[jira] [Commented] (SPARK-18512) FileNotFoundException on _temporary directory with Spark Streaming 2.0.1 and S3A
[
https://issues.apache.org/jira/browse/SPARK-18512?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15751577#comment-15751577
]
Mathieu D commented on SPARK-18512:
---
[SPARK-18883]
> FileNotFoundException on _temporary directory with Spark Streaming 2.0.1 and
> S3A
>
>
> Key: SPARK-18512
> URL: https://issues.apache.org/jira/browse/SPARK-18512
> Project: Spark
> Issue Type: Bug
> Components: Structured Streaming
>Affects Versions: 2.0.1
> Environment: AWS EMR 5.0.1
> Spark 2.0.1
> S3 EU-West-1 (S3A)
>Reporter: Giuseppe Bonaccorso
>
> After a few hours of streaming processing and data saving in Parquet format,
> I got always this exception:
> {code:java}
> java.io.FileNotFoundException: No such file or directory:
> s3a://xxx/_temporary/0/task_
> at
> org.apache.hadoop.fs.s3a.S3AFileSystem.getFileStatus(S3AFileSystem.java:1004)
> at
> org.apache.hadoop.fs.s3a.S3AFileSystem.listStatus(S3AFileSystem.java:745)
> at
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.mergePaths(FileOutputCommitter.java:426)
> at
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.commitJobInternal(FileOutputCommitter.java:362)
> 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$$anonfun$run$1.apply(InsertIntoHadoopFsRelationCommand.scala:115)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
> at
> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:115)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:60)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:58)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:74)
> at
> org.apache.spark.sql.execution.SparkPlan$$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:510)
> 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)
> {code}
> I've tried also s3:// and s3n:// but it always happens after a 3-5 hours.
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[jira] [Commented] (SPARK-18512) FileNotFoundException on _temporary directory with Spark Streaming 2.0.1 and S3A
[
https://issues.apache.org/jira/browse/SPARK-18512?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15751492#comment-15751492
]
Steve Loughran commented on SPARK-18512:
yes, file a SPARK one and that can be a base for blame assignment.
looking at the trace, it's happening because the actual job attempt path is
mssing, which is generally considered traumatic. And you are following a
codepath which only exists if you are using the v1 "all renames at the end"
algorithm. Try to use the v2 algorithm,
mapreduce.fileoutputcommitter.algorithm.version = 2 , to see if that helps
> FileNotFoundException on _temporary directory with Spark Streaming 2.0.1 and
> S3A
>
>
> Key: SPARK-18512
> URL: https://issues.apache.org/jira/browse/SPARK-18512
> Project: Spark
> Issue Type: Bug
> Components: Structured Streaming
>Affects Versions: 2.0.1
> Environment: AWS EMR 5.0.1
> Spark 2.0.1
> S3 EU-West-1 (S3A)
>Reporter: Giuseppe Bonaccorso
>
> After a few hours of streaming processing and data saving in Parquet format,
> I got always this exception:
> {code:java}
> java.io.FileNotFoundException: No such file or directory:
> s3a://xxx/_temporary/0/task_
> at
> org.apache.hadoop.fs.s3a.S3AFileSystem.getFileStatus(S3AFileSystem.java:1004)
> at
> org.apache.hadoop.fs.s3a.S3AFileSystem.listStatus(S3AFileSystem.java:745)
> at
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.mergePaths(FileOutputCommitter.java:426)
> at
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.commitJobInternal(FileOutputCommitter.java:362)
> 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$$anonfun$run$1.apply(InsertIntoHadoopFsRelationCommand.scala:115)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
> at
> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:115)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:60)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:58)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:74)
> at
> org.apache.spark.sql.execution.SparkPlan$$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:510)
> 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)
> {code}
> I've tried also s3:// and s3n:// but it always happens after a 3-5 hours.
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[jira] [Commented] (SPARK-18512) FileNotFoundException on _temporary directory with Spark Streaming 2.0.1 and S3A
[
https://issues.apache.org/jira/browse/SPARK-18512?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15751329#comment-15751329
]
Mathieu D commented on SPARK-18512:
---
I'm experiencing the same problem, but we're using HDFS, not S3.
{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.fo
[jira] [Commented] (SPARK-18512) FileNotFoundException on _temporary directory with Spark Streaming 2.0.1 and S3A
[
https://issues.apache.org/jira/browse/SPARK-18512?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15726310#comment-15726310
]
Steve Loughran commented on SPARK-18512:
It'd be good to get some more details from people who see this, especially if
they have the commit algorithm = 2, which is the one with reduced renames. That
is: collect your stack traces and see what specific conditions trigger it. If
it's that the directory "temporary" has been deleted and yet it still appeared
in the listing for the merge, well, maybe we should have special handling for
the case that it has vanished. For example, in the committer, build a map of
which directories have been deleted by that instance, hence, which it doesn't
have to worry about.
(that's not necessarily going to work, as the committers run across the
cluster; it's why dynamodb is needed)
> FileNotFoundException on _temporary directory with Spark Streaming 2.0.1 and
> S3A
>
>
> Key: SPARK-18512
> URL: https://issues.apache.org/jira/browse/SPARK-18512
> Project: Spark
> Issue Type: Bug
> Components: Structured Streaming
>Affects Versions: 2.0.1
> Environment: AWS EMR 5.0.1
> Spark 2.0.1
> S3 EU-West-1 (S3A)
>Reporter: Giuseppe Bonaccorso
>
> After a few hours of streaming processing and data saving in Parquet format,
> I got always this exception:
> {code:java}
> java.io.FileNotFoundException: No such file or directory:
> s3a://xxx/_temporary/0/task_
> at
> org.apache.hadoop.fs.s3a.S3AFileSystem.getFileStatus(S3AFileSystem.java:1004)
> at
> org.apache.hadoop.fs.s3a.S3AFileSystem.listStatus(S3AFileSystem.java:745)
> at
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.mergePaths(FileOutputCommitter.java:426)
> at
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.commitJobInternal(FileOutputCommitter.java:362)
> 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$$anonfun$run$1.apply(InsertIntoHadoopFsRelationCommand.scala:115)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
> at
> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:115)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:60)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:58)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:74)
> at
> org.apache.spark.sql.execution.SparkPlan$$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:510)
> 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)
> {code}
> I've tried also s3:// and s3n:// but it always happens after a 3-5 hours.
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[jira] [Commented] (SPARK-18512) FileNotFoundException on _temporary directory with Spark Streaming 2.0.1 and S3A
[
https://issues.apache.org/jira/browse/SPARK-18512?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15726148#comment-15726148
]
Adrian Bridgett commented on SPARK-18512:
-
Thanks Steve - just seen a "next few weeks" mentioned in hadoop-common-dev :-)
TBH I can't quite see how the cleanup-failures.ignored patch is going to help
in the mergePaths case - so I'm looking at just re-running our jobs if they hit
problems (and getting some idea of how often that's going to be). S3 is a big
cost saver for us vs running HDFS :-)
> FileNotFoundException on _temporary directory with Spark Streaming 2.0.1 and
> S3A
>
>
> Key: SPARK-18512
> URL: https://issues.apache.org/jira/browse/SPARK-18512
> Project: Spark
> Issue Type: Bug
> Components: Structured Streaming
>Affects Versions: 2.0.1
> Environment: AWS EMR 5.0.1
> Spark 2.0.1
> S3 EU-West-1 (S3A)
>Reporter: Giuseppe Bonaccorso
>
> After a few hours of streaming processing and data saving in Parquet format,
> I got always this exception:
> {code:java}
> java.io.FileNotFoundException: No such file or directory:
> s3a://xxx/_temporary/0/task_
> at
> org.apache.hadoop.fs.s3a.S3AFileSystem.getFileStatus(S3AFileSystem.java:1004)
> at
> org.apache.hadoop.fs.s3a.S3AFileSystem.listStatus(S3AFileSystem.java:745)
> at
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.mergePaths(FileOutputCommitter.java:426)
> at
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.commitJobInternal(FileOutputCommitter.java:362)
> 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$$anonfun$run$1.apply(InsertIntoHadoopFsRelationCommand.scala:115)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
> at
> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:115)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:60)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:58)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:74)
> at
> org.apache.spark.sql.execution.SparkPlan$$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:510)
> 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)
> {code}
> I've tried also s3:// and s3n:// but it always happens after a 3-5 hours.
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[jira] [Commented] (SPARK-18512) FileNotFoundException on _temporary directory with Spark Streaming 2.0.1 and S3A
[
https://issues.apache.org/jira/browse/SPARK-18512?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15726135#comment-15726135
]
Steve Loughran commented on SPARK-18512:
ah, the "when will 2.8 ship" question. Really close, Jun Ping owns the problem,
and the s3a performance work has been helping slow it down (or at least meaning
I've not been pushing for a release).
I am doing a (better, faster) comitter which will be deterministic with
dynamodb backing. Without that, writing to any eventually consistent store is
danger, because spark makes some fundamental assumptions about filesystems "if
a file says it is there in a listing, and of a given size", then you can open
it and read in that much data. Similarly, there's the assumption that after you
delete something, they aren't visible any more.
Anyway, you could ask on the MR JIRA about getting that backported to Hadoop
2.7.x; I don't see any fundamental reason to veto it: no risk of breaking
things if the option isn't set
> FileNotFoundException on _temporary directory with Spark Streaming 2.0.1 and
> S3A
>
>
> Key: SPARK-18512
> URL: https://issues.apache.org/jira/browse/SPARK-18512
> Project: Spark
> Issue Type: Bug
> Components: Structured Streaming
>Affects Versions: 2.0.1
> Environment: AWS EMR 5.0.1
> Spark 2.0.1
> S3 EU-West-1 (S3A)
>Reporter: Giuseppe Bonaccorso
>
> After a few hours of streaming processing and data saving in Parquet format,
> I got always this exception:
> {code:java}
> java.io.FileNotFoundException: No such file or directory:
> s3a://xxx/_temporary/0/task_
> at
> org.apache.hadoop.fs.s3a.S3AFileSystem.getFileStatus(S3AFileSystem.java:1004)
> at
> org.apache.hadoop.fs.s3a.S3AFileSystem.listStatus(S3AFileSystem.java:745)
> at
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.mergePaths(FileOutputCommitter.java:426)
> at
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.commitJobInternal(FileOutputCommitter.java:362)
> 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$$anonfun$run$1.apply(InsertIntoHadoopFsRelationCommand.scala:115)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
> at
> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:115)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:60)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:58)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:74)
> at
> org.apache.spark.sql.execution.SparkPlan$$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:510)
> 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)
> {code}
> I've tried also s3:// and s3n:// but it always happens after a 3-5 hours.
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[jira] [Commented] (SPARK-18512) FileNotFoundException on _temporary directory with Spark Streaming 2.0.1 and S3A
[
https://issues.apache.org/jira/browse/SPARK-18512?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15725242#comment-15725242
]
Adrian Bridgett commented on SPARK-18512:
-
So currently, with Spark2 there's no sensible way to write to S3? (Think of
this as a question not a rant!) That is no way to avoid either S3 rename
latency problems or this issue, unless you use EMRFS or e.g. write to HDFS
first and distcp the files over?
I wonder if a backport of MAPREDUCE-6478 to hadoop-2.7.x is on the cards
(hadoop-2.8.x is presumably a while away from production readiness).
> FileNotFoundException on _temporary directory with Spark Streaming 2.0.1 and
> S3A
>
>
> Key: SPARK-18512
> URL: https://issues.apache.org/jira/browse/SPARK-18512
> Project: Spark
> Issue Type: Bug
> Components: Structured Streaming
>Affects Versions: 2.0.1
> Environment: AWS EMR 5.0.1
> Spark 2.0.1
> S3 EU-West-1 (S3A)
>Reporter: Giuseppe Bonaccorso
>
> After a few hours of streaming processing and data saving in Parquet format,
> I got always this exception:
> {code:java}
> java.io.FileNotFoundException: No such file or directory:
> s3a://xxx/_temporary/0/task_
> at
> org.apache.hadoop.fs.s3a.S3AFileSystem.getFileStatus(S3AFileSystem.java:1004)
> at
> org.apache.hadoop.fs.s3a.S3AFileSystem.listStatus(S3AFileSystem.java:745)
> at
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.mergePaths(FileOutputCommitter.java:426)
> at
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.commitJobInternal(FileOutputCommitter.java:362)
> 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$$anonfun$run$1.apply(InsertIntoHadoopFsRelationCommand.scala:115)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
> at
> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:115)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:60)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:58)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:74)
> at
> org.apache.spark.sql.execution.SparkPlan$$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:510)
> 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)
> {code}
> I've tried also s3:// and s3n:// but it always happens after a 3-5 hours.
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[jira] [Commented] (SPARK-18512) FileNotFoundException on _temporary directory with Spark Streaming 2.0.1 and S3A
[
https://issues.apache.org/jira/browse/SPARK-18512?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15722354#comment-15722354
]
Steve Loughran commented on SPARK-18512:
of course, if you do switch to EMRFS, you should get that consistent view...can
you try that and update the JIRA on whether that makes it go away.
> FileNotFoundException on _temporary directory with Spark Streaming 2.0.1 and
> S3A
>
>
> Key: SPARK-18512
> URL: https://issues.apache.org/jira/browse/SPARK-18512
> Project: Spark
> Issue Type: Bug
> Components: Structured Streaming
>Affects Versions: 2.0.1
> Environment: AWS EMR 5.0.1
> Spark 2.0.1
> S3 EU-West-1 (S3A)
>Reporter: Giuseppe Bonaccorso
>
> After a few hours of streaming processing and data saving in Parquet format,
> I got always this exception:
> {code:java}
> java.io.FileNotFoundException: No such file or directory:
> s3a://xxx/_temporary/0/task_
> at
> org.apache.hadoop.fs.s3a.S3AFileSystem.getFileStatus(S3AFileSystem.java:1004)
> at
> org.apache.hadoop.fs.s3a.S3AFileSystem.listStatus(S3AFileSystem.java:745)
> at
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.mergePaths(FileOutputCommitter.java:426)
> at
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.commitJobInternal(FileOutputCommitter.java:362)
> 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$$anonfun$run$1.apply(InsertIntoHadoopFsRelationCommand.scala:115)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
> at
> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:115)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:60)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:58)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:74)
> at
> org.apache.spark.sql.execution.SparkPlan$$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:510)
> 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)
> {code}
> I've tried also s3:// and s3n:// but it always happens after a 3-5 hours.
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[jira] [Commented] (SPARK-18512) FileNotFoundException on _temporary directory with Spark Streaming 2.0.1 and S3A
[
https://issues.apache.org/jira/browse/SPARK-18512?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15722320#comment-15722320
]
Steve Loughran commented on SPARK-18512:
Actually, this is the problem whcih MAPREDUCE-6478 deals with surfacing; that
{{cleanup-failures.ignored}} option. However, that's not shipping in Hadoop
2.7.x; it will be out in Hadoop 2.8. I do not know what is in AWS EMR, or its
roadmap, so cannot comment about whether setting the flag currently does
anything. Sorry
> FileNotFoundException on _temporary directory with Spark Streaming 2.0.1 and
> S3A
>
>
> Key: SPARK-18512
> URL: https://issues.apache.org/jira/browse/SPARK-18512
> Project: Spark
> Issue Type: Bug
> Components: Structured Streaming
>Affects Versions: 2.0.1
> Environment: AWS EMR 5.0.1
> Spark 2.0.1
> S3 EU-West-1 (S3A)
>Reporter: Giuseppe Bonaccorso
>
> After a few hours of streaming processing and data saving in Parquet format,
> I got always this exception:
> {code:java}
> java.io.FileNotFoundException: No such file or directory:
> s3a://xxx/_temporary/0/task_
> at
> org.apache.hadoop.fs.s3a.S3AFileSystem.getFileStatus(S3AFileSystem.java:1004)
> at
> org.apache.hadoop.fs.s3a.S3AFileSystem.listStatus(S3AFileSystem.java:745)
> at
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.mergePaths(FileOutputCommitter.java:426)
> at
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.commitJobInternal(FileOutputCommitter.java:362)
> 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$$anonfun$run$1.apply(InsertIntoHadoopFsRelationCommand.scala:115)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
> at
> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:115)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:60)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:58)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:74)
> at
> org.apache.spark.sql.execution.SparkPlan$$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:510)
> 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)
> {code}
> I've tried also s3:// and s3n:// but it always happens after a 3-5 hours.
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[jira] [Commented] (SPARK-18512) FileNotFoundException on _temporary directory with Spark Streaming 2.0.1 and S3A
[
https://issues.apache.org/jira/browse/SPARK-18512?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15722304#comment-15722304
]
Steve Loughran commented on SPARK-18512:
no. What you are seeing is an eventual consistency surfacing; the listing
showing files which aren't there, and a committer which expects a consistency
between the file listed and the files existing. HADOOP-13786 covers the
development of an output committer explicitly for s3 + dynamo; it's the latter
which offers the consistency. I could try and make it more robust against a
file in the listing not actually being present though: downgrade from an error
to warning ... though there's a risk that this would hide actual data loss
> FileNotFoundException on _temporary directory with Spark Streaming 2.0.1 and
> S3A
>
>
> Key: SPARK-18512
> URL: https://issues.apache.org/jira/browse/SPARK-18512
> Project: Spark
> Issue Type: Bug
> Components: Structured Streaming
>Affects Versions: 2.0.1
> Environment: AWS EMR 5.0.1
> Spark 2.0.1
> S3 EU-West-1 (S3A)
>Reporter: Giuseppe Bonaccorso
>
> After a few hours of streaming processing and data saving in Parquet format,
> I got always this exception:
> {code:java}
> java.io.FileNotFoundException: No such file or directory:
> s3a://xxx/_temporary/0/task_
> at
> org.apache.hadoop.fs.s3a.S3AFileSystem.getFileStatus(S3AFileSystem.java:1004)
> at
> org.apache.hadoop.fs.s3a.S3AFileSystem.listStatus(S3AFileSystem.java:745)
> at
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.mergePaths(FileOutputCommitter.java:426)
> at
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.commitJobInternal(FileOutputCommitter.java:362)
> 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$$anonfun$run$1.apply(InsertIntoHadoopFsRelationCommand.scala:115)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
> at
> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:115)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:60)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:58)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:74)
> at
> org.apache.spark.sql.execution.SparkPlan$$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:510)
> 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)
> {code}
> I've tried also s3:// and s3n:// but it always happens after a 3-5 hours.
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[jira] [Commented] (SPARK-18512) FileNotFoundException on _temporary directory with Spark Streaming 2.0.1 and S3A
[
https://issues.apache.org/jira/browse/SPARK-18512?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15702656#comment-15702656
]
Giuseppe Bonaccorso commented on SPARK-18512:
-
Thanks! I've already set mergeSchema=false, but I gonna add filterPushdown and
mapreduce options.
> FileNotFoundException on _temporary directory with Spark Streaming 2.0.1 and
> S3A
>
>
> Key: SPARK-18512
> URL: https://issues.apache.org/jira/browse/SPARK-18512
> Project: Spark
> Issue Type: Bug
> Components: Structured Streaming
>Affects Versions: 2.0.1
> Environment: AWS EMR 5.0.1
> Spark 2.0.1
> S3 EU-West-1 (S3A with read-after-write consistency)
>Reporter: Giuseppe Bonaccorso
>
> After a few hours of streaming processing and data saving in Parquet format,
> I got always this exception:
> {code:java}
> java.io.FileNotFoundException: No such file or directory:
> s3a://xxx/_temporary/0/task_
> at
> org.apache.hadoop.fs.s3a.S3AFileSystem.getFileStatus(S3AFileSystem.java:1004)
> at
> org.apache.hadoop.fs.s3a.S3AFileSystem.listStatus(S3AFileSystem.java:745)
> at
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.mergePaths(FileOutputCommitter.java:426)
> at
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.commitJobInternal(FileOutputCommitter.java:362)
> 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$$anonfun$run$1.apply(InsertIntoHadoopFsRelationCommand.scala:115)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
> at
> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:115)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:60)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:58)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:74)
> at
> org.apache.spark.sql.execution.SparkPlan$$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:510)
> 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)
> {code}
> I've tried also s3:// and s3n:// but it always happens after a 3-5 hours.
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[jira] [Commented] (SPARK-18512) FileNotFoundException on _temporary directory with Spark Streaming 2.0.1 and S3A
[
https://issues.apache.org/jira/browse/SPARK-18512?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15702394#comment-15702394
]
Giuseppe Bonaccorso commented on SPARK-18512:
-
It happens after about 1.000.000 writings of (100 - 1000 KB).
I've tried your solution writing to HDFS and it works. Unfortunately I cannot
use distcp on the same cluster, because we're working with Spark Streaming. Is
it possible doing it on the same cluster without distcp? Thanks
> FileNotFoundException on _temporary directory with Spark Streaming 2.0.1 and
> S3A
>
>
> Key: SPARK-18512
> URL: https://issues.apache.org/jira/browse/SPARK-18512
> Project: Spark
> Issue Type: Bug
> Components: Structured Streaming
>Affects Versions: 2.0.1
> Environment: AWS EMR 5.0.1
> Spark 2.0.1
> S3 EU-West-1 (S3A with read-after-write consistency)
>Reporter: Giuseppe Bonaccorso
>
> After a few hours of streaming processing and data saving in Parquet format,
> I got always this exception:
> {code:java}
> java.io.FileNotFoundException: No such file or directory:
> s3a://xxx/_temporary/0/task_
> at
> org.apache.hadoop.fs.s3a.S3AFileSystem.getFileStatus(S3AFileSystem.java:1004)
> at
> org.apache.hadoop.fs.s3a.S3AFileSystem.listStatus(S3AFileSystem.java:745)
> at
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.mergePaths(FileOutputCommitter.java:426)
> at
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.commitJobInternal(FileOutputCommitter.java:362)
> 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$$anonfun$run$1.apply(InsertIntoHadoopFsRelationCommand.scala:115)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
> at
> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:115)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:60)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:58)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:74)
> at
> org.apache.spark.sql.execution.SparkPlan$$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:510)
> 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)
> {code}
> I've tried also s3:// and s3n:// but it always happens after a 3-5 hours.
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[jira] [Commented] (SPARK-18512) FileNotFoundException on _temporary directory with Spark Streaming 2.0.1 and S3A
[
https://issues.apache.org/jira/browse/SPARK-18512?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15702373#comment-15702373
]
Steve Loughran commented on SPARK-18512:
one question: what's the size of data being committed here?
> FileNotFoundException on _temporary directory with Spark Streaming 2.0.1 and
> S3A
>
>
> Key: SPARK-18512
> URL: https://issues.apache.org/jira/browse/SPARK-18512
> Project: Spark
> Issue Type: Bug
> Components: Structured Streaming
>Affects Versions: 2.0.1
> Environment: AWS EMR 5.0.1
> Spark 2.0.1
> S3 EU-West-1 (S3A with read-after-write consistency)
>Reporter: Giuseppe Bonaccorso
>
> After a few hours of streaming processing and data saving in Parquet format,
> I got always this exception:
> {code:java}
> java.io.FileNotFoundException: No such file or directory:
> s3a://xxx/_temporary/0/task_
> at
> org.apache.hadoop.fs.s3a.S3AFileSystem.getFileStatus(S3AFileSystem.java:1004)
> at
> org.apache.hadoop.fs.s3a.S3AFileSystem.listStatus(S3AFileSystem.java:745)
> at
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.mergePaths(FileOutputCommitter.java:426)
> at
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.commitJobInternal(FileOutputCommitter.java:362)
> 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$$anonfun$run$1.apply(InsertIntoHadoopFsRelationCommand.scala:115)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
> at
> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:115)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:60)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:58)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:74)
> at
> org.apache.spark.sql.execution.SparkPlan$$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:510)
> 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)
> {code}
> I've tried also s3:// and s3n:// but it always happens after a 3-5 hours.
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[jira] [Commented] (SPARK-18512) FileNotFoundException on _temporary directory with Spark Streaming 2.0.1 and S3A
[
https://issues.apache.org/jira/browse/SPARK-18512?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15702368#comment-15702368
]
Steve Loughran commented on SPARK-18512:
This looks like a consistency problem; s3 listing always lags the
creation/deletion/update of contents.
the committer has listed paths to merge in, then gone through each one to see
their type: if not a file, lists the subdirectory, and, interestingly gets an
exception at this point. Maybe the first listing found an object which is no
longer there by the time the second listing went through, that is, the
exception isn't a delay-on-create, its a delay-on-delete.
create listing delays could be handled in the committer by having a retry on an
FNFE; it'd slighly increase the time before a failure, but as that's a failure
path, not too serious; delete delays could be addressed the opposite: ignore
the problem, on the basis that if the listing failed, there's no file to
rename. That's more worrying as it's a sign of a problem which could have
implications further up the commit process: things are changing in the listing
of files being renamed.
HADOOP-13345 is going to address list inconsistency; I'm doing a committer
there which I could also try to make more robust even when not using a
dynamo-DB backed bucket. Question is: what is the good retry policy here,
especially given once an inconsistency has surfaced, a large amount of the
merge may already have taken place. Backing up and retrying may be differently
dangerous.
One thing I would recommend trying is: commit to HDFS, then copy. Do that and
you can turn speculation on in your executors, get the local Virtual HDD perf
and networking, as well as a consistent view. copy to s3a after all that you
want done is complete.
> FileNotFoundException on _temporary directory with Spark Streaming 2.0.1 and
> S3A
>
>
> Key: SPARK-18512
> URL: https://issues.apache.org/jira/browse/SPARK-18512
> Project: Spark
> Issue Type: Bug
> Components: Structured Streaming
>Affects Versions: 2.0.1
> Environment: AWS EMR 5.0.1
> Spark 2.0.1
> S3 EU-West-1 (S3A with read-after-write consistency)
>Reporter: Giuseppe Bonaccorso
>
> After a few hours of streaming processing and data saving in Parquet format,
> I got always this exception:
> {code:java}
> java.io.FileNotFoundException: No such file or directory:
> s3a://xxx/_temporary/0/task_
> at
> org.apache.hadoop.fs.s3a.S3AFileSystem.getFileStatus(S3AFileSystem.java:1004)
> at
> org.apache.hadoop.fs.s3a.S3AFileSystem.listStatus(S3AFileSystem.java:745)
> at
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.mergePaths(FileOutputCommitter.java:426)
> at
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.commitJobInternal(FileOutputCommitter.java:362)
> 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$$anonfun$run$1.apply(InsertIntoHadoopFsRelationCommand.scala:115)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
> at
> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:115)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:60)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:58)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:74)
> at
> org.apache.spark.sql.execution.SparkPlan$$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
[jira] [Commented] (SPARK-18512) FileNotFoundException on _temporary directory with Spark Streaming 2.0.1 and S3A
[
https://issues.apache.org/jira/browse/SPARK-18512?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15695800#comment-15695800
]
Genmao Yu commented on SPARK-18512:
---
[~giuseppe.bonaccorso] How can i reproduce this failure? Can u provide some
code snippet？
> FileNotFoundException on _temporary directory with Spark Streaming 2.0.1 and
> S3A
>
>
> Key: SPARK-18512
> URL: https://issues.apache.org/jira/browse/SPARK-18512
> Project: Spark
> Issue Type: Bug
> Components: Structured Streaming
>Affects Versions: 2.0.1
> Environment: AWS EMR 5.0.1
> Spark 2.0.1
> S3 EU-West-1 (S3A with read-after-write consistency)
>Reporter: Giuseppe Bonaccorso
>
> After a few hours of streaming processing and data saving in Parquet format,
> I got always this exception:
> {code:java}
> java.io.FileNotFoundException: No such file or directory:
> s3a://xxx/_temporary/0/task_
> at
> org.apache.hadoop.fs.s3a.S3AFileSystem.getFileStatus(S3AFileSystem.java:1004)
> at
> org.apache.hadoop.fs.s3a.S3AFileSystem.listStatus(S3AFileSystem.java:745)
> at
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.mergePaths(FileOutputCommitter.java:426)
> at
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.commitJobInternal(FileOutputCommitter.java:362)
> 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$$anonfun$run$1.apply(InsertIntoHadoopFsRelationCommand.scala:115)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
> at
> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:115)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:60)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:58)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:74)
> at
> org.apache.spark.sql.execution.SparkPlan$$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:510)
> 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)
> {code}
> I've tried also s3:// and s3n:// but it always happens after a 3-5 hours.
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This message was sent by Atlassian JIRA
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[jira] [Commented] (SPARK-18512) FileNotFoundException on _temporary directory with Spark Streaming 2.0.1 and S3A
[
https://issues.apache.org/jira/browse/SPARK-18512?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15686061#comment-15686061
]
Giuseppe Bonaccorso commented on SPARK-18512:
-
No, I didn't. I'm afraid that relaunching a streaming task can cause a loss of
data.
> FileNotFoundException on _temporary directory with Spark Streaming 2.0.1 and
> S3A
>
>
> Key: SPARK-18512
> URL: https://issues.apache.org/jira/browse/SPARK-18512
> Project: Spark
> Issue Type: Bug
> Components: Structured Streaming
>Affects Versions: 2.0.1
> Environment: AWS EMR 5.0.1
> Spark 2.0.1
> S3 EU-West-1 (S3A with read-after-write consistency)
>Reporter: Giuseppe Bonaccorso
>
> After a few hours of streaming processing and data saving in Parquet format,
> I got always this exception:
> {code:java}
> java.io.FileNotFoundException: No such file or directory:
> s3a://xxx/_temporary/0/task_
> at
> org.apache.hadoop.fs.s3a.S3AFileSystem.getFileStatus(S3AFileSystem.java:1004)
> at
> org.apache.hadoop.fs.s3a.S3AFileSystem.listStatus(S3AFileSystem.java:745)
> at
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.mergePaths(FileOutputCommitter.java:426)
> at
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.commitJobInternal(FileOutputCommitter.java:362)
> 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$$anonfun$run$1.apply(InsertIntoHadoopFsRelationCommand.scala:115)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
> at
> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:115)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:60)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:58)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:74)
> at
> org.apache.spark.sql.execution.SparkPlan$$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:510)
> 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)
> {code}
> I've tried also s3:// and s3n:// but it always happens after a 3-5 hours.
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[jira] [Commented] (SPARK-18512) FileNotFoundException on _temporary directory with Spark Streaming 2.0.1 and S3A
[
https://issues.apache.org/jira/browse/SPARK-18512?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15684863#comment-15684863
]
Shixiong Zhu commented on SPARK-18512:
--
Did you enable speculation?
> FileNotFoundException on _temporary directory with Spark Streaming 2.0.1 and
> S3A
>
>
> Key: SPARK-18512
> URL: https://issues.apache.org/jira/browse/SPARK-18512
> Project: Spark
> Issue Type: Bug
> Components: Structured Streaming
>Affects Versions: 2.0.1
> Environment: AWS EMR 5.0.1
> Spark 2.0.1
> S3 EU-West-1 (S3A with read-after-write consistency)
>Reporter: Giuseppe Bonaccorso
>
> After a few hours of streaming processing and data saving in Parquet format,
> I got always this exception:
> {code:java}
> java.io.FileNotFoundException: No such file or directory:
> s3a://xxx/_temporary/0/task_
> at
> org.apache.hadoop.fs.s3a.S3AFileSystem.getFileStatus(S3AFileSystem.java:1004)
> at
> org.apache.hadoop.fs.s3a.S3AFileSystem.listStatus(S3AFileSystem.java:745)
> at
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.mergePaths(FileOutputCommitter.java:426)
> at
> org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.commitJobInternal(FileOutputCommitter.java:362)
> 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$$anonfun$run$1.apply(InsertIntoHadoopFsRelationCommand.scala:115)
> at
> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
> at
> org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:115)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:60)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:58)
> at
> org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:74)
> at
> org.apache.spark.sql.execution.SparkPlan$$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:510)
> 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)
> {code}
> I've tried also s3:// and s3n:// but it always happens after a 3-5 hours.
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