When retrying microbatch models, propagate prior successful state #10802
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QMalcolm
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ChenyuLInx
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| @@ -454,7 +454,7 @@ def resource_class(cls) -> Type[HookNodeResource]: | |||
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| @dataclass | |||
| class ModelNode(ModelResource, CompiledNode): | |||
| batches: Optional[List[BatchType]] = None | |||
| batch_info: Optional[BatchResults] = None | |||
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Will this cause a loading error for a previous manifest?
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This has no effect on the written manifest, which is intentional. That is the case because these do not exist on the artifact class for the object
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Resolves #10800
Problem
If you invoked
dbt retryon a microbatch model twice, where on the firstdbt retryall the retried batches failed, then on the seconddbt retryinvocation the microbatch model would rerun all the batches that were run on the initialdbt runbeing retried.Solution
When going through multiple
dbt retryinvocations, ensure that the priorsuccessfulbatch information continues to be passed.Checklist