ferruzzi commented on code in PR #55088:
URL: https://github.com/apache/airflow/pull/55088#discussion_r2356878935
##########
airflow-core/docs/howto/deadline-alerts.rst:
##########
@@ -97,6 +100,55 @@ Airflow provides several built-in reference points that you
can use with Deadlin
``DeadlineReference.FIXED_DATETIME``
Specifies a fixed point in time. Useful when Dags must complete by a
specific time.
+``DeadlineReference.AVERAGE_RUNTIME``
+ Calculates deadlines based on the average runtime of previous DAG runs.
This reference
+ analyzes historical execution data to predict when the current run should
complete.
+ The deadline is set to the current time plus the calculated average
runtime plus the interval.
+ If insufficient historical data exists, no deadline is created.
+
+ Parameters:
+ * ``limit`` (int, optional): Maximum number of recent DAG runs to
analyze. Defaults to 10.
+ * ``min_runs`` (int, optional): Minimum number of completed runs
required to calculate average. Defaults to same value as ``limit``.
+
+ Example usage:
+
+ .. code-block:: python
+
+ # Use default settings (analyze up to 10 runs, require 10 runs)
+ DeadlineReference.AVERAGE_RUNTIME()
+
+ # Analyze up to 20 runs but calculate with minimum 5 runs
+ DeadlineReference.AVERAGE_RUNTIME(limit=20, min_runs=5)
+
+ # Strict: require exactly 15 runs to calculate
+ DeadlineReference.AVERAGE_RUNTIME(limit=15, min_runs=15)
+
+Here's an example using average runtime:
+
+.. code-block:: python
+
+ with DAG(
+ dag_id="average_runtime_deadline",
+ deadline=DeadlineAlert(
+ reference=DeadlineReference.AVERAGE_RUNTIME(limit=15, min_runs=5),
+ interval=timedelta(minutes=30), # Alert if 30 minutes past
expected completion
Review Comment:
Ah, yup, something got weird there. I think the above example can be moved
down to replace this one.
##########
airflow-core/docs/howto/deadline-alerts.rst:
##########
@@ -97,6 +100,55 @@ Airflow provides several built-in reference points that you
can use with Deadlin
``DeadlineReference.FIXED_DATETIME``
Specifies a fixed point in time. Useful when Dags must complete by a
specific time.
+``DeadlineReference.AVERAGE_RUNTIME``
+ Calculates deadlines based on the average runtime of previous DAG runs.
This reference
+ analyzes historical execution data to predict when the current run should
complete.
+ The deadline is set to the current time plus the calculated average
runtime plus the interval.
+ If insufficient historical data exists, no deadline is created.
+
+ Parameters:
+ * ``limit`` (int, optional): Maximum number of recent DAG runs to
analyze. Defaults to 10.
+ * ``min_runs`` (int, optional): Minimum number of completed runs
required to calculate average. Defaults to same value as ``limit``.
+
+ Example usage:
+
+ .. code-block:: python
+
+ # Use default settings (analyze up to 10 runs, require 10 runs)
+ DeadlineReference.AVERAGE_RUNTIME()
+
+ # Analyze up to 20 runs but calculate with minimum 5 runs
+ DeadlineReference.AVERAGE_RUNTIME(limit=20, min_runs=5)
+
+ # Strict: require exactly 15 runs to calculate
+ DeadlineReference.AVERAGE_RUNTIME(limit=15, min_runs=15)
+
+Here's an example using average runtime:
+
+.. code-block:: python
+
+ with DAG(
+ dag_id="average_runtime_deadline",
+ deadline=DeadlineAlert(
+ reference=DeadlineReference.AVERAGE_RUNTIME(limit=15, min_runs=5),
+ interval=timedelta(minutes=30), # Alert if 30 minutes past
expected completion
Review Comment:
Ah, yup, something got weird there. I think the above example can be moved
down to replace this one.
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