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https://issues.apache.org/jira/browse/FLINK-32241?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17741662#comment-17741662
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Alexis Sarda-Espinosa edited comment on FLINK-32241 at 7/10/23 3:27 PM:
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[I am seeing this same issue without standby
JMs|https://lists.apache.org/thread/24228yww7bz5kskx5zkjt1fwkvh47dqs], at some
point the JM pod restarts and then all checkpoints and savepoints fail even if
I restart all JM and TM pods manually.
[~_anton] where did you set {{fs.azure.data.blocks.buffer}}? Does Flink forward
it if I place that in {{flink-conf.yaml}}?
EDIT: [found the
answer|https://nightlies.apache.org/flink/flink-docs-release-1.17/docs/deployment/filesystems/azure/#wasb],
yes it does.
was (Author: asardaes):
[I am seeing this same issue without standby
JMs|https://lists.apache.org/thread/24228yww7bz5kskx5zkjt1fwkvh47dqs], at some
point the JM pod restarts and then all checkpoints and savepoints fail even if
I restart all JM and TM pods manually.
[~_anton] where did you set {{fs.azure.data.blocks.buffer}}? Does Flink forward
it if I place that in {{flink-conf.yaml}}?
> UnsupportedFileSystemException when using the ABFS Hadoop driver for
> checkpointing in Flink 1.17
> ------------------------------------------------------------------------------------------------
>
> Key: FLINK-32241
> URL: https://issues.apache.org/jira/browse/FLINK-32241
> Project: Flink
> Issue Type: Bug
> Components: FileSystems, Runtime / Checkpointing
> Affects Versions: 1.17.0, 1.17.1
> Environment: Flink 1.17.1
> Hadoop 3.3.4
> Flink Operator 1.4.0
> Kubernetes 1.24
> Reporter: Anton Ippolitov
> Priority: Minor
>
> https://issues.apache.org/jira/browse/HADOOP-18707 introduced a new
> functionality in the ABFS Hadoop client which buffers data on local disk by
> default.
> It looks like this breaks with Flink 1.17 in a scenario where:
> * ABFS is used for checkpointing
> * JobManager HA is enabled
> * First JobManager leader dies and a stand-by JobManager takes over
> I can reliably reproduce this with Flink 1.17.1 running on Kubernetes by
> simply killing the JM leader pod. Once the stand-by JobManager takes over,
> all checkpoints consistently fail with the following error:
> {noformat}
> org.apache.flink.runtime.checkpoint.CheckpointException: Failure to finalize
> checkpoint. at
> org.apache.flink.runtime.checkpoint.CheckpointCoordinator.finalizeCheckpoint(CheckpointCoordinator.java:1424)
> at
> org.apache.flink.runtime.checkpoint.CheckpointCoordinator.completePendingCheckpoint(CheckpointCoordinator.java:1310)
> at
> org.apache.flink.runtime.checkpoint.CheckpointCoordinator.receiveAcknowledgeMessage(CheckpointCoordinator.java:1202)
> at
> org.apache.flink.runtime.scheduler.ExecutionGraphHandler.lambda$acknowledgeCheckpoint$1(ExecutionGraphHandler.java:89)
> at
> org.apache.flink.runtime.scheduler.ExecutionGraphHandler.lambda$processCheckpointCoordinatorMessage$3(ExecutionGraphHandler.java:119)
> at
> java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
> at
> java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
> at java.base/java.lang.Thread.run(Thread.java:829) Caused by:
> org.apache.hadoop.fs.UnsupportedFileSystemException: No FileSystem for scheme
> "file" at
> org.apache.hadoop.fs.FileSystem.getFileSystemClass(FileSystem.java:3443) at
> org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:3466) at
> org.apache.hadoop.fs.FileSystem.access$300(FileSystem.java:174) at
> org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:3574) at
> org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:3521) at
> org.apache.hadoop.fs.FileSystem.get(FileSystem.java:540) at
> org.apache.hadoop.fs.FileSystem.getLocal(FileSystem.java:496) at
> org.apache.hadoop.fs.LocalDirAllocator$AllocatorPerContext.confChanged(LocalDirAllocator.java:316)
> at
> org.apache.hadoop.fs.LocalDirAllocator$AllocatorPerContext.getLocalPathForWrite(LocalDirAllocator.java:393)
> at
> org.apache.hadoop.fs.LocalDirAllocator.getLocalPathForWrite(LocalDirAllocator.java:165)
> at
> org.apache.hadoop.fs.LocalDirAllocator.getLocalPathForWrite(LocalDirAllocator.java:146)
> at
> org.apache.hadoop.fs.store.DataBlocks$DiskBlockFactory.createTmpFileForWrite(DataBlocks.java:980)
> at
> org.apache.hadoop.fs.store.DataBlocks$DiskBlockFactory.create(DataBlocks.java:960)
> at
> org.apache.hadoop.fs.azurebfs.services.AbfsOutputStream.createBlockIfNeeded(AbfsOutputStream.java:262)
> at
> org.apache.hadoop.fs.azurebfs.services.AbfsOutputStream.<init>(AbfsOutputStream.java:173)
> at
> org.apache.hadoop.fs.azurebfs.AzureBlobFileSystemStore.createFile(AzureBlobFileSystemStore.java:580)
> at
> org.apache.hadoop.fs.azurebfs.AzureBlobFileSystem.create(AzureBlobFileSystem.java:301)
> at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:1195) at
> org.apache.hadoop.fs.FileSystem.create(FileSystem.java:1175) at
> org.apache.hadoop.fs.FileSystem.create(FileSystem.java:1064) at
> org.apache.flink.fs.azure.common.hadoop.HadoopFileSystem.create(HadoopFileSystem.java:154)
> at
> org.apache.flink.fs.azure.common.hadoop.HadoopFileSystem.create(HadoopFileSystem.java:37)
> at
> org.apache.flink.core.fs.PluginFileSystemFactory$ClassLoaderFixingFileSystem.create(PluginFileSystemFactory.java:170)
> at
> org.apache.flink.runtime.state.filesystem.FSDataOutputStreamWrapper.<init>(FSDataOutputStreamWrapper.java:42)
> at
> org.apache.flink.runtime.state.filesystem.FsCheckpointMetadataOutputStream.getOutputStreamWrapper(FsCheckpointMetadataOutputStream.java:179)
> at
> org.apache.flink.runtime.state.filesystem.FsCheckpointMetadataOutputStream.<init>(FsCheckpointMetadataOutputStream.java:64)
> at
> org.apache.flink.runtime.state.filesystem.FsCheckpointStorageLocation.createMetadataOutputStream(FsCheckpointStorageLocation.java:116)
> at
> org.apache.flink.runtime.checkpoint.PendingCheckpoint.finalizeCheckpoint(PendingCheckpoint.java:330)
> at
> org.apache.flink.runtime.checkpoint.CheckpointCoordinator.finalizeCheckpoint(CheckpointCoordinator.java:1410)
> ... 7 common frames omitted{noformat}
> I am not exactly sure why this works with the first JM and why all of a
> sudden the local Hadoop FS implementation cannot be loaded on a stand-by
> JM... I am running with default settings when it comes to Hadoop FS etc.
> Anyway, I found a workaround thanks to
> https://issues.apache.org/jira/browse/SPARK-43188: simply setting
> {{fs.azure.data.blocks.buffer}} to {{array}} seems to solve the issue. So
> this is minor priority.
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