时间戳

首页 > 解决方案 > Apache Airflow 2 从 1.1 升级后不执行任务

python-3.x - Apache Airflow 2 从 1.1 升级后不执行任务

问题描述

我今天升级到 Airflow 2.0（docker），从那时起，我无法执行任何任务（它们成功失败，但由于以下错误而卡在绿色）。

编辑：我正在编辑它以突出 vanilla docker-compose 文件与我专门进行的更改之间的区别。

airflow_worker       | 
airflow_worker       | 
airflow_worker       | airflow command error: argument GROUP_OR_COMMAND: celery subcommand works only with CeleryExecutor, your current executor: SequentialExecutor, see help above.
airflow_worker       | usage: airflow [-h] GROUP_OR_COMMAND ...
airflow_worker       | shows all the options here
airflow_worker       |   -h, --help         show this help message and exit
airflow_worker exited with code 2

我使用了标准的 docker-compose 并做了一些小的改动以满足我的需要。这是我的 docker-compose.yml

version: '3'
x-airflow-common:
  &airflow-common
  image: ${AIRFLOW_IMAGE_NAME:-apache/airflow:2.2.1}
  # build: .
  environment:
    &airflow-common-env
    AIRFLOW__CORE__EXECUTOR: CeleryExecutor
    AIRFLOW__CORE__SQL_ALCHEMY_CONN: postgresql+psycopg2:**//xxx:xxx@db/xxx**
    AIRFLOW__CELERY__RESULT_BACKEND: **db+postgresql://xxx:xxx@db/xxx**
    AIRFLOW__CELERY__BROKER_URL: redis://:@redis:6379/0
    AIRFLOW__CORE__FERNET_KEY: '**xxx**'
    AIRFLOW__CORE__DAGS_ARE_PAUSED_AT_CREATION: 'true'
    AIRFLOW__CORE__LOAD_EXAMPLES: '**false**'
    AIRFLOW__API__AUTH_BACKEND: 'airflow.api.auth.backend.basic_auth'
    _AIRFLOW_WWW_USER_USERNAME: airflow
    _AIRFLOW_WWW_USER_PASSWORD: airflow
    _PIP_ADDITIONAL_REQUIREMENTS: ${_PIP_ADDITIONAL_REQUIREMENTS:-}
  volumes:
    **- ./dags:/opt/airflow/dags
    - ./logs:/opt/airflow/logs
    - ./plugins:/opt/airflow/plugins
    - ./pgadmin-data:/var/lib/pgadmin**
    - ./airflow/dags:/opt/airflow/dags
    - ./airflow/logs:/opt/airflow/logs
    - ./airflow/plugins:/opt/airflow/plugins
  user: "${AIRFLOW_UID:-1000}:0"
  depends_on:
    &airflow-common-depends-on
    redis:
      condition: service_healthy
    db:
      condition: service_healthy

services:
  db:
    image: **postgres:latest**
    **env_file:
      - database.env**
    **volumes:
      - ./db/:/var/lib/postgresql/data**
    healthcheck:
      test: [ "CMD", "pg_isready", "-q", "-d", "airflow", "-U", "airflow" ]
      interval: 5s
      retries: 5
    restart: always

  redis:
    container_name: redis_queue
    image: redis:6.2.6-bullseye
    command: redis-server --requirepass redispass
    **env_file:
      - redis.env**
    expose:
      - 6379
    healthcheck:
      test: ["CMD", "redis-cli", "ping"]
      interval: 5s
      timeout: 30s
      retries: 50
    restart: always

  airflow-webserver:
    <<: *airflow-common
    container_name: airflow_web
    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
    container_name: airflow_scheduler
    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

  flower:
    <<: *airflow-common
    container_name: flower_web
    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

  airflow-worker:
    <<: *airflow-common
    container_name: airflow_worker
    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:
      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**
  
  pgadmin:
    image: dpage/pgadmin4:latest
    restart: always
    e**nv_file:
      - pg_admin.env**
    ports:
    - "8060:80"
    links:
    - "db:pgsql-server"

  airflow-init:
    <<: *airflow-common
    entrypoint: /bin/bash
    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
    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:
      - .**/airflow**:/sources

volumes:
  db:
  pgadmin-data:
  dags:
  logs:
  plugins:

该错误每隔几分钟就会显示一次，或者每当气流尝试执行我的任务时显示。

标签： python-3.xdjangoceleryairflow

解决方案

迁移到 Airflow 2.2.3 时我遇到了同样的错误：

气流命令错误：参数 GROUP_OR_COMMAND：airflow worker 命令，已被删除，请使用airflow celery worker，请参阅上面的帮助。

将入口点/命令更改为以下内容可解决问题：

airflow celery worker

推荐阅读