prevent timeout fetch daily maximo

dags/fetch_maximo_daily.py

@@ -3,16 +3,51 @@ import requests
 import json
 import uuid
 import logging
+import time
 
 from airflow import DAG
-from airflow.operators.python import PythonOperator
+from airflow.operators.python import PythonOperator, BranchPythonOperator
+from airflow.operators.trigger_dagrun import TriggerDagRunOperator
+from airflow.operators.dummy import DummyOperator
 from airflow.utils.dates import days_ago
+from airflow.models import Variable, DagRun
+from airflow.utils.session import create_session
+from airflow.utils.state import State
 
 # Configure logging
 logger = logging.getLogger(__name__)
 
 
-def fetch_maximo_data(**context):
+def is_dag_already_running(**context):
+    """
+    Check if there are other active DAG runs to prevent duplicate execution
+    """
+    dag_id = context["dag"].dag_id
+    run_id = context["run_id"]
+
+    with create_session() as session:
+        # Count running instances of this DAG excluding the current run
+        running_dags = (
+            session.query(DagRun)
+            .filter(
+                DagRun.dag_id == dag_id,
+                DagRun.run_id != run_id,
+                DagRun.state == State.RUNNING,
+            )
+            .count()
+        )
+
+    if running_dags > 0:
+        logger.info(
+            f"Found {running_dags} other running instance(s) of this DAG. Skipping execution."
+        )
+        return "skip_execution"
+    else:
+        logger.info("No other running instances found. Proceeding with execution.")
+        return "fetch_daily_maximo_data"
+
+
+def fetch_daily_maximo_data(**context):
     """
     Fetch data from the Maximo endpoint using GET method and process the response
     """
@@ -38,7 +73,7 @@ def fetch_maximo_data(**context):
         response = requests.get(
             url=fetch_url,
             headers=headers,
-            timeout=420,  # Increased timeout to 7 minutes (420 seconds)
+            timeout=60,  # Increased timeout to 60 seconds
         )
 
         logger.info(
@@ -90,6 +125,24 @@ def fetch_maximo_data(**context):
         }
 
 
+def process_response(**context):
+    """
+    Process the response from the Maximo API
+    """
+    ti = context["ti"]
+    result = ti.xcom_pull(task_ids="fetch_daily_maximo_data", key="fetch_result")
+
+    if result:
+        logger.info(f"Processing result: {result}")
+        # Add any additional processing logic here
+
+        # Sleep for a short time to simulate processing
+        time.sleep(2)
+
+        return True
+    return False
+
+
 # Define default arguments for the DAG
 default_args = {
     "owner": "airflow",
@@ -108,14 +161,40 @@ dag = DAG(
     # Schedule to run daily at 21:00, 22:00, and 23:00
     schedule_interval="0 21-23 * * *",
     start_date=days_ago(1),
-    tags=["maximo", "api", "fetch"],
+    tags=["maximo", "api", "fetch", "continuous", "daily"],
     catchup=False,
 )
 
+# Branch operator to check if we should proceed or skip
+check_running = BranchPythonOperator(
+    task_id="check_if_already_running",
+    python_callable=is_dag_already_running,
+    provide_context=True,
+    dag=dag,
+)
+
+# Skip execution dummy task
+skip_execution = DummyOperator(
+    task_id="skip_execution",
+    dag=dag,
+)
+
 # Define the task to fetch data from Maximo using PythonOperator
 fetch_task = PythonOperator(
-    task_id="fetch_maximo_data",
-    python_callable=fetch_maximo_data,
+    task_id="fetch_daily_maximo_data",
+    python_callable=fetch_daily_maximo_data,
     provide_context=True,
     dag=dag,
 )
+
+# Define task to process the response
+process_task = PythonOperator(
+    task_id="process_response",
+    python_callable=process_response,
+    provide_context=True,
+    dag=dag,
+)
+
+# Set task dependencies
+check_running >> [skip_execution, fetch_task]
+fetch_task >> process_task