cody5514 opened a new issue #13779:
URL: https://github.com/apache/airflow/issues/13779


   **Apache Airflow version**: 1.10.10
   
   
   **Kubernetes version (if you are using kubernetes)** (use `kubectl version`):
   
   **Environment**: composer
   
   - **Cloud provider or hardware configuration**: gcp
   - **OS** (e.g. from /etc/os-release):
   - **Kernel** (e.g. `uname -a`):
   - **Install tools**:
   - **Others**:
   
   **What happened**:
   
   Seems to be a code issue.
   
[**CloudDataFusionStartPipelineOperator**](https://github.com/apache/airflow/blob/18d9320c2619dc569485a29fc71a62c26d29b3c9/airflow/providers/google/cloud/operators/datafusion.py#L847-L863)
 calls the 
[**start_pipeline**](https://github.com/apache/airflow/blob/18d9320c2619dc569485a29fc71a62c26d29b3c9/airflow/providers/google/cloud/hooks/datafusion.py#L427)
 hook before checking for **success_states** and calling the 
**wait_for_pipeline_state** hook.  If the pipeline takes more than 5 mins to 
run (default for the **wait_for_pipeline_state** hook) then the operator never 
checks for **success_states** because the **start_pipeline** hook [also calls 
the **wait_for_pipeline_state** 
hook](https://github.com/apache/airflow/blob/18d9320c2619dc569485a29fc71a62c26d29b3c9/airflow/providers/google/cloud/hooks/datafusion.py#L473-L479).
   
   So the **start_pipeline** hook calling of **wait_for_pipeline_state** 
supersedes the **CloudDataFusionStartPipelineOperator** if the pipeline takes 
longer than 5 mins to enter a RUNNING state.
   
   **What you expected to happen**:
   
   It's a code issue.  I expect that if I provide **success_states** and 
**pipeline_timeout** parameters to the data fusion operator for those 
parameters to change the success states and timeout parameters for the DAG.
   
   **How to reproduce it**:
   Run the operator with success_states and pipeline_timeout parameters on a 
pipeline that takes more than 5 mins to start RUNNING.
   
   
   **Anything else we need to know**:
   
   
   


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