在 Docker 上快速运行 Apache Airflow 2.2.4

Docker 安装 Apache Airflow

参考资料
安装依赖
快速运行 Apache Airflow 2.2.4
清除环境信息

参考资料

Running Airflow in Docker

安装依赖

Docker Engine
Docker Composite

快速运行 Apache Airflow 2.2.4

在 Docker 使用 CeleryExecutor（一种统计 worker 数量的途径）快速运行 Apache Airflow

1. 下载 docker-compose.yaml

命令：



# 创建一个目录

mkdir -p /home/public/Soft/airflow

cd /home/public/Soft/airflow

# 下载

curl -LfO 'https://airflow.apache.org/docs/apache-airflow/2.2.4/docker-compose.yaml'

这个文件包含了多个服务的定义：

airflow-scheduler - The scheduler monitors all tasks and DAGs, then triggers the task instances once their dependencies are complete.
airflow-webserver - The webserver is available at http://localhost:8080.
airflow-worker - The worker that executes the tasks given by the scheduler.
airflow-init - The initialization service.
flower - The flower app for monitoring the environment. It is available at http://localhost:5555.
postgres - The database.
redis - The redis - broker that forwards messages from scheduler to worker.

docker-compose.yaml 文件内容如下：

# 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:2.2.4

# 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:2.2.4}

  # build: .

  environment:

    &airflow-common-env

    AIRFLOW__CORE__EXECUTOR: CeleryExecutor

    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_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

    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=$$(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

volumes:

  postgres-db-volume:

2. 在 docker-compose.yaml 同级目录下创建文件夹

在 docker-compose.yaml 同级目录下，创建 dags logs plugins文件夹

cd /home/public/Soft/airflow

mkdir -p ./dags

mkdir -p ./logs

mkdir -p ./plugins

dags logs plugins文件夹作用：

./dags - you can put your DAG files here.
./logs - contains logs from task execution and scheduler.
./plugins - you can put your custom plugins here.

3. 初始化环境

初始化环境，就是添加几个文件夹。

3.1 设置正确的用户

命令：

cd /home/public/Soft/airflow

echo -e "AIRFLOW_UID=$(id -u)" > .env

其中，AIRFLOW_UID 是 Docker Compose 环境变量，具体请看（https://airflow.apache.org/docs/apache-airflow/2.2.4/start/docker.html#docker-compose-env-variables ）。

生成的 .env 文件内容可能如下：

AIRFLOW_UID=50000

3.2 初始化数据库

cd /home/public/Soft/airflow

docker-compose up airflow-init

控制台可能打印如下内容：

airflow-init_1       | Upgrades done

airflow-init_1       | Admin user airflow created

airflow-init_1       | 2.2.4

start_airflow-init_1 exited with code 0

初始化，默认的 Airflow 的登陆用户和密码： airflow airflow

4. 运行 airflow

cd /home/public/Soft/airflow

docker-compose up

5. 访问环境

有3中方式访问环境：命令行，浏览器访问，REST API。

5.1 命令行

下载 airflow.sh

curl -LfO 'https://airflow.apache.org/docs/apache-airflow/2.2.4/airflow.sh'

chmod +x airflow.sh

airflow.sh 脚本内容如下：

#!/usr/bin/env bash

# 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.

#

# Run airflow command in container

#

PROJECT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"

set -euo pipefail

export COMPOSE_FILE="${PROJECT_DIR}/docker-compose.yaml"

if [ $# -gt 0 ]; then

    exec docker-compose run --rm airflow-cli "${@}"

else

    exec docker-compose run --rm airflow-cli

fi

使用 airflow.sh 可以快速执行命令，例如：

arflow.sh info

5.2 浏览器访问

浏览器访问 http://localhost:8080
默认登录名和密码： airflow airflow

5.3 给 REST API 发请求

使用 curl 发请求：

ENDPOINT_URL="http://localhost:8080/"

curl -X GET  \

    --user "airflow:airflow" \

    "${ENDPOINT_URL}/api/v1/pools"

清除容器

清除容器，卷等，命令如下：

docker-compose down --volumes --rmi all

清除环境信息

以上是快速启动配置，如果需要定制化配置，则可以先清除环境信息

停止容器

cd /home/public/Soft/airflow

docker-compose down --volumes --remove-orphans

删除下载目录和 docker-compose.yaml

cd /home/public/Soft/airflow

rm -rf *

重新下载 docker-compose.yaml

curl -LfO 'https://airflow.apache.org/docs/apache-airflow/2.2.4/docker-compose.yaml'

从开头重新执行指令

巴特西