上文简单的了解了airflow的概念与使用场景，今天就通过Docker安装一下Airflow,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，因为是云上平台，为防止配置搞坏环境，你可以先提前进行快照。
代码语言：javascript复制 # 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
/etc/docker/daemon.json
{
"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
代码语言：javascript复制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 ，在官方的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，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 "$${HOSTNAME}"']
interval: 10s
timeout: 10s
retries: 5
restart: always
depends_on:
<<: *airflow-common-depends-on
airflow-init:
condition: service_completed_successfully
airflow-init:
<<: *airflow-common
entrypoint: /bin/bash
# yamllint disable rule:line-length
command:
- -c
- |
function ver() {
printf "dddd" $${1//./ }
}
airflow_version=$$(gosu airflow airflow version)
airflow_version_comparable=$$(ver $${airflow_version})
min_airflow_version=2.2.0
min_airflow_version_comparable=$$(ver $${min_airflow_version})
if (( airflow_version_comparable < min_airflow_version_comparable )); then
echo
echo -e " 33[1;31mERROR!!!: Too old Airflow version $${airflow_version}!e[0m"
echo "The minimum Airflow version supported: $${min_airflow_version}. Only use this or higher!"
echo
exit 1
fi
if [[ -z "${AIRFLOW_UID}" ]]; then
echo
echo -e " 33[1;33mWARNING!!!: AIRFLOW_UID not set!e[0m"
echo "If you are on Linux, you SHOULD follow the instructions below to set "
echo "AIRFLOW_UID environment variable, otherwise files will be owned by root."
echo "For other operating systems you can get rid of the warning with manually created .env file:"
echo " See: https://airflow.apache.org/docs/apache-airflow/stable/start/docker.html#setting-the-right-airflow-user"
echo
fi
one_meg=1048576
mem_available=$$(($$(getconf _PHYS_PAGES) * $$(getconf PAGE_SIZE) / one_meg))
cpus_available=$$(grep -cE 'cpu[0-9] ' /proc/stat)
disk_available=$$(df / | tail -1 | awk '{print $$4}')
warning_resources="false"
if (( mem_available < 4000 )) ; then
echo
echo -e " 33[1;33mWARNING!!!: Not enough memory available for Docker.e[0m"
echo "At least 4GB of memory required. You have $$(numfmt --to iec $$((mem_available * one_meg)))"
echo
warning_resources="true"
fi
if (( cpus_available < 2 )); then
echo
echo -e " 33[1;33mWARNING!!!: Not enough CPUS available for Docker.e[0m"
echo "At least 2 CPUs recommended. You have $${cpus_available}"
echo
warning_resources="true"
fi
if (( disk_available < one_meg * 10 )); then
echo
echo -e " 33[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 " 33[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: ${_AIRFLOW_WWW_USER_PASSWORD:-airflow}
user: "0:0"
volumes:
- .:/sources
airflow-cli:
<<: *airflow-common
profiles:
- debug
environment:
<<: *airflow-common-env
CONNECTION_CHECK_MAX_COUNT: "0"
# Workaround for entrypoint issue. See: https://github.com/apache/airflow/issues/16252
command:
- bash
- -c
- airflow
flower:
<<: *airflow-common
command: celery flower
ports:
- 5555:5555
healthcheck:
test: ["CMD", "curl", "--fail", "http://localhost:5555/"]
interval: 10s
timeout: 10s
retries: 5
restart: always
depends_on:
<<: *airflow-common-depends-on
airflow-init:
condition: service_completed_successfully
在官方docker-compose.yaml基础上只修改了x-airflow-common,MySQL,Redis相关配置，接下来就应该启动容器了，在启动之前，需要创建几个持久化目录:
mkdir -p ./dags ./logs ./plugins
echo -e "AIRFLOW_UID=$(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
