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https://issues.apache.org/jira/browse/SPARK-18883?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15763747#comment-15763747
]
Mathieu D commented on SPARK-18883:
-----------------------------------
The problem does not appear with
mapreduce.fileoutputcommitter.algorithm.version=2 so far
> FileNotFoundException on _temporary directory
> ----------------------------------------------
>
> Key: SPARK-18883
> URL: https://issues.apache.org/jira/browse/SPARK-18883
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 2.0.2
> Environment: We're on a CDH 5.7, Hadoop 2.6.
> Reporter: Mathieu D
>
> I'm experiencing the following exception, usually after some time with heavy
> load :
> {code}
> 16/12/15 11:25:18 ERROR InsertIntoHadoopFsRelationCommand: Aborting job.
> java.io.FileNotFoundException: File
> hdfs://nameservice1/user/xdstore/rfs/rfsDB/_temporary/0 does not exist.
> at
> org.apache.hadoop.hdfs.DistributedFileSystem.listStatusInternal(DistributedFileSystem.java:795)
> at
> org.apache.hadoop.hdfs.DistributedFileSystem.access$700(DistributedFileSystem.java:106)
> at
> org.apache.hadoop.hdfs.DistributedFileSystem$18.doCall(DistributedFileSystem.java:853)
> at
> org.apache.hadoop.hdfs.DistributedFileSystem$18.doCall(DistributedFileSystem.java:849)
> at
> org.apache.hadoop.fs.FileSystemLinkResolver.resolve(FileSystemLinkResolver.java:81)
> at
> org.apache.hadoop.hdfs.DistributedFileSystem.listStatus(DistributedFileSystem.java:860)
> at org.apache.hadoop.fs.FileSystem.listStatus(FileSystem.java:1517)
> at org.apache.hadoop.fs.FileSystem.listStatus(FileSystem.java:1557)
> at
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.getAllCommittedTaskPaths(FileOutputCommitter.java:291)
> at
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.commitJobInternal(FileOutputCommitter.java:361)
> at
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.commitJob(FileOutputCommitter.java:334)
> at
> org.apache.parquet.hadoop.ParquetOutputCommitter.commitJob(ParquetOutputCommitter.java:46)
> at
> org.apache.spark.sql.execution.datasources.BaseWriterContainer.commitJob(WriterContainer.scala:222)
> at
> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand$$anonfun$run$1.apply$mcV$sp(InsertIntoHadoopFsRelationCommand.scala:144)
> at
> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand$$anonfun$run$1.apply(InsertIntoHadoopFsRelationCommand.scala:115)
> at
> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand$$anonfun$run$1.apply(InsertIntoHadoopFsRelationCommand.scala:115)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
> at
> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:115)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:58)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:56)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:74)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:115)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:115)
> at
> org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:136)
> at
> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
> at
> org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:133)
> at
> org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:114)
> at
> org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:86)
> at
> org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:86)
> at
> org.apache.spark.sql.execution.datasources.DataSource.write(DataSource.scala:525)
> at
> org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:211)
> at
> org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:194)
> at
> org.apache.spark.sql.DataFrameWriter.parquet(DataFrameWriter.scala:488)
> at
> com.bluedme.woda.ng.indexer.RfsRepository.append(RfsRepository.scala:36)
> at
> com.bluedme.woda.ng.indexer.RfsRepository.insert(RfsRepository.scala:23)
> at
> com.bluedme.woda.cmd.ShareDatasetImpl.runImmediate(ShareDatasetImpl.scala:33)
> at
> com.bluedme.woda.cmd.ShareDatasetImpl.runImmediate(ShareDatasetImpl.scala:13)
> at
> com.bluedme.woda.cmd.ImmediateCommandImpl$$anonfun$run$1.apply(CommandImpl.scala:21)
> at
> com.bluedme.woda.cmd.ImmediateCommandImpl$$anonfun$run$1.apply(CommandImpl.scala:21)
> at
> scala.concurrent.impl.Future$PromiseCompletingRunnable.liftedTree1$1(Future.scala:24)
> at
> scala.concurrent.impl.Future$PromiseCompletingRunnable.run(Future.scala:24)
> at
> scala.concurrent.impl.ExecutionContextImpl$AdaptedForkJoinTask.exec(ExecutionContextImpl.scala:121)
> at
> scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
> at
> scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
> at
> scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
> at
> scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
> {code}
> Looks similar to [SPARK-18512] although it's not the same environment : no
> streaming, no S3 here. Final path in stack different.
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