本 docker-compose 文件在 centos7.9 系统, docker 版本为 24.0.2 上测试的
如果你的 docker 版本低于 24.xxx 就需要手动安装 docker-compose, 高于 24 就不需要安装了, docker 已经自带了
官方文档, 关于 docker 部署
1. 先执行 mkdir -p ./dags ./logs ./plugins ./config ./data/mysql/data ./data/mysql/conf
echo -e "AIRFLOW_UID=$(id -u)" > .env
2. 初始化数据库 docker compose up airflow-init
3. 启动服务docker compose up
附上修改过后的 docker-compose.yaml
version: '3.8'
x-airflow-common:
&airflow-common
image: ${AIRFLOW_IMAGE_NAME:-apache/airflow:2.6.3}
# build: .
environment:
&airflow-common-env
# [core]
AIRFLOW__CORE__EXECUTOR: CeleryExecutor
AIRFLOW__CORE__FERNET_KEY: ''
AIRFLOW__CORE__DAGS_ARE_PAUSED_AT_CREATION: 'true'
AIRFLOW__CORE__LOAD_EXAMPLES: 'false'
AIRFLOW__CORE__DEFAULT_TIMEZONE: "Asia/Shanghai "
# [database]
# AIRFLOW__DATABASE__SQL_ALCHEMY_CONN: postgresql+psycopg2://airflow:airflow@postgres/airflow
AIRFLOW__DATABASE__SQL_ALCHEMY_CONN: mysql+mysqldb://airflow:airflow@mysql/airflow
# [celery]
AIRFLOW__CELERY__RESULT_BACKEND: db+mysql://airflow:airflow@mysql/airflow # 此处替换为mysql连接方式
AIRFLOW__CELERY__BROKER_URL: redis://:admin1234@redis:6379/0
# [webserver]
AIRFLOW__WEBSERVER__BROKER_URL: ""
AIRFLOW__WEBSERVER__DEFAULT_UI_TIMEZONE: "Asia/Shanghai"
AIRFLOW__WEBSERVER__WARN_DEPLOYMENT_EXPOSURE: False
# [smtp]
# smtp_host = email-smtp.amazonaws.com
# smtp_user = AKI
# smtp_password = BCIXc
# smtp_port = 587
# smtp_mail_from = [email protected]
# [api]
AIRFLOW__API__AUTH_BACKENDS: 'airflow.api.auth.backend.basic_auth,airflow.api.auth.backend.session'
# yamllint disable rule:line-length
# Use simple http server on scheduler for health checks
# See https://airflow.apache.org/docs/apache-airflow/stable/administration-and-deployment/logging-monitoring/check-health.html#scheduler-health-check-server
# yamllint enable rule:line-length
AIRFLOW__SCHEDULER__ENABLE_HEALTH_CHECK: 'true'
# WARNING: Use _PIP_ADDITIONAL_REQUIREMENTS option ONLY for a quick checks
# for other purpose (development, test and especially production usage) build/extend Airflow image.
_PIP_ADDITIONAL_REQUIREMENTS: ${_PIP_ADDITIONAL_REQUIREMENTS:-}
volumes:
- ${AIRFLOW_PROJ_DIR:-.}/dags:/opt/airflow/dags
- ${AIRFLOW_PROJ_DIR:-.}/logs:/opt/airflow/logs
- ${AIRFLOW_PROJ_DIR:-.}/config:/opt/airflow/config
- ${AIRFLOW_PROJ_DIR:-.}/plugins:/opt/airflow/plugins
# - ./airflow.cfg:/opt/airflow/airflow.cfg
user: "${AIRFLOW_UID:-50000}:0"
depends_on:
&airflow-common-depends-on
redis:
condition: service_healthy
mysql:
condition: service_healthy
services:
mysql:
image: mysql:8.0.27 # 修改为mysql最新版镜像
environment:
MYSQL_ROOT_PASSWORD: root # MySQL root账号密码
MYSQL_USER: airflow
MYSQL_PASSWORD: airflow # airflow用户的密码
MYSQL_DATABASE: airflow
# docker安全验证
security_opt:
- seccomp:unconfined
command:
- --default-authentication-plugin=mysql_native_password # 指定默认的认证插件
# - --collation-server=utf8_general_ci # 依据官方指定字符集
# - --character-set-server=utf8 # 依据官方指定字符编码
volumes:
- ./data/mysql/data:/var/lib/mysql # 持久化MySQL数据
- ./data/mysql/conf/mysql.cnf:/etc/mysql.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:latest
expose:
- 6379
command: redis-server --requirepass admin1234 # redis-server开启密码认证
healthcheck:
test: [ "CMD", "redis-cli", "-a","admin1234","ping" ]
interval: 10s
timeout: 30s
retries: 50
start_period: 30s
restart: always
airflow-webserver:
<<: *airflow-common
command: webserver
ports:
- "8083:8080"
healthcheck:
test: [ "CMD", "curl", "--fail", "http://localhost:8080/health" ]
interval: 30s
timeout: 10s
retries: 5
start_period: 30s
restart: always
depends_on:
<<: *airflow-common-depends-on
airflow-init:
condition: service_completed_successfully
airflow-scheduler:
<<: *airflow-common
command: scheduler
healthcheck:
test: [ "CMD", "curl", "--fail", "http://localhost:8974/health" ]
interval: 30s
timeout: 10s
retries: 5
start_period: 30s
restart: always
depends_on:
<<: *airflow-common-depends-on
airflow-init:
condition: service_completed_successfully
airflow-worker:
<<: *airflow-common
command: celery worker
user: 'airflow'
healthcheck:
test:
- "CMD-SHELL"
- 'celery --app airflow.executors.celery_executor.app inspect ping -d "celery@$${HOSTNAME}"'
interval: 30s
timeout: 10s
retries: 1
start_period: 30s
environment:
<<: *airflow-common-env
# Required to handle warm shutdown of the celery workers properly
# See https://airflow.apache.org/docs/docker-stack/entrypoint.html#signal-propagation
DUMB_INIT_SETSID: "0"
restart: always
depends_on:
<<: *airflow-common-depends-on
airflow-init:
condition: service_completed_successfully
airflow-triggerer:
<<: *airflow-common
command: triggerer
user: 'airflow'
healthcheck:
test: [ "CMD-SHELL", 'airflow jobs check --job-type TriggererJob --hostname "$${HOSTNAME}"' ]
interval: 30s
timeout: 10s
retries: 1
start_period: 30s
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/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
# 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:
- ${AIRFLOW_PROJ_DIR:-.}:/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: 30s
timeout: 10s
retries: 5
start_period: 30s
restart: always
depends_on:
<<: *airflow-common-depends-on
airflow-init:
condition: service_completed_successfully
volumes:
postgres-db-volume:
标签:__,8.0,AIRFLOW,airflow,redis,Airflow,mysql,docker,任务调度
From: https://www.cnblogs.com/Dr-wei/p/17611970.html