上文简单的聊聊了解了airflow的概念与使用场景，今天就通过Docker安装一下Airflow,器化在使用中在深入的了解一下airflow有哪些具体的功能。
1Airflow容器化部署
阿里云的安装宿主机环境：
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[1],纯净系统，就没必要卸载旧版本了，聊聊因为是器化云上平台，为防止配置搞坏环境，安装你可以先提前进行快照。聊聊
# 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 # 查看可安装的器化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=<VERSION_STRING> docker-ce-cli=<VERSION_STRING> 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
{ "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，比如阿里云的云服务器提供商安装等等... ], "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+，聊聊在官方的器化docker-compose脚本[2]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，安装因此将此处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用户的聊聊密码 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: ${ _AIRFLOW_WWW_USER_PASSWORD:-airflow} user: "0:0" volumes: - .:/sources airflow-cli: <<: *airflow-common profiles: - debug environment: <<: *airflow-common-env CONNECTION_CHECK_MAX_COUNT: "0" # Workaround for entrypoint issue. See: https://github.com/apache/airflow/issues/16252 command: - bash - -c - airflow flower: <<: *airflow-common command: celery flower ports: - 5555:5555 healthcheck: test: ["CMD", "curl", "--fail", "http://localhost:5555/"] interval: 10s timeout: 10s retries: 5 restart: always depends_on: <<: *airflow-common-depends-on airflow-init: condition: service_completed_successfully 在官方docker-compose.yaml基础上只修改了x-airflow-common,MySQL,Redis相关配置，接下来就应该启动容器了，器化在启动之前，安装需要创建几个持久化目录:
mkdir -p ./dags ./logs ./plugins echo -e "AIRFLOW_UID=$(id -u)" > .env # 注意，此处一定要保证AIRFLOW_UID是普通用户的站群服务器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，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。
参考资料
[1]Install Docker Engine on Ubuntu: https://docs.docker.com/engine/install/ubuntu/
[2]官方docker-compose.yaml: https://airflow.apache.org/docs/apache-airflow/2.2.3/docker-compose.yaml