Airflow 在 Docker 中运行其他容器的作业

Question

我尝试在 Airflow 中使用 PythonOperator 运行 (python_callable) 以执行其他容器的作业 (PHP)。 但如果失败，主要错误在这里：

Broken DAG: [/opt/airflow/dags/cobalagi.py] Traceback (most recent call last):
  File "<frozen importlib._bootstrap>", line 219, in _call_with_frames_removed
  File "/opt/airflow/dags/cobalagi.py", line 3, in <module>
    import command
ModuleNotFoundError: No module named 'command'

---

尝试删除“导入命令”，但 Airflow 图形变为红色（失败），错误日志如下：

[2022-08-16, 04:31:52 UTC] {standard_task_runner.py:97} ERROR - Failed to execute job 1055 for task address (Object of type bytes is not JSON serializable; 15679)

---

权限被拒绝错误。 尝试重新启动桌面，但仍然：

[2022-08-16, 11:05:40 UTC] {standard_task_runner.py:97} ERROR - Failed to execute job 2046 for task address (Error while fetching server API version: ('Connection aborted.', PermissionError(13, 'Permission denied')); 740)

---

然后我在 docker-compose.yml 目录中使用“pip install command”安装“command”，但错误是一样的。 这是源代码：

version: '2.3.2'
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:2.3.2}
  # build: .
  environment:
    &airflow-common-env
    AIRFLOW__CORE__EXECUTOR: LocalExecutor
    AIRFLOW__DATABASE__SQL_ALCHEMY_CONN: postgresql+psycopg2://airflow:airflow@postgres/airflow
    # For backward compatibility, with Airflow <2.3
    AIRFLOW__CORE__SQL_ALCHEMY_CONN: postgresql+psycopg2://airflow:airflow@postgres/airflow
    AIRFLOW__CORE__FERNET_KEY: ''
    AIRFLOW__CORE__DAGS_ARE_PAUSED_AT_CREATION: 'true'
    AIRFLOW__CORE__LOAD_EXAMPLES: 'false'
    AIRFLOW__API__AUTH_BACKENDS: 'airflow.api.auth.backend.basic_auth'
    _PIP_ADDITIONAL_REQUIREMENTS: ${_PIP_ADDITIONAL_REQUIREMENTS:- airflow-code-editor apache-airflow-providers-docker}
  volumes:
    - ./dags:/opt/airflow/dags
    - ./logs:/opt/airflow/logs
    - ./plugins:/opt/airflow/plugins
    - //var/run/docker.sock:/var/run/docker.sock
  user: "${AIRFLOW_UID:-50000}:0"
  depends_on:
    &airflow-common-depends-on
    postgres:
      condition: service_healthy

services:
  postgres:
    image: postgres:13
    ports:
      - 5432:5432
    environment:
      POSTGRES_USER: airflow
      POSTGRES_PASSWORD: airflow
      POSTGRES_DB: airflow
    volumes:
      - postgres-db-volume:/var/lib/postgresql/data
      - //var/run/docker.sock:/var/run/docker.sock
    healthcheck:
      test: ["CMD", "pg_isready", "-U", "airflow"]
      interval: 5s
      retries: 5
    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-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}
      _PIP_ADDITIONAL_REQUIREMENTS: ''
    user: "0:0"
    volumes:
      - .:/sources
      - //var/run/docker.sock:/var/run/docker.sock

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

---

这是 python.py：

import docker

from airflow import DAG
from datetime import datetime, timedelta
from airflow.operators.python_operator import PythonOperator


from command import showAddress

default_args = {
    "owner": "airflow", 
    "start_date": datetime(2021, 3, 7)}

def showAddress():
    client = docker.from_env()
    container = client.containers.get('shouts-laravel-app')
    cmd = container.exec_run(
        "php artisan showAddress"
    )

    return cmd

with DAG(
    dag_id="tryToShow", 
    default_args=default_args, 
    schedule_interval='@daily'
    
) as dag:

    showAddress = PythonOperator(
        task_id="address",
        python_callable=showAddress
    )

    showAddress

---

我已经在 1 个名为 laravel_laravel-shouts 的网络中制作了这些容器。 这是 Docker：

Z469A31FD9D773110F14057BAECCDDD25Z列表

请帮忙，我应该怎么做才能达到目标（使用气流运行 PHP 作业）？

Answer 1

在某些情况下，方法exec_run返回字节，当您在PythonOperator中调用方法showAddress时，该方法的结果将存储在 xcom 中，因此它需要可序列化，但字节不是，因此 Airflow 提出了错误：

ERROR - Failed to execute job 1055 for task address (Object of type bytes is not JSON serializable; 15679)

尝试将元组cmd中的数据转换为字符串：这是一种方法。

# just replace
# return cmd
# by
return cmd[1].decode('utf-8') if isinstance(cmd[1], bytes) else cmd[1]