Comments (3)
I don't think we have an option to add "trigger_rule" Airflow configuration in only one TFX component. Similar #498 feature request can help you use-case but it's still a work in progress. I would request you to close this issue and follow similar thread for updates on the feature implementation. Thank you!
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This issue has been marked stale because it has no recent activity since 7 days. It will be closed if no further activity occurs. Thank you.
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This issue was closed due to lack of activity after being marked stale for past 7 days.
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Related Issues (20)
- tfx.components.Transform returns invalid results however outside of the tfx the results are correct. HOT 1
- TFX.components.transform id HOT 4
- Cannot submit a custom training job to a VAI Persistent Resource HOT 13
- BigQueryExampleGen failing in InteractiveContext on 1.14.0 HOT 7
- tfx pipeline compile --engine=vertex fails in 1.14.0 HOT 3
- TFX pipeline Local orchestrator documentation site contains several errors/exceptions HOT 8
- TFX 1.14 docker image pip broken HOT 11
- Allow List of Lists and SequenceExample in dict_to_example HOT 3
- loosening google-cloud-* package constraints for TFX 1.13 HOT 10
- TFX1.14.0 causing Google Cloud Dataflow jobs to fail HOT 27
- Slow parquet to TFRecord using parquet_executor.Executor HOT 3
- StatisticsGen treats zeros as missing data after FileBasedExampleGen with parquet_executor HOT 1
- [Request] Update to Apache Beam 2.52.0, enable Beam 2.46.0 compatibility HOT 5
- Error executing pip install tfx in new conda environment with python 3.10 HOT 6
- installing tfx 1.13.0 by pip takes so much time HOT 5
- TFX trainer component running in Kubeflow fails although it was successful in the Interactive Context HOT 8
- TFX components in GCP does not display component logs in GCP Vertex AI HOT 17
- DataFlow Job in TFX pipeline fails after running for an hour HOT 6
- TFX component never completes even though Vertex AI custom job succeeds / fails HOT 8
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