You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@flink.apache.org by "Matthias (Jira)" <ji...@apache.org> on 2021/01/15 11:27:00 UTC

[jira] [Updated] (FLINK-17464) Stanalone HA Cluster crash with non-recoverable cluster state - need to wipe cluster to recover service

     [ https://issues.apache.org/jira/browse/FLINK-17464?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Matthias updated FLINK-17464:
-----------------------------
    Affects Version/s: 1.12.0
                       1.11.3

> Stanalone HA Cluster crash with non-recoverable cluster state - need to wipe cluster to recover service
> -------------------------------------------------------------------------------------------------------
>
>                 Key: FLINK-17464
>                 URL: https://issues.apache.org/jira/browse/FLINK-17464
>             Project: Flink
>          Issue Type: Bug
>          Components: Runtime / Coordination
>    Affects Versions: 1.10.0, 1.12.0, 1.11.3
>            Reporter: John Lonergan
>            Priority: Critical
>
> When recovering job graphs after a failover of the JobManager, or after a restart of the cluster, the HA Cluster can get into a state where it cannot be restarted and the only resoluton we have identified is to destroy the Zookkeeper job graph store.
> This happens when any job graph that is being recovered throws an exception during recovery on the master. 
> Whilst we encountered this issues on a sink that extends "InitialiseOnMaster" we believe the vulnerability is generic in nature and the unrecolverable problems encountered will occur if the application code throws any exception for any reason during recovery on the main line. 
> These application exceptions propagate up to the JobManager ClusterEntryPoint class at which point the JM leader does a system.exit. If there are remaining JobManagers then they will also follow leader election and also encounter the same sequence of events. Ultimately all JM's exit and then all TM's fail also. 
> The entire cluster is destroyed.
> Because these events happen during job graph recovery then merely attempt a restart of the cluster will fail leaving the only option as destroying the job graph state. 
> If one is running a shared cluster with many jobs then this is effectively a DOS and results in prolonged down time as code or data changes are necessary to work around the issue.
> --
> Of course if the same exception were to be thrown during job submission using the CLI, then we would not see the cluster crashing nor the cluster being corrupted; the job would merely fail.
> Our feeling is that the job graph recovery process ought to behave in a similar fashion to the job submission processes.
> If a job submission fails then the job is recorded as failed and there is no further impact on the cluster. However, if job recovery fails then the entire cluster is taken down, and may as we have seen, become inoperable.
> We feel that a failure to restore a single job graph ought merely to result in the job being recorded as failed. It should not result in a cluster-wide impact.
> We do not understand the logic of the design in this space. However, if the existing logic was for the benefit of single job clusters then this is a poor result for multi job clusters. In which case we ought to be able to configure a cluster for "multi-job mode" so that job graph recovery is "sandboxed"  and doesn't take out the entire cluster.
> ---
> It is easy to demonstrate the problem using the built in Flink streaming Word Count example.
> In order for this to work you configure the job to write a single output file and also write this to HDFS not to a local disk. 
> You will note that the class FileOutputFormat extends InitializeOnMaster and the initializeGlobal() function executes only when the file is on HDFS, not on local disk.
> When this functon runs it will generate an exception if the output already exists.
> Therefore to demonstrate the issues do the following:
> - configure the job to write a single file to HDFS
> - configure the job to to read a large file so that the job takes some time to execute and we have time to complete the next few steps bnefore the job finishes.
> - run the job on a HA cluster with two JM nodes
> - wait for the job to start and the output file to be created
> - kill the leader JM before the job has finished 
> - observe JM failover occuring ... 
> - recovery during failover will NOT suceed because the recovery of the Word Count job will fail due to the presence of the output file
> - observe all JM's and TM's ultimately terminating
> Once the cluster has outright failed then try and restart it.
> During restart the cluster will detect the presence of job graphs in Zk and attempt to restore them. This however, is doomed due to the same vulnerability that causes the global outage above.
> -------
> For operability Flink needs a mod such that the job graph recovery process is entirely sandboxed and failure of a given job during job graph recovery ought to result merely in a failed job and not a failed cluster.



--
This message was sent by Atlassian Jira
(v8.3.4#803005)