datax-admin/app/core/airflow/templates/dag_template.py.jinja2

from airflow import DAG
from datetime import datetime
from airflow.operators.empty import EmptyOperator
from airflow.providers.cncf.kubernetes.operators.kubernetes_pod import KubernetesPodOperator
from airflow.configuration import conf
from airflow.utils.task_group import TaskGroup
import requests

job_id = {{ job_id }}

def task_finish_alert(context):
    print('############### task begin callback!###################')
    url = 'http://192.168.199.109:18082/jpt/af_run/notification'
    ti = context['ti']
    requests.post(url, json={"data": {
        "job_id": job_id,
        "dag_id": ti.dag_id,
        "task_id": ti.task.task_id,
        "run_ts": ti.execution_date.strftime('%Y%m%dT%H%M%S'),
        "start_time": ti.start_date.timestamp(),
        "end_time": ti.end_date.timestamp(),
        "status": ti.current_state()
    }})


def dag_begin_alert(context):
    print('############### dag begin callback!###################')
    url = 'http://192.168.199.109:18082/jpt/af_run'
    ti = context['ti']
    requests.post(url, json={"data": {
        "job_id": job_id,
        "dag_id": ti.dag_id,
        "task_id": ti.task.task_id,
        "run_ts": ti.execution_date.strftime('%Y%m%dT%H%M%S'),
        "start_time": ti.start_date.timestamp(),
        "end_time": ti.end_date.timestamp(),
        "status": ti.current_state()
    }})

print('enter dag run!')
namespace = conf.get("kubernetes", "NAMESPACE")


# set the name that will be printed
name = "dag_user{{ user_name }}"

# instantiate the DAG
with DAG(start_date=datetime(2022,6,1),catchup=False,schedule_interval='@daily',dag_id="{{ dag_id }}",is_paused_upon_creation= not {{ trigger_status }}) as dag:
    op_start = EmptyOperator(task_id='start', on_success_callback=dag_begin_alert)

    {% for spark_node in spark_nodes %}
    with TaskGroup("{{ spark_node['name'] }}", prefix_group_id=False, tooltip="{{ spark_node['desc'] }}") as op_{{ spark_node['id'] }}:
    {% for spark_sub_node in spark_node['sub_nodes'] %}
        op_{{ spark_sub_node['id'] }} = KubernetesPodOperator(
                                                                    task_id="{{ spark_sub_node["id"] }}",
                                                                    image="{{ spark_sub_node['image'] }}",
                                                                    in_cluster=True,
                                                                    namespace=namespace,
                                                                    name="{{ spark_sub_node['name'] }}",
                                                                    random_name_suffix=True,
                                                                    labels={'app':'backend', 'env':'dev', 'run_ts':{{ "'{{ ts_nodash }}'" }} },
                                                                    reattach_on_restart=True,
                                                                    is_delete_operator_pod=False,
                                                                    get_logs=True,
                                                                    log_events_on_failure=True,
                                                                    cmds={{ spark_sub_node['cmds'] }},
                                                                    env_vars={{ spark_sub_node['env'] }},
                                                                    on_success_callback=task_finish_alert,
                                                                    on_failure_callback=task_finish_alert
                                                                    )
    {% endfor %}
        {% for edge in spark_node['edges'] %}
        op_{{edge[0] }} >>  op_{{edge[1] }}
        {% endfor %}
    {% endfor %}



    {% for node in nodes %}
    {{ node['operator_name'] }} = KubernetesPodOperator(
        task_id="{{ node["id"] }}",
        image="{{ node['image'] }}",
        in_cluster=True,
        namespace=namespace,
        name="{{ node['name'] }}",
        random_name_suffix=True,
        labels={'app':'backend', 'env':'dev', 'run_ts':{{ "'{{ ts_nodash }}'" }} },
        reattach_on_restart=True,
        is_delete_operator_pod=False,
        get_logs=True,
        log_events_on_failure=True,
        cmds={{ node['cmds'] }},
        env_vars={{ node['env'] }},
        on_success_callback=task_finish_alert,
        on_failure_callback=task_finish_alert
{#        on_failure_callback=task_finish_alert#}
        )
    op_start >> {{ node['operator_name'] }}
    {% endfor %}



    {% for edge in edges%}
    {{ edge['source_operator_name'] }} >> {{ edge['target_operator_name'] }}
    {% endfor %}