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https://issues.apache.org/jira/browse/BEAM-8539?focusedWorklogId=337543&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-337543
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ASF GitHub Bot logged work on BEAM-8539:
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Author: ASF GitHub Bot
Created on: 01/Nov/19 20:28
Start Date: 01/Nov/19 20:28
Worklog Time Spent: 10m
Work Description: lukecwik commented on pull request #9969: [BEAM-8539]
Provide an initial definition of all job states and the state transition diagram
URL: https://github.com/apache/beam/pull/9969#discussion_r341739058
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File path: model/job-management/src/main/proto/beam_job_api.proto
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@@ -201,6 +201,16 @@ message JobMessagesResponse {
}
// Enumeration of all JobStates
+//
+// The state transition diagram is:
+// STOPPED -> STARTING -> RUNNING -> DONE
+// \> FAILED
+// \> CANCELLING -> CANCELLED
+// \> UPDATING -> UPDATED
+// \> DRAINING -> DRAINED
Review comment:
Yeah, this is the problem with UPDATED since it is dependent on the
implementation within the Runner. Is an UPDATED job the same job as the prior
one or a new job which continues from the prior state? In Dataflow it is the
latter but the former can make sense for other runners.
Not sure of any RUNNING -> STOPPED scenarios today but adding
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Issue Time Tracking
-------------------
Worklog Id: (was: 337543)
Time Spent: 1h (was: 50m)
> Clearly define the valid job state transitions
> ----------------------------------------------
>
> Key: BEAM-8539
> URL: https://issues.apache.org/jira/browse/BEAM-8539
> Project: Beam
> Issue Type: Improvement
> Components: beam-model, runner-core, sdk-java-core, sdk-py-core
> Reporter: Chad Dombrova
> Priority: Major
> Time Spent: 1h
> Remaining Estimate: 0h
>
> The Beam job state transitions are ill-defined, which is big problem for
> anything that relies on the values coming from JobAPI.GetStateStream.
> I was hoping to find something like a state transition diagram in the docs so
> that I could determine the start state, the terminal states, and the valid
> transitions, but I could not find this. The code reveals that the SDKs differ
> on the fundamentals:
> Java InMemoryJobService:
> * start state: *STOPPED*
> * run - about to submit to executor: STARTING
> * run - actually running on executor: RUNNING
> * terminal states: DONE, FAILED, CANCELLED, DRAINED
> Python AbstractJobServiceServicer / LocalJobServicer:
> * start state: STARTING
> * terminal states: DONE, FAILED, CANCELLED, *STOPPED*
> I think it would be good to make python work like Java, so that there is a
> difference in state between a job that has been prepared and one that has
> additionally been run.
> It's hard to tell how far this problem has spread within the various runners.
> I think a simple thing that can be done to help standardize behavior is to
> implement the terminal states as an enum in the beam_job_api.proto, or create
> a utility function in each language for checking if a state is terminal, so
> that it's not left up to each runner to reimplement this logic.
>
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