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How does retry_exponential_backoff work in Airflow tasks?

How do the parameters retries, retry_delay and retry_exponential_backoff interact? When there is a retry, when is it scheduled? Exponential backoff sounds interesting, but how does it work?

e.g. what happens with these parameters? When are the retries scheduled?

retries=3,
retry_delay=300,
retry_exponential_backoff=True
Solution

  • The code for understanding how Airflow implements exponential backoff can be found in airflow/models/taskinstance.py (link). Exponential backoff will double the wait time between retries after every retry.

    Here are some examples of different wait intervals between retries to illustrate how long the scheduler will wait to re-schedule a task for a retry:

    retries retry_delay retry_exponential_backoff number of seconds to 1st retry NoSt 2nd retry NoSt 3rd retry
    3 60 True 60 120 240
    3 60 False 60 60 60
    1 120 True 120 N/A N/A
    1 120 False 120 N/A N/A
    3 300 True 300 600 1200
    3 300 False 300 300 300