Airflow 2.5.0配置Dask调度器/Worker后UI提示调度器未运行

核心问题分析 #

1. 遗漏Airflow自身调度器：你错误地用Dask调度器替代了Airflow调度器——Airflow的DaskExecutor逻辑是让Airflow调度器将任务提交给Dask集群执行，Airflow自身的scheduler进程必须保留，UI提示的心跳缺失就是因为这个核心进程未启动。
2. 残留无用配置：配置中仍保留AIRFLOW__CELERY__RESULT_BACKEND、AIRFLOW__CELERY__BROKER_URL等Celery相关变量，使用DaskExecutor时这些配置完全无效。
3. 数据库连接错误：mysql+mysqlconnector://airflow:localhost@3306/airflow中的localhost指向容器自身，若MySQL部署在宿主机或其他容器，该地址无法建立连接。
4. Dask服务配置冗余：Dask调度器/Worker无需继承Airflow的环境变量和卷，且dask-worker服务存在YAML缩进语法错误。
5. 缺少Dask依赖：Airflow容器需安装dask和distributed库才能与Dask集群通信。

修复后的Docker Compose配置 #

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# Airflow 2.5.0 with DaskExecutor configuration
---
version: '3'
x-airflow-common:
  &airflow-common
  image: ${AIRFLOW_IMAGE_NAME:-apache/airflow:2.5.0}
  environment:
    &airflow-common-env
    AIRFLOW__CORE__EXECUTOR: DaskExecutor
    # 修正数据库连接：替换为实际MySQL地址（宿主机IP/容器服务名）和密码
    AIRFLOW__DATABASE__SQL_ALCHEMY_CONN: mysql+mysqlconnector://airflow:your_mysql_password@your_mysql_host:3306/airflow
    AIRFLOW__CORE__SQL_ALCHEMY_CONN: mysql+mysqlconnector://airflow:your_mysql_password@your_mysql_host:3306/airflow
    # 配置Dask集群地址
    AIRFLOW__DASK__CLUSTER_ADDRESS: tcp://127.0.0.1:8786
    AIRFLOW__CORE__FERNET_KEY: ''
    AIRFLOW__CORE__DAGS_ARE_PAUSED_AT_CREATION: 'true'
    AIRFLOW__CORE__LOAD_EXAMPLES: 'true'
    AIRFLOW__API__AUTH_BACKENDS: 'airflow.api.auth.backend.basic_auth'
    # 添加Dask依赖库
    _PIP_ADDITIONAL_REQUIREMENTS: ${_PIP_ADDITIONAL_REQUIREMENTS:- mysql mysql-connector-python dask distributed}
  volumes:
    - ./dags:/opt/airflow/dags
    - ./logs:/opt/airflow/logs
    - ./plugins:/opt/airflow/plugins
  user: "${AIRFLOW_UID:-50000}:0"
  depends_on:
    &airflow-common-depends-on
    redis:
      condition: service_healthy
    # 若MySQL为容器部署，在此添加MySQL服务的依赖

services:
  redis:
    image: redis:latest
    network_mode: "host"
    expose:
      - 6379
    healthcheck:
      test: ["CMD", "redis-cli", "ping"]
      interval: 5s
      timeout: 30s
      retries: 50
    restart: always

  airflow-webserver:
    <<: *airflow-common
    network_mode: "host"
    command: webserver
    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

  # 新增Airflow自身调度器进程，必须保留
  airflow-scheduler:
    <<: *airflow-common
    network_mode: "host"
    command: scheduler
    healthcheck:
      test: ["CMD-SHELL", 'airflow jobs check --job-type SchedulerJob --hostname 127.0.0.1']
      interval: 10s
      timeout: 10s
      retries: 5
    restart: always
    depends_on:
      <<: *airflow-common-depends-on
      airflow-init:
        condition: service_completed_successfully

  # 简化Dask调度器配置
  dask-scheduler:
    image: daskdev/dask:latest
    network_mode: "host"
    command: dask-scheduler
    restart: always

  # 修复缩进错误，简化Dask Worker配置
  dask-worker:
    image: daskdev/dask:latest
    network_mode: "host"
    command: ["dask worker", "tcp://127.0.0.1:8786"]
    restart: always
    depends_on:
      - dask-scheduler

  airflow-triggerer:
    <<: *airflow-common
    network_mode: "host"
    command: triggerer
    healthcheck:
      test: ["CMD-SHELL", 'airflow jobs check --job-type TriggererJob --hostname 127.0.0.1']
      interval: 10s
      timeout: 10s
      retries: 5
    restart: always
    depends_on:
      <<: *airflow-common-depends-on
      airflow-init:
        condition: service_completed_successfully

  airflow-init:
    <<: *airflow-common
    network_mode: "host"
    entrypoint: /bin/bash
    command:
      - -c
      - |
        function ver() {
          printf "%04d%04d%04d%04d" $${1//./ }
        }
        airflow_version=$$(AIRFLOW__LOGGING__LOGGING_LEVEL=INFO && 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/howto/docker-compose/index.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/howto/docker-compose/index.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
    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}
      _PIP_ADDITIONAL_REQUIREMENTS: ''
    user: "0:0"
    volumes:
      - .:/sources

  airflow-cli:
    <<: *airflow-common
    profiles:
      - debug
    environment:
      <<: *airflow-common-env
      CONNECTION_CHECK_MAX_COUNT: "0"
    command:
      - bash
      - -c
      - airflow

额外操作步骤 #

1. 将配置中的your_mysql_password和your_mysql_host替换为实际的MySQL密码和地址
2. 若MySQL为容器部署，需在services节点下添加MySQL服务，并在airflow-common的depends_on中补充依赖
3. 启动前清理旧容器和卷：docker compose down -v，再执行docker compose up -d

内容的提问来源于stack exchange，提问作者s misra