Docker部署Airflow执行BashOperator时遇权限拒绝问题求助
我是初学者,在Docker部署的Airflow中运行Python文件时遭遇权限拒绝错误。该Python脚本的首个任务是将/opt/airflow/filepy/unzip/zip目录下的压缩文件解压至另一目录,这些压缩文件来自数据湖,我无法修改获取流程,仅需通过Airflow编排。脚本在Ubuntu 20命令行中可正常运行,但添加chmod命令修改目录权限后仍无法解决问题。
我的DAG位于/opt/airflow/dags,Python脚本位于/opt/airflow/filepy,手动可正常解压文件,以下是相关docker-compose配置:
# Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not use this file except in compliance # with the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. # # Basic Airflow cluster configuration for CeleryExecutor with Redis and PostgreSQL. # # WARNING: This configuration is for local development. Do not use it in a production deployment. # # This configuration supports basic configuration using environment variables or an .env file # The following variables are supported: # # AIRFLOW_IMAGE_NAME - Docker image name used to run Airflow. # Default: apache/airflow:2.3.4 # AIRFLOW_UID - User ID in Airflow containers # Default: 50000 # Those configurations are useful mostly in case of standalone testing/running Airflow in test/try-out mode # # _AIRFLOW_WWW_USER_USERNAME - Username for the administrator account (if requested). # Default: airflow # _AIRFLOW_WWW_USER_PASSWORD - Password for the administrator account (if requested). # Default: airflow # _PIP_ADDITIONAL_REQUIREMENTS - Additional PIP requirements to add when starting all containers. # Default: '' # # Feel free to modify this file to suit your needs. --- 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:2.3.4} # build: . environment: &airflow-common-env AIRFLOW__CORE__EXECUTOR: CeleryExecutor 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__CELERY__RESULT_BACKEND: db+postgresql://airflow:airflow@postgres/airflow AIRFLOW__CELERY__BROKER_URL: redis://:@redis:6379/0 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' _PIP_ADDITIONAL_REQUIREMENTS: ${_PIP_ADDITIONAL_REQUIREMENTS:- azure-core azure-functions progressbar2 wheel pytest-shutil threaded queuelib azure-storage-blob xml-python urllib3 apache-airflow-providers-microsoft-azure==4.2.0} # progressbar} volumes: - ./dags:/opt/airflow/dags - ./logs:/opt/airflow/logs - ./plugins:/opt/airflow/plugins - /home/lopp/s3i/infra/sqlserver/BD_NF:/opt/airflow/filepy user: "${AIRFLOW_UID:-50000}:0" command: "chown -R ${AIRFLOW_UID:-50000}.${AIRFLOW_UID:-50000} /opt/airflow/dags" command: "chown -R ${AIRFLOW_UID:-50000}.${AIRFLOW_UID:-50000} /opt/airflow/filepy" command: "chown -R ${AIRFLOW_UID:-50000}.${AIRFLOW_UID:-50000} /opt/airflow/filepy/unzip" command: "chown -R ${AIRFLOW_UID:-50000}.${AIRFLOW_UID:-50000} /opt/airflow/filepy/unzip/zip" depends_on: &airflow-common-depends-on redis: condition: service_healthy postgres: condition: service_healthy services: postgres: image: postgres:13 environment: POSTGRES_USER: airflow POSTGRES_PASSWORD: airflow POSTGRES_DB: airflow volumes: - postgres-db-volume:/var/lib/postgresql/data healthcheck: test: ["CMD", "pg_isready", "-U", "airflow"] interval: 5s retries: 5 restart: always redis: image: redis:latest expose: - 6379 healthcheck: test: ["CMD", "redis-cli", "ping"] 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=$$(AIRFLOW__LOGGING__LOGGING_LEVEL=INFO && gosu airflow airflow version) airflow_version_comparable=$$(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: $${min_airflow_version}. Only use this or higher!" echo exit 1 fi if [[ -z "${AIRFLOW_UID}" ]]; then echo echo -e "\033[1;33mWARNING!!!: AIRFLOW_UID not set!\e[0m" echo "If you are on Linux, you SHOULD follow the instructions below to set " echo "AIRFLOW_UID environment variable, otherwise files will be owned by root." echo "For other operating systems you can get rid of the warning with manually created .env file:" echo " See: https://airflow.apache.org/docs/apache-airflow/stable/start/docker.html#setting-the-right-airflow-user" echo fi one_meg=1048576 mem_available=$$(($$(getconf _PHYS_PAGES) * $$(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: ${_AIRFLOW_WWW_USER_PASSWORD:-airflow} _PIP_ADDITIONAL_REQUIREMENTS: '' user: "0:0" volumes: - .:/sources airflow-cli: <<: *airflow-common profiles: - debug environment: <<: *airflow-common-env CONNECTION_CHECK_MAX_COUNT: "0" # Workaround for entrypoint issue. See: https://github.com/apache/airflow/issues/16252 command: - bash - -c - airflow # You can enable flower by adding "--profile flower" option e.g. docker-compose --profile flower up # or by explicitly targeted on the command line e.g. docker-compose up flower. # See: https://docs.docker.com/compose/profiles/ flower: <<: *airflow-common command: celery flower profiles: - flower ports: - 5555:5555 healthcheck: test: ["CMD", "curl", "--fail", "http://localhost:5555/"] interval: 10s timeout: 10s retries: 5 restart: always depends_on: <<: *airflow-common-depends-on airflow-init: condition: service_completed_successfully volumes: postgres-db-volume:
问题原因
你的docker-compose配置中,x-airflow-common模板里重复定义了多个command字段,Docker Compose只会执行最后一个command,前面的chown权限修改命令全部失效。容器启动时没有完成目录权限配置,导致Airflow运行时无法访问目标目录。
解决方案
1. 清理公共模板的重复command字段
删除x-airflow-common里所有的command字段,因为各个服务(webserver、scheduler、worker)都有自己的启动命令,不需要在公共模板中重复设置。
2. 修改airflow-init服务的权限配置
在airflow-init的command脚本中,添加对/opt/airflow/filepy目录的权限设置,修改后的脚本片段如下:
mkdir -p /sources/logs /sources/dags /sources/plugins chown -R "${AIRFLOW_UID}:0" /sources/{logs,dags,plugins} # 新增该行,给Airflow用户设置filepy目录权限 chown -R "${AIRFLOW_UID}:0" /opt/airflow/filepy exec /entrypoint airflow version
3. 修复宿主机挂载目录权限
在宿主机上执行以下命令,确保挂载的本地目录对Airflow容器的UID(默认50000)开放权限:
sudo chown -R 50000:0 /home/lopp/s3i/infra/sqlserver/BD_NF
4. 重启容器验证
执行命令重启所有Airflow容器:
docker-compose down -v && docker-compose up -d
进入worker容器检查目录权限:
docker-compose exec airflow-worker ls -l /opt/airflow/filepy/unzip/zip
确认文件或目录的所有者/组为Airflow用户(UID 50000),之后再运行DAG即可解决权限问题。
内容的提问来源于stack exchange,提问作者Larissa Kelmer

