ParquetUtils$$anon$1.newInstance(ParquetUtils.scala:490)
at
org.apache.spark.sql.execution.datasources.SingleDirectoryDataWriter.newOutputWriter(FileFormatDataWriter.scala:161)
at
org.apache.spark.sql.execution.datasources.SingleDirectoryDataWriter.<init>(FileFormatDataWriter.scala:146)
at
org.apache.spark.sql.execution.datasources.FileFormatWriter$.executeTask(FileFormatWriter.scala:389)
at
org.apache.spark.sql.execution.datasources.WriteFilesExec.$anonfun$doExecuteWrite$1(WriteFiles.scala:100)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:888)
at
org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:888)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:364) at
org.apache.spark.rdd.RDD.iterator(RDD.scala:328) at
org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:92) at
org.apache.spark.TaskContext.runTaskWithListeners(TaskContext.scala:161) at
org.apache.spark.scheduler.Task.run(Task.scala:139) at
org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:554)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1529) at
org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:557) at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
... 1 more {code}
Before that, I was able to write into Azure Data Lake Storage with Spark 3.1.2
with hadoop-azure 3.2.1 without encountering this error.
Here's what I have tried but with no success:
* Spark 3.3.2 with hadoop-azure 3.3.2
* Spark 3.3.2 with hadoop-azure 3.3.5
* Spark 3.4.0 with hadoop-azure 3.3.4
* Spark 3.4.0 with hadoop-azure 3.3.5
Regards,
> Cannot write to Azure Datalake Gen2 (abfs/abfss) after Spark 3.1.2
> ------------------------------------------------------------------
>
> Key: SPARK-43188
> URL: https://issues.apache.org/jira/browse/SPARK-43188
> Project: Spark
> Issue Type: Bug
> Components: PySpark, Spark Core
> Affects Versions: 3.3.2, 3.4.0
> Reporter: Nicolas PHUNG
> Priority: Major
>
> Hello,
> I have an issue with Spark 3.3.2 & Spark 3.4.0 to write into Azure Data Lake
> Storage Gen2 (abfs/abfss scheme). I've got the following errors:
> {code:java}
> warn 13:12:47.554: StdErr from Kernel Process 23/04/19 13:12:47 ERROR
> FileFormatWriter: Aborting job
> 6a75949c-1473-4445-b8ab-d125be3f0f21.org.apache.spark.SparkException: Job
> aborted due to stage failure: Task 1 in stage 0.0 failed 1 times, most recent
> failure: Lost task 1.0 in stage 0.0 (TID 1) (myhost executor driver):
> org.apache.hadoop.util.DiskChecker$DiskErrorException: Could not find any
> valid local directory for datablock-0001- at
> org.apache.hadoop.fs.LocalDirAllocator$AllocatorPerContext.getLocalPathForWrite(LocalDirAllocator.java:462)
> at
> org.apache.hadoop.fs.LocalDirAllocator.getLocalPathForWrite(LocalDirAllocator.java:165)
> at
> org.apache.hadoop.fs.LocalDirAllocator.getLocalPathForWrite(LocalDirAllocator.java:146)
> at
> org.apache.hadoop.fs.store.DataBlocks$DiskBlockFactory.createTmpFileForWrite(DataBlocks.java:980)
> at
> org.apache.hadoop.fs.store.DataBlocks$DiskBlockFactory.create(DataBlocks.java:960)
> at
> org.apache.hadoop.fs.azurebfs.services.AbfsOutputStream.createBlockIfNeeded(AbfsOutputStream.java:262)
> at
> org.apache.hadoop.fs.azurebfs.services.AbfsOutputStream.<init>(AbfsOutputStream.java:173)
> at
> org.apache.hadoop.fs.azurebfs.AzureBlobFileSystemStore.createFile(AzureBlobFileSystemStore.java:580)
> at
> org.apache.hadoop.fs.azurebfs.AzureBlobFileSystem.create(AzureBlobFileSystem.java:301)
> at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:1195) at
> org.apache.hadoop.fs.FileSystem.create(FileSystem.java:1175) at
> org.apache.parquet.hadoop.util.HadoopOutputFile.create(HadoopOutputFile.java:74)
> at
> org.apache.parquet.hadoop.ParquetFileWriter.<init>(ParquetFileWriter.java:347)
> at
> org.apache.parquet.hadoop.ParquetFileWriter.<init>(ParquetFileWriter.java:314)
> at
> org.apache.parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:480)
> at
> org.apache.parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:420)
> at
> org.apache.parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:409)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetOutputWriter.<init>(ParquetOutputWriter.scala:36)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetUtils$$anon$1.newInstance(ParquetUtils.scala:490)
> at
> org.apache.spark.sql.execution.datasources.SingleDirectoryDataWriter.newOutputWriter(FileFormatDataWriter.scala:161)
> at
> org.apache.spark.sql.execution.datasources.SingleDirectoryDataWriter.<init>(FileFormatDataWriter.scala:146)
> at
> org.apache.spark.sql.execution.datasources.FileFormatWriter$.executeTask(FileFormatWriter.scala:389)
> at
> org.apache.spark.sql.execution.datasources.WriteFilesExec.$anonfun$doExecuteWrite$1(WriteFiles.scala:100)
> at
> org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:888)
> at
> org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:888)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:364) at
> org.apache.spark.rdd.RDD.iterator(RDD.scala:328) at
> org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:92) at
> org.apache.spark.TaskContext.runTaskWithListeners(TaskContext.scala:161)
> at org.apache.spark.scheduler.Task.run(Task.scala:139) at
> org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:554)
> at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1529)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:557)
> 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)
> Driver stacktrace: at
> org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2785)
> at
> org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2721)
> at
> org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2720)
> at
> scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
> at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49) at
> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2720)
> at
> org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1206)
> at
> org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1206)
> at scala.Option.foreach(Option.scala:407) at
> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1206)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2984)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2923)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2912)
> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49) at
> org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:971) at
> org.apache.spark.SparkContext.runJob(SparkContext.scala:2263) at
> org.apache.spark.sql.execution.datasources.FileFormatWriter$.$anonfun$executeWrite$4(FileFormatWriter.scala:307)
> at
> org.apache.spark.sql.execution.datasources.FileFormatWriter$.writeAndCommit(FileFormatWriter.scala:271)
> at
> org.apache.spark.sql.execution.datasources.FileFormatWriter$.executeWrite(FileFormatWriter.scala:304)
> at
> org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:190)
> at
> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:190)
> at
> org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:113)
> at
> org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:111)
> at
> org.apache.spark.sql.execution.command.DataWritingCommandExec.executeCollect(commands.scala:125)
> at
> org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.$anonfun$applyOrElse$1(QueryExecution.scala:98)
> at
> org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$6(SQLExecution.scala:118)
> at
> org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:195)
> at
> org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:103)
> at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:827)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:65)
> at
> org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:98)
> at
> org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:94)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$1(TreeNode.scala:512)
> at
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:104)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformDownWithPruning(TreeNode.scala:512)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDownWithPruning(LogicalPlan.scala:31)
> at
> org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning(AnalysisHelper.scala:267)
> at
> org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning$(AnalysisHelper.scala:263)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:31)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:31)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:488)
> at
> org.apache.spark.sql.execution.QueryExecution.eagerlyExecuteCommands(QueryExecution.scala:94)
> at
> org.apache.spark.sql.execution.QueryExecution.commandExecuted$lzycompute(QueryExecution.scala:81)
> at
> org.apache.spark.sql.execution.QueryExecution.commandExecuted(QueryExecution.scala:79)
> at
> org.apache.spark.sql.execution.QueryExecution.assertCommandExecuted(QueryExecution.scala:133)
> at
> org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:856)
> at
> org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:387)
> at
> org.apache.spark.sql.DataFrameWriter.saveInternal(DataFrameWriter.scala:360)
> at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:239)
> at org.apache.spark.sql.DataFrameWriter.parquet(DataFrameWriter.scala:789)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:498) at
> py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244) at
> py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:374) at
> py4j.Gateway.invoke(Gateway.java:282) at
> py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132) at
> py4j.commands.CallCommand.execute(CallCommand.java:79) at
> py4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:182)
> at py4j.ClientServerConnection.run(ClientServerConnection.java:106) at
> java.lang.Thread.run(Thread.java:748)Caused by:
> org.apache.hadoop.util.DiskChecker$DiskErrorException: Could not find any
> valid local directory for datablock-0001- at
> org.apache.hadoop.fs.LocalDirAllocator$AllocatorPerContext.getLocalPathForWrite(LocalDirAllocator.java:462)
> at
> org.apache.hadoop.fs.LocalDirAllocator.getLocalPathForWrite(LocalDirAllocator.java:165)
> at
> org.apache.hadoop.fs.LocalDirAllocator.getLocalPathForWrite(LocalDirAllocator.java:146)
> at
> org.apache.hadoop.fs.store.DataBlocks$DiskBlockFactory.createTmpFileForWrite(DataBlocks.java:980)
> at
> org.apache.hadoop.fs.store.DataBlocks$DiskBlockFactory.create(DataBlocks.java:960)
> at
> org.apache.hadoop.fs.azurebfs.services.AbfsOutputStream.createBlockIfNeeded(AbfsOutputStream.java:262)
> at
> org.apache.hadoop.fs.azurebfs.services.AbfsOutputStream.<init>(AbfsOutputStream.java:173)
> at
> org.apache.hadoop.fs.azurebfs.AzureBlobFileSystemStore.createFile(AzureBlobFileSystemStore.java:580)
> at
> org.apache.hadoop.fs.azurebfs.AzureBlobFileSystem.create(AzureBlobFileSystem.java:301)
> at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:1195) at
> org.apache.hadoop.fs.FileSystem.create(FileSystem.java:1175) at
> org.apache.parquet.hadoop.util.HadoopOutputFile.create(HadoopOutputFile.java:74)
> at
> org.apache.parquet.hadoop.ParquetFileWriter.<init>(ParquetFileWriter.java:347)
> at
> org.apache.parquet.hadoop.ParquetFileWriter.<init>(ParquetFileWriter.java:314)
> at
> org.apache.parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:480)
> at
> org.apache.parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:420)
> at
> org.apache.parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:409)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetOutputWriter.<init>(ParquetOutputWriter.scala:36)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetUtils$$anon$1.newInstance(ParquetUtils.scala:490)
> at
> org.apache.spark.sql.execution.datasources.SingleDirectoryDataWriter.newOutputWriter(FileFormatDataWriter.scala:161)
> at
> org.apache.spark.sql.execution.datasources.SingleDirectoryDataWriter.<init>(FileFormatDataWriter.scala:146)
> at
> org.apache.spark.sql.execution.datasources.FileFormatWriter$.executeTask(FileFormatWriter.scala:389)
> at
> org.apache.spark.sql.execution.datasources.WriteFilesExec.$anonfun$doExecuteWrite$1(WriteFiles.scala:100)
> at
> org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:888)
> at
> org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:888)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:364) at
> org.apache.spark.rdd.RDD.iterator(RDD.scala:328) at
> org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:92) at
> org.apache.spark.TaskContext.runTaskWithListeners(TaskContext.scala:161)
> at org.apache.spark.scheduler.Task.run(Task.scala:139) at
> org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:554)
> at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1529)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:557)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
> ... 1 more {code}
> Before that, I was able to write into Azure Data Lake Storage with Spark
> 3.1.2 with hadoop-azure 3.2.1 without encountering this error.
> Here's what I have tried but with no success:
> * Spark 3.3.2 with hadoop-azure 3.3.2
> * Spark 3.3.2 with hadoop-azure 3.3.5
> * Spark 3.4.0 with hadoop-azure 3.3.4
> * Spark 3.4.0 with hadoop-azure 3.3.5
> Regards,
>
--
This message was sent by Atlassian Jira
(v8.20.10#820010)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
