airflow 1.x 分布式部署实战（qbit）

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    前言

    • airflow 是 DAG(有向无环图)的任务管理系统，简单的理解就是一个高级版的 crontab。
    • airflow 解决了 crontab 无法解决的任务依赖问题。

    环境与组件

    • Ubuntu 18.04
    • MySQL 5.7
    • Python 3.6.9
    • airflow 1.10.10
    • celery 4.4.2
    • RabbitMQ 3.6.10
      master-node

    实战步骤

    基本步骤

    • 安装 Python3 的 pip

      sudo apt install python3-pip

    • 安装 MySQL 开发包

      # 避免报错： OSError: mysql_config not found
sudo apt install libmysqlclient-dev python3-dev

    • 在 3 台 airflow 服务器服务器上创建账号

      sudo useradd airflow -m -s /bin/bash
sudo passwd airflow
    • 以下步骤在 airflow 账号下进行

    • 修改 PATH 环境变量

      在 /home/airflow/.bashrc 文件尾追加以下内容：
export PATH=/home/airflow/.local/bin:$PATH

    • 升级 pip

      pip3 install pip --upgrade

    • 设置豆瓣镜像

      pip3 config set global.index-url https://pypi.doubanio.com/simple/

    • 在 3 台机器上安装 airflow

      # 全家桶（master）
pip3 install "apache-airflow[all]==1.10.*"
# OR 选择性安装
pip3 install "apache-airflow[mysql,celery,rabbitmq]==1.10.*"

    • 查看 airflow 版本并创建 airflow 的 HOME 目录

      # 默认 ~/airflow 目录
airflow version

    • 设置 Ubuntu 18.04 系统时区

      timedatectl set-timezone Asia/Shanghai

    • 修改后台时区（/home/airflow/airflow/airflow.cfg）

      [core]
# Default timezone in case supplied date times are naive
# can be utc (default), system, or any IANA timezone string (e.g. Europe/Amsterdam)
# default_timezone = utc  
# 改为 system 或 Asia/Shanghai
default_timezone = system

    • 启用 RBAC UI 并修改 UI 时区

      [webserver]
rbac=True
default_ui_timezone = system

    • 修改 MySQL 连接（/home/airflow/airflow/airflow.cfg）

      [core]
# MySQL 连接字符串
sql_alchemy_conn = mysql+pymysql://youruser:passwd@192.168.x.y/airflow

    • 安装 pymysql

      pip3 install pymysql
    • 手动创建 airflow 数据库

    • 初始化数据库表

      airflow initdb
    • 查看数据库是否初始化成功
      airflow-mysql.png

    • 创建用户

      # 角色表： ab_role
# 用户表： ab_user
# 创建 Admin 角色用户 
airflow create_user --lastname user \
 --firstname admin \
 --username admin \
 --email walkerqt@foxmail.com \
 --role Admin \
 --password admin123
# 创建 Viewer 角色用户 
airflow create_user --lastname user \
 --firstname view \
 --username view \
 --email walkerqt@163.com \
 --role Viewer \
 --password view123

    • 启动 web 服务器，默认端口是 8080

      airflow webserver -p 8080

    • 启动定时器

      airflow scheduler
    • 用浏览器打开 192.168.y.z:8080 查看 WEB UI
      web-ui-login
      登陆后
      web-ui
    • 在 RabbitMQ 上创建 airflow 账号，并分配 virtual host
      RabbitMQ

    • 修改 master 配置文件（/home/airflow/airflow/airflow.cfg）

      [core]
executor = CeleryExecutor
[celery]
broker_url = amqp://mq_user:mq_pwd@192.168.y.z:5672/vhost_airflow
result_backend = db+mysql://youruser:passwd@192.168.x.y/airflow

    • 从 master 同步配置文件到 node

      # 测试
rsync -v /home/airflow/airflow/airflow.cfg airflow@node1_ip:/home/airflow/airflow/
rsync -v /home/airflow/airflow/airflow.cfg airflow@node2_ip:/home/airflow/airflow/

    • 免密码提示脚本

      # 明文暴露了密码，不建议生产环境使用
sshpass -p airflow rsync /home/airflow/airflow/airflow.cfg airflow@node1_ip:/home/airflow/airflow/
sshpass -p airflow rsync /home/airflow/airflow/airflow.cfg airflow@node2_ip:/home/airflow/airflow/

    • 创建测试脚本（/home/airflow/airflow/dags/send_msg.py），发送本机 IP 到企业微信。

      # encoding: utf-8
# author: qbit
# date: 2020-04-02
# summary: 发送/分配任务到任务结点

import os
import time
import json
import psutil  
import requests
from datetime import timedelta
from airflow.utils.dates import days_ago
from airflow.models import DAG
from airflow.operators.python_operator import PythonOperator

default_args = {
  'owner': 'Airflow',
  # depends_on_past 是否依赖于过去。
  # 如果为True，那么必须要上次的DAG执行成功了，这次的DAG才能执行。
  'depends_on_past': False,
  'start_date': days_ago(1),
}

dag = DAG(
  dag_id='send_msg',
  default_args=default_args,
  # catchup 是否回补（backfill）开始时间到现在的任务
  catchup=False,  
  start_date=days_ago(1),
  schedule_interval=timedelta(seconds=60),
  tags=['example']
)
      def GetLocalIPByPrefix(prefix):
  r"""
  多网卡情况下，根据前缀获取IP
  测试可用：Windows、Linux，Python 3.6.x，psutil 5.4.x
  ipv4/ipv6 地址均适用
  注意如果有多个相同前缀的 ip，只随机返回一个
  """
  localIP = ''
  dic = psutil.net_if_addrs()
  for adapter in dic:
      snicList = dic[adapter]
      for snic in snicList:
          if not snic.family.name.startswith('AF_INET'):
              continue                
          ip = snic.address
          if ip.startswith(prefix):
              localIP = ip
   
  return localIP     

def send_msg(msg='default msg', **context):
  r""" 发送 message 到企业微信 """
  print(context)
  run_id = context['run_id']
  nowTime = time.strftime('%Y-%m-%d %H:%M:%S',time.localtime())
  message =  '%s\n%s\n%s_%d\n%s' % (run_id, nowTime, 
                      GetLocalIPByPrefix('192.168.'), os.getpid(), msg)
  print(message)
  
  '''
  发送代码
  '''
      first = PythonOperator(
  task_id='send_msg_1',
  python_callable=send_msg,
  op_kwargs={'msg':'111'},
  provide_context=True,
  dag=dag,
)

second = PythonOperator(
  task_id='send_msg_2',
  python_callable=send_msg,
  op_kwargs={'msg':'222'},
  provide_context=True,
  dag=dag,
)

third = PythonOperator(
  task_id='send_msg_3',
  python_callable=send_msg,
  op_kwargs={'msg':'333'},
  provide_context=True,
  dag=dag,
)

[third, first] >> second

      send_msg

    • 验证脚本

      # 打印出所有正在活跃状态的 DAGs
airflow list_dags

# 打印出 'send_msg' DAG 中所有的任务
airflow list_tasks send_msg

# 打印出 'send_msg' DAG 的任务层次结构
airflow list_tasks send_msg --tree

    • 从 master 同步 dags 目录到 node

      sshpass -p airflow rsync -a /home/airflow/airflow/dags/ airflow@node1_ip:/home/airflow/airflow/dags/
sshpass -p airflow rsync -a /home/airflow/airflow/dags/ airflow@node2_ip:/home/airflow/airflow/dags/

    • 启动步骤

      # master
airflow webserver -p 8080
airflow scheduler
airflow flower  # 默认端口 5555
# node1/node2
airflow worker

    错误排查

    • 启动 worker 如果报类似下面的错误，是 celery 连 RabbitMQ的问题，卸载 librabbitmq 即可。
      卸载命令：

      pip3 uninstall librabbitmq

      错误：

      [2020-04-02 14:54:42,279: CRITICAL/MainProcess] Unrecoverable error: SystemError('<built-in method _basic_recv of Connection object at 0x7fc1da870a68> returned a result with an error set',)
Traceback (most recent call last):
File "/home/airflow/.local/lib/python3.6/site-packages/kombu/messaging.py", line 624, in _receive_callback
  return on_m(message) if on_m else self.receive(decoded, message)
File "/home/airflow/.local/lib/python3.6/site-packages/celery/worker/consumer/consumer.py", line 571, in on_task_received
  callbacks,
File "/home/airflow/.local/lib/python3.6/site-packages/celery/worker/strategy.py", line 203, in task_message_handler
  handle(req)
File "/home/airflow/.local/lib/python3.6/site-packages/celery/worker/worker.py", line 223, in _process_task_sem
  return self._quick_acquire(self._process_task, req)
File "/home/airflow/.local/lib/python3.6/site-packages/kombu/asynchronous/semaphore.py", line 62, in acquire
  callback(*partial_args, **partial_kwargs)
File "/home/airflow/.local/lib/python3.6/site-packages/celery/worker/worker.py", line 228, in _process_task
  req.execute_using_pool(self.pool)
File "/home/airflow/.local/lib/python3.6/site-packages/celery/worker/request.py", line 652, in execute_using_pool
  correlation_id=task_id,
File "/home/airflow/.local/lib/python3.6/site-packages/celery/concurrency/base.py", line 158, in apply_async
  **options)
File "/home/airflow/.local/lib/python3.6/site-packages/billiard/pool.py", line 1530, in apply_async
  self._quick_put((TASK, (result._job, None, func, args, kwds)))
File "/home/airflow/.local/lib/python3.6/site-packages/celery/concurrency/asynpool.py", line 885, in send_job
  body = dumps(tup, protocol=protocol)
TypeError: can't pickle memoryview objects

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
File "/home/airflow/.local/lib/python3.6/site-packages/celery/worker/worker.py", line 205, in start
  self.blueprint.start(self)
File "/home/airflow/.local/lib/python3.6/site-packages/celery/bootsteps.py", line 119, in start
  step.start(parent)
File "/home/airflow/.local/lib/python3.6/site-packages/celery/bootsteps.py", line 369, in start
  return self.obj.start()
File "/home/airflow/.local/lib/python3.6/site-packages/celery/worker/consumer/consumer.py", line 318, in start
  blueprint.start(self)
File "/home/airflow/.local/lib/python3.6/site-packages/celery/bootsteps.py", line 119, in start
  step.start(parent)
File "/home/airflow/.local/lib/python3.6/site-packages/celery/worker/consumer/consumer.py", line 599, in start
  c.loop(*c.loop_args())
File "/home/airflow/.local/lib/python3.6/site-packages/celery/worker/loops.py", line 83, in asynloop
  next(loop)
File "/home/airflow/.local/lib/python3.6/site-packages/kombu/asynchronous/hub.py", line 364, in create_loop
  cb(*cbargs)
File "/home/airflow/.local/lib/python3.6/site-packages/kombu/transport/base.py", line 238, in on_readable
  reader(loop)
File "/home/airflow/.local/lib/python3.6/site-packages/kombu/transport/base.py", line 220, in _read
  drain_events(timeout=0)
File "/home/airflow/.local/lib/python3.6/site-packages/librabbitmq/__init__.py", line 227, in drain_events
  self._basic_recv(timeout)
SystemError: <built-in method _basic_recv of Connection object at 0x7fc1da870a68> returned a result with an error set

    相关链接

    airflowcelerypython
    qbit
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