airflow 示例

from airflow import DAG
from airflow.operators.bash import BashOperator
from datetime import datetime, timedelta
import pendulum # 引入时区库

# 配置 DataX 路径
DATAX_HOME = "/opt/module/datax"
JOB_PATH = "/opt/module/datax/job/test/ods_platform_order_detail_di.json"

# 设置北京时区
local_tz = pendulum.timezone("Asia/Shanghai")

default_args = {
    'owner': 'airflow',
    'depends_on_past': False,
    # 使用北京时区的开始时间
    'start_date': datetime(2024, 1, 1, tzinfo=local_tz),
    # --- 邮件配置开始 ---
    'email': ['你的收件邮箱@example.com'], 
    'email_on_failure': True,          
    'email_on_retry': False,            
    # --- 邮件配置结束 ---
    'retries': 1,
    'retry_delay': timedelta(minutes=5),
}

with DAG(
    'ods_platform_order_detail_di',
    default_args=default_args,
    schedule_interval=None, # 手动触发模式
    catchup=False,
    tags=['datax', 'ods']
) as dag:

    run_datax = BashOperator(
        task_id='run_datax_job',
        bash_command=f'python3.9 {DATAX_HOME}/bin/datax.py {JOB_PATH}',
        env={'PYTHONPATH': DATAX_HOME},
        # 成功也发邮件（你之前添加的参数）
        email_on_success=True 
    )

    # 关键修正：确保这一行在 with 缩进内
    run_datax

import pendulum
from datetime import datetime, timedelta
from airflow import DAG
from airflow.operators.bash import BashOperator
from airflow.utils.task_group import TaskGroup
from airflow.utils.email import send_email # 必须导入这个函数

# 1. 定义成功回调函数
def send_success_email(context):
    """
    context 是 Airflow 自动传入的任务上下文字典
    """
    ti = context['task_instance']
    dag_id = ti.dag_id
    task_id = ti.task_id
    exec_date = context['execution_date'].astimezone(pendulum.timezone("Asia/Shanghai"))
    
    subject = f"Airflow 任务成功通知: {dag_id}"
    
    # 构建 HTML 邮件内容
    html_content = f"""
    <h3>任务运行成功！</h3>
    <p><b>DAG ID:</b> {dag_id}</p>
    <p><b>Task ID:</b> {task_id}</p>
    <p><b>执行时间:</b> {exec_date.format('YYYY-MM-DD HH:mm:ss')}</p>
    <p><b>主机名:</b> {ti.hostname}</p>
    <br>
    <p>请登录 Airflow UI 查看详细日志。</p>
    """
    
    # 发送邮件
    send_email(
        to=['707924553@qq.com'],
        subject=subject,
        html_content=html_content
    )

# 2. 设置时区和默认参数
local_tz = pendulum.timezone("Asia/Shanghai")

default_args = {
    'owner': 'airflow',
    'depends_on_past': False,
    'start_date': datetime(2024, 1, 1, tzinfo=local_tz),
    'email': ['707924553@qq.com'],
    'email_on_failure': True,   # 失败依然使用系统默认报警
    'email_on_success': False,  # 关闭系统默认的成功邮件，改用我们自定义的回调
    'retries': 1,
    'retry_delay': timedelta(minutes=5),
}

# 3. 定义 DAG
with DAG(
    'datax_complex_sync_v2',
    default_args=default_args,
    schedule_interval=None,
    catchup=False
) as dag:

    start = BashOperator(task_id='start_node', bash_command='echo "Start"')

    with TaskGroup("sync_group") as sync_group:
        with TaskGroup("doris_ops") as doris_ops:
            t1 = BashOperator(task_id='pre_check', bash_command='echo "Check"')
            t2 = BashOperator(task_id='datax_run', bash_command='echo "Run"')
            t1 >> t2 

        with TaskGroup("logging_ops") as logging_ops:
            t3 = BashOperator(task_id='log_start', bash_command='echo "Log Start"')
            t4 = BashOperator(task_id='log_end', bash_command='echo "Log End"')
            t3 >> t4

        doris_ops >> logging_ops

    # 在最后一个节点配置回调
    end = BashOperator(
        task_id='end_node',
        bash_command='echo "All Success"',
        on_success_callback=send_success_email  # <--- 在这里绑定回调函数
    )

    start >> sync_group >> end