AirFlowのコンテナ設定(Dockerfile)
FROM apache/airflow:2.6.3-python3.8
USER root
RUN apt-get update
&& apt-get install -y
build-essential
default-mysql-client
python3-dev
python-dev default-libmysqlclient-dev
USER airflow
CMD mkdir -p ./dags /.logs ./plugins ./config
AirFlowのコンテナ設定(Docker-compose.yml)
# 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:2.6.3
# AIRFLOW_UID - User ID in Airflow containers
# Default: 50000
# AIRFLOW_PROJ_DIR - Base path to which all the files will be volumed.
# Default: .
# 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.
# Use this option ONLY for quick checks. Installing requirements at container
# startup is done EVERY TIME the service is started.
# A better way is to build a custom image or extend the official image
# as described in https://airflow.apache.org/docs/docker-stack/build.html.
# Default: ''
#
# Feel free to modify this file to suit your needs.
---
version: '3.8'
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.
build: .
expose:
- 18080
environment:
&airflow-common-env
AIRFLOW_UID: 50000
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,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
- ${AIRFLOW_PROJ_DIR:-.}/plugins:/opt/airflow/plugins
user: "${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: 10s
retries: 5
start_period: 5s
restart: always
redis:
image: redis:latest
expose:
- 6379
healthcheck:
test: ["CMD", "redis-cli", "ping"]
interval: 10s
timeout: 30s
retries: 50
start_period: 30s
restart: always
airflow-webserver:
<<: *airflow-common
command: webserver -p 18080
ports:
- "18080:18080"
healthcheck:
test: ["CMD", "curl", "--fail", "http://localhost:18080/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
# ここから
tmpfs:
- '/opt/airflow/'
# ここまでを追加
healthcheck:
test:
- "CMD-SHELL"
- 'celery --app airflow.executors.celery_executor.app inspect ping -d "celery@$${HOSTNAME}"'
interval: 30s
timeout: 10s
retries: 5
start_period: 30s
environment:
<<: *airflow-common-env
# Required to handle warm shutdown of the celery workers properly
# See https://airflow.apache.org/docs/docker-stack/entrypoint.html#signal-propagation
DUMB_INIT_SETSID: "0"
restart: always
depends_on:
<<: *airflow-common-depends-on
airflow-init:
condition: service_completed_successfully
airflow-triggerer:
<<: *airflow-common
command: triggerer
healthcheck:
test: ["CMD-SHELL", 'airflow jobs check --job-type TriggererJob --hostname "$${HOSTNAME}"']
interval: 30s
timeout: 10s
retries: 5
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 "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/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 "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/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:
.envファイル
AIRFLOW_UID=50000
以上がDockerの設定。
カレントに3ファイルはおく必要があり。
注意事項として、上記ファイルは私のサンドボックス設定なので遊び用なので悪しからず。
設定することによって不具合や不利益が生じても自己責任で。
ほぼ、公式の設定に沿っていますがポートだけは変更しています。
で、ここからが本題。VSCodeでデバッグ
初めにいっておきますが、滅茶苦茶しまりました。
前提として、AirFlowのコンテナが起動していることを確認してください。
後、こいつも必要になります。
デバックするには、ホスト側とコンテナ側にもデバック用のプラグインをインストールする必要があるのであしからず。
先に以下の参考資料を読んでおくとよいと思います。
とても参考になりました。m(__)m
下記をコマンド入力。
Remote-Containers: Attach to a Running Container…
すると、稼働しているコンテナがリスト表示されるのでスケジュールを選択する。
コンテナ名は自身の環境によって名前が変わるのでご注意を。
接続されると以下のようになるはず。
コンテナ内のフォルダを移動したい場合は、
ファイルメニューのフォルダを開くを選択。
するとコンテナ内のフォルダが表示されるのでDAGがあるフォルダに移動すればOK。
コンテナのシェルで、airflowの実行モジュールを検索しておく。
自身の環境によって変わるので、参考程度に。
インタプリタの設定をする。
VSCode内でCTRL+Shift+Pで開いてPython Select Interpreterを選択する。
AirFlowのパッケージが入ったインタプリタを選択する。
Dockerでインストールしたのは、3.8なのでここでは3.8を選択している。
launch.json(VSCodeのデバック設定)
{
// IntelliSense を使用して利用可能な属性を学べます。
// 既存の属性の説明をホバーして表示します。
// 詳細情報は次を確認してください: https://go.microsoft.com/fwlink/?linkid=830387
"version": "0.2.0",
"configurations": [
{
"name": "AirFlow DAG テスト",
"type": "debugpy",
"request": "launch",
"program": "/home/airflow/.local/bin/airflow", // <- コンテナにある Airflow までのパス
"console": "integratedTerminal",
// https://airflow.apache.org/docs/apache-airflow/stable/cli-and-env-variables-ref.html
// の
// Test a task instance. This will run a task without checking for dependencies or recording its state in the database
// を参照してね
"args": [
"tasks", // <-- CLI commands(固定。airflowのテストのおまじない)
"test", // <-- CLI commands(固定。airflowのテストのおまじない)
"20240728_tutorial", // <-- 自身が作った dag_id を指定。
"working_hours_calculation", // <-- デバッグしたい自身が作成した task_name を指定。
"2024-07-29" // <-- 実行日時指定。
// DAGに引数を渡したい場合は以下を追記
// , "-t",
// "hogehoge..."
],
}
]
}
一寸面倒なんだけど、AirFlowの公式で示されるテスト手順でテストする。
引数(args)で指定しているのはAirFlowのテストお作法。
詳しくしりたい場合はのこと。
結構弄ることになるんだけど、ポイントは二つ。
dag_idとtask_nameを自身で作成したバッチの名前にするだけ。
きちんと動作すると、ほれこの通り。
ねっ・・・簡単じゃ・・・なかったよ(;´д｀)トホホ
どんだけ調べて苦労したのか分からなかったよ。
変数の値もウォッチで参照できていることが確認できるね。
という自分用のメモでした。
参考程度に。