Airflow 2.2.3 + MySQL 8.0.27 + Redis 6.2 部署Airflow任务调度平台

上文简单的了解了airflow的概念与使用场景，今天就通过Docker安装一下Airflow,在使用中在深入的了解一下airflow有哪些具体的功能。

Airflow容器化部署

阿里云的宿主机环境：

• 操作系统: Ubuntu 20.04.3 LTS
• 内核版本: Linux 5.4.0-91-generic

安装docker

安装Docker可参考官方文档,纯净系统，就没必要卸载旧版本了，因为是云上平台，为防止配置搞坏环境，你可以先提前进行快照。

 # 更新repo
 sudo apt-get update
 sudo apt-get install \
    ca-certificates \
    curl \
    gnupg \
    lsb-release
    
# 添加docker gpg key
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo gpg --dearmor -o /usr/share/keyrings/docker-archive-keyring.gpg

# 设置docker stable仓库地址
echo \
  "deb [arch=$(dpkg --print-architecture) signed-by=/usr/share/keyrings/docker-archive-keyring.gpg] https://download.docker.com/linux/ubuntu \
  $(lsb_release -cs) stable" | sudo tee /etc/apt/sources.list.d/docker.list > /dev/null
  
# 查看可安装的docker-ce版本
root@bigdata1:~# apt-cache madison docker-ce
 docker-ce | 5:20.10.12~3-0~ubuntu-focal | https://download.docker.com/linux/ubuntu focal/stable amd64 Packages
 docker-ce | 5:20.10.11~3-0~ubuntu-focal | https://download.docker.com/linux/ubuntu focal/stable amd64 Packages
 docker-ce | 5:20.10.10~3-0~ubuntu-focal | https://download.docker.com/linux/ubuntu focal/stable amd64 Packages
 docker-ce | 5:20.10.9~3-0~ubuntu-focal | https://download.docker.com/linux/ubuntu focal/stable amd64 Packages

# 安装命令格式
#sudo apt-get install docker-ce= docker-ce-cli= containerd.io
# 安装指定版本
sudo apt-get install docker-ce=5:20.10.12~3-0~ubuntu-focal docker-ce-cli=5:20.10.12~3-0~ubuntu-focal containerd.io

优化Docker配置

/etc/docker/daemon.json

{
    "data-root": "/var/lib/docker",
    "exec-opts": [
        "native.cgroupdriver=systemd"
    ],
    "registry-mirrors": [
        "https://****.mirror.aliyuncs.com" #此处配置一些加速的地址，比如阿里云的等等...
    ],
    "storage-driver": "overlay2",
    "storage-opts": [
        "overlay2.override_kernel_check=true"
    ],
    "log-driver": "json-file",
    "log-opts": {
        "max-size": "100m",
        "max-file": "3"
    }
}

配置开机自己

systemctl daemon-reload
systemctl enable --now docker.service

容器化安装Airflow

数据库选型

根据官网的说明，数据库建议使用MySQL8+和postgresql 9.6+，在官方的docker-compose脚本中使用是PostgreSQL,因此我们需要调整一下docker-compose.yml的内容

---
version: '3'
x-airflow-common:
  &airflow-common
  # In order to add custom dependencies or upgrade provider packages you can use your extended image.
  # Comment the image line, place your Dockerfile in the directory where you placed the docker-compose.yaml
  # and uncomment the "build" line below, Then run `docker-compose build` to build the images.
  image: ${AIRFLOW_IMAGE_NAME:-apache/airflow:2.2.3}
  # build: .
  environment:
    &airflow-common-env
    AIRFLOW__CORE__EXECUTOR: CeleryExecutor
    AIRFLOW__CORE__SQL_ALCHEMY_CONN: mysql+mysqldb://airflow:aaaa@mysql/airflow # 此处替换为mysql连接方式
    AIRFLOW__CELERY__RESULT_BACKEND: db+mysql://airflow:aaaa@mysql/airflow # 此处替换为mysql连接方式
    AIRFLOW__CELERY__BROKER_URL: redis://:xxxx@redis:6379/0 # 为保证安全，我们对redis开启了认证，因此将此处xxxx替换为redis密码
    AIRFLOW__CORE__FERNET_KEY: ''
    AIRFLOW__CORE__DAGS_ARE_PAUSED_AT_CREATION: 'true'
    AIRFLOW__CORE__LOAD_EXAMPLES: 'true'
    AIRFLOW__API__AUTH_BACKEND: 'airflow.api.auth.backend.basic_auth'
    _PIP_ADDITIONAL_REQUIREMENTS: ${_PIP_ADDITIONAL_REQUIREMENTS:-}
  volumes:
    - ./dags:/opt/airflow/dags
    - ./logs:/opt/airflow/logs
    - ./plugins:/opt/airflow/plugins
  user: "${AIRFLOW_UID:-50000}:0"
  depends_on:
    &airflow-common-depends-on
    redis:
      condition: service_healthy
    mysql: # 此处修改为mysql service名称
      condition: service_healthy

services:
  mysql:
    image: mysql:8.0.27 # 修改为mysql最新版镜像
    environment:
      MYSQL_ROOT_PASSWORD: bbbb # MySQL root账号密码
      MYSQL_USER: airflow
      MYSQL_PASSWORD: aaaa # airflow用户的密码
      MYSQL_DATABASE: airflow
    command:
      --default-authentication-plugin=mysql_native_password # 指定默认的认证插件
      --collation-server=utf8mb4_general_ci # 依据官方指定字符集
      --character-set-server=utf8mb4 # 依据官方指定字符编码
    volumes:
      - /apps/airflow/mysqldata8:/var/lib/mysql # 持久化MySQL数据
      - /apps/airflow/my.cnf:/etc/my.cnf # 持久化MySQL配置文件
    healthcheck:
      test:  mysql --user=$$MYSQL_USER --password=$$MYSQL_PASSWORD -e 'SHOW DATABASES;' # healthcheck command
      interval: 5s
      retries: 5
    restart: always

  redis:
    image: redis:6.2
    expose:
      - 6379
    command: redis-server --requirepass xxxx # redis-server开启密码认证
    healthcheck:
      test: ["CMD", "redis-cli","-a","xxxx","ping"] # redis使用密码进行healthcheck
      interval: 5s
      timeout: 30s
      retries: 50
    restart: always

  airflow-webserver:
    <<: *airflow-common
    command: webserver
    ports:
      - 8080:8080
    healthcheck:
      test: ["CMD", "curl", "--fail", "http://localhost:8080/health"]
      interval: 10s
      timeout: 10s
      retries: 5
    restart: always
    depends_on:
      <<: *airflow-common-depends-on
      airflow-init:
        condition: service_completed_successfully

  airflow-scheduler:
    <<: *airflow-common
    command: scheduler
    healthcheck:
      test: ["CMD-SHELL", 'airflow jobs check --job-type SchedulerJob --hostname "$${HOSTNAME}"']
      interval: 10s
      timeout: 10s
      retries: 5
    restart: always
    depends_on:
      <<: *airflow-common-depends-on
      airflow-init:
        condition: service_completed_successfully

  airflow-worker:
    <<: *airflow-common
    command: celery worker
    healthcheck:
      test:
        - "CMD-SHELL"
        - 'celery --app airflow.executors.celery_executor.app inspect ping -d "celery@$${HOSTNAME}"'
      interval: 10s
      timeout: 10s
      retries: 5
    environment:
      <<: *airflow-common-env
      # Required to handle warm shutdown of the celery workers properly
      # See https://airflow.apache.org/docs/docker-stack/entrypoint.html#signal-propagation
      DUMB_INIT_SETSID: "0"
    restart: always
    depends_on:
      <<: *airflow-common-depends-on
      airflow-init:
        condition: service_completed_successfully

  airflow-triggerer:
    <<: *airflow-common
    command: triggerer
    healthcheck:
      test: ["CMD-SHELL", 'airflow jobs check --job-type TriggererJob --hostname "$${HOSTNAME}"']
      interval: 10s
      timeout: 10s
      retries: 5
    restart: always
    depends_on:
      <<: *airflow-common-depends-on
      airflow-init:
        condition: service_completed_successfully

  airflow-init:
    <<: *airflow-common
    entrypoint: /bin/bash
    # yamllint disable rule:line-length
    command:
      - -c
      - |
        function ver() {
          printf "%04d%04d%04d%04d" $${1//./ }
        }
        airflow_version=$$(gosu airflow airflow version)
        airflow_version_comparable=$$(ver $${airflow_version})
        min_airflow_version=2.2.0
        min_airflow_version_comparable=$$(ver $${min_airflow_version})
        if (( airflow_version_comparable < min_airflow_version_comparable )); then
          echo
          echo -e "\033[1;31mERROR!!!: Too old Airflow version $${airflow_version}!\e[0m"
          echo "The minimum Airflow version supported: $${min_airflow_version}. Only use this or higher!"
          echo
          exit 1
        fi
        if [[ -z "${AIRFLOW_UID}" ]]; then
          echo
          echo -e "\033[1;33mWARNING!!!: AIRFLOW_UID not set!\e[0m"
          echo "If you are on Linux, you SHOULD follow the instructions below to set "
          echo "AIRFLOW_UID environment variable, otherwise files will be owned by root."
          echo "For other operating systems you can get rid of the warning with manually created .env file:"
          echo "    See: https://airflow.apache.org/docs/apache-airflow/stable/start/docker.html#setting-the-right-airflow-user"
          echo
        fi
        one_meg=1048576
        mem_available=$$(($$(getconf _PHYS_PAGES) * $$(getconf PAGE_SIZE) / one_meg))
        cpus_available=$$(grep -cE 'cpu[0-9]+' /proc/stat)
        disk_available=$$(df / | tail -1 | awk '{print $$4}')
        warning_resources="false"
        if (( mem_available < 4000 )) ; then
          echo
          echo -e "\033[1;33mWARNING!!!: Not enough memory available for Docker.\e[0m"
          echo "At least 4GB of memory required. You have $$(numfmt --to iec $$((mem_available * one_meg)))"
          echo
          warning_resources="true"
        fi
        if (( cpus_available < 2 )); then
          echo
          echo -e "\033[1;33mWARNING!!!: Not enough CPUS available for Docker.\e[0m"
          echo "At least 2 CPUs recommended. You have $${cpus_available}"
          echo
          warning_resources="true"
        fi
        if (( disk_available < one_meg * 10 )); then
          echo
          echo -e "\033[1;33mWARNING!!!: Not enough Disk space available for Docker.\e[0m"
          echo "At least 10 GBs recommended. You have $$(numfmt --to iec $$((disk_available * 1024 )))"
          echo
          warning_resources="true"
        fi
        if [[ $${warning_resources} == "true" ]]; then
          echo
          echo -e "\033[1;33mWARNING!!!: You have not enough resources to run Airflow (see above)!\e[0m"
          echo "Please follow the instructions to increase amount of resources available:"
          echo "   https://airflow.apache.org/docs/apache-airflow/stable/start/docker.html#before-you-begin"
          echo
        fi
        mkdir -p /sources/logs /sources/dags /sources/plugins
        chown -R "${AIRFLOW_UID}:0" /sources/{logs,dags,plugins}
        exec /entrypoint airflow version
    # yamllint enable rule:line-length
    environment:
      <<: *airflow-common-env
      _AIRFLOW_DB_UPGRADE: 'true'
      _AIRFLOW_WWW_USER_CREATE: 'true'
      _AIRFLOW_WWW_USER_USERNAME: ${_AIRFLOW_WWW_USER_USERNAME:-airflow}
      _AIRFLOW_WWW_USER_PASSWORD: ${_AIRFLOW_WWW_USER_PASSWORD:-airflow}
    user: "0:0"
    volumes:
      - .:/sources

  airflow-cli:
    <<: *airflow-common
    profiles:
      - debug
    environment:
      <<: *airflow-common-env
      CONNECTION_CHECK_MAX_COUNT: "0"
    # Workaround for entrypoint issue. See: https://github.com/apache/airflow/issues/16252
    command:
      - bash
      - -c
      - airflow

  flower:
    <<: *airflow-common
    command: celery flower
    ports:
      - 5555:5555
    healthcheck:
      test: ["CMD", "curl", "--fail", "http://localhost:5555/"]
      interval: 10s
      timeout: 10s
      retries: 5
    restart: always
    depends_on:
      <<: *airflow-common-depends-on
      airflow-init:
        condition: service_completed_successfully

在官方docker-compose.yaml基础上只修改了x-airflow-common,MySQL,Redis相关配置，接下来就应该启动容器了，在启动之前，需要创建几个持久化目录:

mkdir -p ./dags ./logs ./plugins
echo -e "AIRFLOW_UID=$(id -u)" > .env # 注意，此处一定要保证AIRFLOW_UID是普通用户的UID,且保证此用户有创建这些持久化目录的权限

如果不是普通用户，在运行容器的时候，会报错，No module named 'airflow'找不到airflow模块

docker-compose up airflow-init #初始化数据库，以及创建表
docker-compose up -d #创建airflow容器

当出现容器的状态为unhealthy的时候，要通过docker inspect $container_name查看报错的原因，至此airflow的安装就已经完成了。