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Status
Current state: Under Discussion
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Please keep the discussion on the mailing list rather than commenting on the wiki (wiki discussions get unwieldy fast).
Motivation
In highly-available setups with multiple masters, we need a component that provides the newly elected leader with the current state of a job that it’s trying to recover. We already have the first version of this component, the RunningJobsRegistry
(RJR), that has several limitations we want to address in this FLIP.
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Another limitation is that RJR does not provide access to the JobResult
of a completed job, so we may need to return the UNKNOWN
result, when we failover in application mode (FLINK-21928). Having access to a JobResult
, after the job has completed, would also pave the road for supporting multi-stage jobs in ApplicationMode
and highly available job drivers in general.
Public Interfaces
Briefly list any new interfaces that will be introduced as part of this proposal or any existing interfaces that will be removed or changed. The purpose of this section is to concisely call out the public contract that will come along with this feature.
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Binary log formatThe network protocol and api behaviorAny class in the public packages under clientsConfiguration, especially client configurationorg/apache/kafka/common/serializationorg/apache/kafka/commonorg/apache/kafka/common/errorsorg/apache/kafka/clients/producerorg/apache/kafka/clients/consumer (eventually, once stable)
MonitoringCommand line tools and argumentsAnything else that will likely break existing users in some way when they upgrade
Proposed Changes
In this document we propose removing RJR and introducing a new opt-in component, the JobResultStore (JSR).
JobId semantics
For the purpose of this FLIP and the future work on the ApplicationMode, we need to re-define the JobId semantics to meet the following properties.
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We don’t need any changes to interfaces around JobID as we can simply use ClusterId as a JobResultStore namespace.
JobResultStore
JobResultStore (JRS) is the successor to RJR, which is able to outlive a concrete job in order to solve recovery issues in multi-master setups. The idea of the JobResultStore
is to persist information about successfully completed jobs that is under the control of a 3rd party. The cleanup of the information stored in the JRS, is the responsibility of the 3rd party (e.g. after the Flink cluster has been fully stopped).
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- Access to the
JobResult
of a globally terminated job (especially useful for highly-available job drivers). JobResult
is initially marked as dirty and needs to be committed after resource cleanup.- Ensure that we don’t restart jobs that have already been completed.
Atomic cleanup of job resources
In multi-master setups, we need to cleanup following resources after the job finishes:
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For a client accessing the job result we could think of providing the actual job's result since the actual computation is done even with the job still being in the cleanup phase.
Recovery workflow
draw.io Diagram | ||||||||||||||||||||
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Cleanup (Draft)
Currently, the different artifacts are cleaned up in different locations:
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The plan is to unite the cleanup logic in a single component that is, i.e. the Dispatcher, as it is also the component being in charge of accessing the JobResultStore
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Implementation
Interface
Compatibility, Deprecation, and Migration Plan
- What impact (if any) will there be on existing users?
- If we are changing behavior how will we phase out the older behavior?
- If we need special migration tools, describe them here.
- When will we remove the existing behavior?
Test Plan
Describe in few sentences how the FLIP will be tested. We are mostly interested in system tests (since unit-tests are specific to implementation details). How will we know that the implementation works as expected? How will we know nothing broke?
Rejected Alternatives
If there are alternative ways of accomplishing the same thing, what were they? The purpose of this section is to motivate why the design is the way it is and not some other way.