pmercatoris opened a new issue, #29339:
URL: https://github.com/apache/airflow/issues/29339

   ### Apache Airflow version
   
   2.5.1
   
   ### What happened
   
   I am trying to map a task group within another task group which is already 
mapped. However, when launching the dag, all tasks of the containing task group 
successfully finish. 
   However, the following occurs:  
   
   - The contained task group is not mapped and has a state of  `upstream 
failed`. 
   
![image](https://user-images.githubusercontent.com/8655813/216397932-b07c623b-f3ca-45c5-8a52-6bd7911fe538.png)
   
![image](https://user-images.githubusercontent.com/8655813/216398586-6f8ebb2b-6b99-4df5-898e-1356c66f73be.png)
   
   - The graph UI doesn't show after launching the dag as in 
https://github.com/apache/airflow/issues/29287 
   
![image](https://user-images.githubusercontent.com/8655813/216398113-767abd6a-07e6-499b-8f59-4316f9edd695.png)
   
   
   ### What you think should happen instead
   
   I would expect the print_group and print task to start as soon as 1 of the 
load task finishes
   
   ### How to reproduce
   
   I am currently using the docker-compose of the version 2.5.1
   `FROM apache/airflow:2.5.1-python3.10`
   
   ```python
   import pendulum
   from airflow.decorators import dag, task, task_group
   
   @task
   def get_symbols():
       res = [('A', 1, 111), ('B', 2, 222)]
       return res
   
   
   @task
   def print(symbol_info, data_interval_end=None):
       # Do some work...
       print(symbol_info)
       return symbol_info
   
   @task_group()
   def print_group(symbol):
       return print(symbol_info=symbol)
   
   
   @task
   def extract(symbol_info, data_interval_end=None):
       # Do some work...
       return symbol_info
   @task
   def transform(symbol_info, data_interval_end=None):
       # Do some work...
       return symbol_info
   
   @task
   def load(symbol_info, data_interval_end=None):
       # Do some work...
       return 2*[symbol_info]
   
   @task_group
   def etl_tg(symbol):
       raw_symbols_data = extract(symbol_info=symbol)
       clean_symbols_data = transform(symbol_info=raw_symbols_data)
       loaded_symbols = load(symbol_info=clean_symbols_data)
       return print_group.expand(symbol=loaded_symbols)
   
   @dag(
       dag_id=f"task_group_mapping_2",
       tags=["sandbox"],
       schedule=None,
       start_date=pendulum.datetime(2023, 1, 1, tz="UTC"),
       catchup=False,
       max_active_runs=1,
   )
   def etl_dag():
   
       # DAG
       symbols = get_symbols()
       etl_tg.expand(symbol=symbols)
   
   etl_dag() 
   ```
   
   ### Operating System
   
   Ubuntu 20.04.5 LTS
   
   ### Versions of Apache Airflow Providers
   
   _No response_
   
   ### Deployment
   
   Docker-Compose
   
   ### Deployment details
   
   _No response_
   
   ### Anything else
   
   _No response_
   
   ### Are you willing to submit PR?
   
   - [ ] Yes I am willing to submit a PR!
   
   ### Code of Conduct
   
   - [X] I agree to follow this project's [Code of 
Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)
   


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