Docker 气流图像本地主机错误 (Windows 10)
Docker localhost error with airflow image (Windows 10)
我正在尝试使用 docker 运行 气流图像。前一段时间它工作正常。但是，我 运行 localhost 上的其他应用程序没有使用 docker（使用 VisualStudio），当我重新 运行 我的气流之后，localhost 不再工作.
我尝试重新安装 Docker 和 AirFlow imagem，但没有成功。
我正在使用 Apache 网站上提供的 Airflow 2.1.4 docker imagem。
我的 AirFlow 在 localhost:8080 上设置为 运行。有没有办法知道另一个应用程序是否正在使用 8080?
我不知道有什么必要的信息可以post在这里澄清我的问题。我相信检查是否有其他应用程序绑定到 localhost:8080 上的 运行（visual studio 的实例或 docker 本身）可以解决问题。但是如何做到这一点？
我的 docker-compose.yaml 文件：
# 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:2.1.4
# AIRFLOW_UID - User ID in Airflow containers
# Default: 50000
# AIRFLOW_GID - Group ID in Airflow containers
# Default: 0
#
# 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:2.1.4}
# 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}:${AIRFLOW_GID:-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:
- 5000:8080
healthcheck:
test: ["CMD", "curl", "--fail", "http://localhost:5000/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-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=2.1.0
min_airflow_version_comparable=$$(ver $${min_airflow_version})
if (( airflow_version_comparable < min_airflow_version_comparable )); then
echo
echo -e "3[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 "3[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 and AIRFLOW_GID environment variables, 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=$$(df / | tail -1 | awk '{print $}')
warning_resources="false"
if (( mem_available < 4000 )) ; then
echo
echo -e "3[1;33mWARNING!!!: Not enough memory available for Docker.\e[0m"
echo "At least 4GB of memory required. You have $$(numfmt --to iec $$((mem_available * one_meg)))"
echo
warning_resources="true"
fi
if (( cpus_available < 2 )); then
echo
echo -e "3[1;33mWARNING!!!: Not enough CPUS available for Docker.\e[0m"
echo "At least 2 CPUs recommended. You have $${cpus_available}"
echo
warning_resources="true"
fi
if (( disk_available < one_meg * 10 )); then
echo
echo -e "3[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 "3[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}:${AIRFLOW_GID}" /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:${AIRFLOW_GID:-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:
我的气流网络服务器日志：
airflow-webserver_1 | ....................
airflow-webserver_1 | ERROR! Maximum number of retries (20) reached.
airflow-webserver_1 |
airflow-webserver_1 | Last check result:
airflow-webserver_1 | $ airflow db check
airflow-webserver_1 | Unable to load the config, contains a configuration error.
airflow-webserver_1 | Traceback (most recent call last):
airflow-webserver_1 | File "/usr/local/lib/python3.6/pathlib.py", line 1248, in mkdir
airflow-webserver_1 | self._accessor.mkdir(self, mode)
airflow-webserver_1 | File "/usr/local/lib/python3.6/pathlib.py", line 387, in wrapped
airflow-webserver_1 | return strfunc(str(pathobj), *args)
airflow-webserver_1 | FileNotFoundError: [Errno 2] No such file or directory: '/opt/airflow/logs/scheduler/2021-09-20'
airflow-webserver_1 |
airflow-webserver_1 | During handling of the above exception, another exception occurred:
airflow-webserver_1 |
airflow-webserver_1 | Traceback (most recent call last):
airflow-webserver_1 | File "/usr/local/lib/python3.6/logging/config.py", line 565, in configure
airflow-webserver_1 | handler = self.configure_handler(handlers[name])
airflow-webserver_1 | File "/usr/local/lib/python3.6/logging/config.py", line 738, in configure_handler
airflow-webserver_1 | result = factory(**kwargs)
airflow-webserver_1 | File "/home/airflow/.local/lib/python3.6/site-packages/airflow/utils/log/file_processor_handler.py", line 47, in __init__
airflow-webserver_1 | Path(self._get_log_directory()).mkdir(parents=True, exist_ok=True)
airflow-webserver_1 | File "/usr/local/lib/python3.6/pathlib.py", line 1252, in mkdir
airflow-webserver_1 | self.parent.mkdir(parents=True, exist_ok=True)
airflow-webserver_1 | File "/usr/local/lib/python3.6/pathlib.py", line 1248, in mkdir
airflow-webserver_1 | self._accessor.mkdir(self, mode)
airflow-webserver_1 | File "/usr/local/lib/python3.6/pathlib.py", line 387, in wrapped
airflow-webserver_1 | return strfunc(str(pathobj), *args)
airflow-webserver_1 | PermissionError: [Errno 13] Permission denied: '/opt/airflow/logs/scheduler'
airflow-webserver_1 |
airflow-webserver_1 | During handling of the above exception, another exception occurred:
airflow-webserver_1 |
airflow-webserver_1 | Traceback (most recent call last):
airflow-webserver_1 | File "/home/airflow/.local/bin/airflow", line 5, in <module>
airflow-webserver_1 | from airflow.__main__ import main
airflow-webserver_1 | File "/home/airflow/.local/lib/python3.6/site-packages/airflow/__init__.py", line 46, in <module>
airflow-webserver_1 | settings.initialize()
airflow-webserver_1 | File "/home/airflow/.local/lib/python3.6/site-packages/airflow/settings.py", line 444, in initialize
airflow-webserver_1 | LOGGING_CLASS_PATH = configure_logging()
airflow-webserver_1 | File "/home/airflow/.local/lib/python3.6/site-packages/airflow/logging_config.py", line 73, in configure_logging
airflow-webserver_1 | raise e
airflow-webserver_1 | File "/home/airflow/.local/lib/python3.6/site-packages/airflow/logging_config.py", line 68, in configure_logging
airflow-webserver_1 | dictConfig(logging_config)
airflow-webserver_1 | File "/usr/local/lib/python3.6/logging/config.py", line 802, in dictConfig
airflow-webserver_1 | dictConfigClass(config).configure()
airflow-webserver_1 | File "/usr/local/lib/python3.6/logging/config.py", line 573, in configure
airflow-webserver_1 | '%r: %s' % (name, e))
airflow-webserver_1 | ValueError: Unable to configure handler 'processor': [Errno 13] Permission denied: '/opt/airflow/logs/scheduler'
airflow-webserver_1 |
airflow-webserver_1 exited with code 1
我在 windows 10.
上使用 Docker 桌面
我的 docker 容器的屏幕 -ps 显示 localhost 绑定在 8080 运行ning Unhealthy
编辑：
要检查 运行 已经在 docker 中的所有容器，您可以 运行 以下命令并检查是否有人在使用端口 8080：
docker container ls
通常与 Web 开发相关的所有内容都默认部署在 80/8080/443/8443 上，因此这里最好的解决方法是将 docker 容器的端口绑定更改为不同于 8080 的其他端口。
如果你使用“docker”命令，你会看到类似“-p local_port:container_port”的选项，你可以为“local_port”设置另一个端口为了不将容器 8080 绑定到您本地的 8080。这样您将获得所有内容 运行ning
为了帮助您多一点，我们需要您的 OS 至少向您发送一个有效的命令来检查您是否有任何进程使用 8080 端口以及如何唤醒您的 docker图像（参数、命令、docker-撰写...）
我使用以下命令检查容器运行状况日志：
docker inspect --format='{{json .State.Health}}' dags_airflow-webserver_1
显示错误：
0curl: (7) Failed to connect to localhost port 5000: Connection refused\n"
我在 Whosebug 上搜索并找到了 sammue 问题
我解决问题的方法是 运行 VSCode 和 Docker Desktop作为管理员
您服务器的日志显示
FileNotFoundError: [Errno 2] No such file or directory:
'/opt/airflow/logs/scheduler/2021-09-20'
和
PermissionError: [Errno 13] Permission denied:
'/opt/airflow/logs/scheduler'
您的撰写文件包含
volumes:
- ./dags:/opt/airflow/dags
- ./logs:/opt/airflow/logs
- ./plugins:/opt/airflow/plugins
user: "${AIRFLOW_UID:-50000}:${AIRFLOW_GID:-0}"
这意味着您的所有容器都共享主机中的多个文件夹，并且 运行 作为环境变量 AIRFLOW_UID 的任何用户。可能发生了两件事之一-
- 该环境变量已更改。它已设置，现在未设置，或类似的东西或
- 您与您的用户对这些文件夹进行了
chown。这可能是问题所在。特别是 dags 文件夹几乎肯定归您的个人用户所有，并且 uid 50000 没有读取这些文件的权限。如果这些文件归 50000 人所有，您将无法自己读取它们。对于本地工作，我会推荐 运行 这些命令，将 AIRFLOW_UID 设置为您的用户 ID，例如 AIRFLOW_UID=$(id -u) docker-compose up.
现在......我不在 Windows 上开发，我知道我刚刚给你的行在 Windows 上不起作用，并且文件系统权限与 docker-desktop 甚至在它的不同版本之间。但是您的问题将归结为这些共享绑定装载文件夹的权限。
我正在尝试使用 docker 运行 气流图像。前一段时间它工作正常。但是，我 运行 localhost 上的其他应用程序没有使用 docker（使用 VisualStudio），当我重新 运行 我的气流之后，localhost 不再工作.
我尝试重新安装 Docker 和 AirFlow imagem，但没有成功。
我正在使用 Apache 网站上提供的 Airflow 2.1.4 docker imagem。
我的 AirFlow 在 localhost:8080 上设置为 运行。有没有办法知道另一个应用程序是否正在使用 8080?
我不知道有什么必要的信息可以post在这里澄清我的问题。我相信检查是否有其他应用程序绑定到 localhost:8080 上的 运行（visual studio 的实例或 docker 本身）可以解决问题。但是如何做到这一点？
我的 docker-compose.yaml 文件：
# 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:2.1.4
# AIRFLOW_UID - User ID in Airflow containers
# Default: 50000
# AIRFLOW_GID - Group ID in Airflow containers
# Default: 0
#
# 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:2.1.4}
# 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}:${AIRFLOW_GID:-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:
- 5000:8080
healthcheck:
test: ["CMD", "curl", "--fail", "http://localhost:5000/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@$${HOSTNAME}"'
interval: 10s
timeout: 10s
retries: 5
environment:
<<: *airflow-common-env
# Required to handle warm shutdown of the celery workers properly
# See https://airflow.apache.org/docs/docker-stack/entrypoint.html#signal-propagation
DUMB_INIT_SETSID: "0"
restart: always
depends_on:
<<: *airflow-common-depends-on
airflow-init:
condition: service_completed_successfully
airflow-init:
<<: *airflow-common
entrypoint: /bin/bash
# yamllint disable rule:line-length
command:
- -c
- |
function ver() {
printf "%04d%04d%04d%04d" $${1//./ }
}
airflow_version=$$(gosu airflow airflow version)
airflow_version_comparable=$$(ver $${airflow_version})
min_airflow_version=2.1.0
min_airflow_version_comparable=$$(ver $${min_airflow_version})
if (( airflow_version_comparable < min_airflow_version_comparable )); then
echo
echo -e "3[1;31mERROR!!!: Too old Airflow version $${airflow_version}!\e[0m"
echo "The minimum Airflow version supported: $${min_airflow_version}. Only use this or higher!"
echo
exit 1
fi
if [[ -z "${AIRFLOW_UID}" ]]; then
echo
echo -e "3[1;33mWARNING!!!: AIRFLOW_UID not set!\e[0m"
echo "If you are on Linux, you SHOULD follow the instructions below to set "
echo "AIRFLOW_UID and AIRFLOW_GID environment variables, otherwise files will be owned by root."
echo "For other operating systems you can get rid of the warning with manually created .env file:"
echo " See: https://airflow.apache.org/docs/apache-airflow/stable/start/docker.html#setting-the-right-airflow-user"
echo
fi
one_meg=1048576
mem_available=$$(($$(getconf _PHYS_PAGES) * $$(getconf PAGE_SIZE) / one_meg))
cpus_available=$$(grep -cE 'cpu[0-9]+' /proc/stat)
disk_available=$$(df / | tail -1 | awk '{print $}')
warning_resources="false"
if (( mem_available < 4000 )) ; then
echo
echo -e "3[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 "3[1;33mWARNING!!!: Not enough CPUS available for Docker.\e[0m"
echo "At least 2 CPUs recommended. You have $${cpus_available}"
echo
warning_resources="true"
fi
if (( disk_available < one_meg * 10 )); then
echo
echo -e "3[1;33mWARNING!!!: Not enough Disk space available for Docker.\e[0m"
echo "At least 10 GBs recommended. You have $$(numfmt --to iec $$((disk_available * 1024 )))"
echo
warning_resources="true"
fi
if [[ $${warning_resources} == "true" ]]; then
echo
echo -e "3[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 "${AIRFLOW_UID}:${AIRFLOW_GID}" /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: ${_AIRFLOW_WWW_USER_PASSWORD:-airflow}
user: "0:${AIRFLOW_GID:-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:
我的气流网络服务器日志：
airflow-webserver_1 | ....................
airflow-webserver_1 | ERROR! Maximum number of retries (20) reached.
airflow-webserver_1 |
airflow-webserver_1 | Last check result:
airflow-webserver_1 | $ airflow db check
airflow-webserver_1 | Unable to load the config, contains a configuration error.
airflow-webserver_1 | Traceback (most recent call last):
airflow-webserver_1 | File "/usr/local/lib/python3.6/pathlib.py", line 1248, in mkdir
airflow-webserver_1 | self._accessor.mkdir(self, mode)
airflow-webserver_1 | File "/usr/local/lib/python3.6/pathlib.py", line 387, in wrapped
airflow-webserver_1 | return strfunc(str(pathobj), *args)
airflow-webserver_1 | FileNotFoundError: [Errno 2] No such file or directory: '/opt/airflow/logs/scheduler/2021-09-20'
airflow-webserver_1 |
airflow-webserver_1 | During handling of the above exception, another exception occurred:
airflow-webserver_1 |
airflow-webserver_1 | Traceback (most recent call last):
airflow-webserver_1 | File "/usr/local/lib/python3.6/logging/config.py", line 565, in configure
airflow-webserver_1 | handler = self.configure_handler(handlers[name])
airflow-webserver_1 | File "/usr/local/lib/python3.6/logging/config.py", line 738, in configure_handler
airflow-webserver_1 | result = factory(**kwargs)
airflow-webserver_1 | File "/home/airflow/.local/lib/python3.6/site-packages/airflow/utils/log/file_processor_handler.py", line 47, in __init__
airflow-webserver_1 | Path(self._get_log_directory()).mkdir(parents=True, exist_ok=True)
airflow-webserver_1 | File "/usr/local/lib/python3.6/pathlib.py", line 1252, in mkdir
airflow-webserver_1 | self.parent.mkdir(parents=True, exist_ok=True)
airflow-webserver_1 | File "/usr/local/lib/python3.6/pathlib.py", line 1248, in mkdir
airflow-webserver_1 | self._accessor.mkdir(self, mode)
airflow-webserver_1 | File "/usr/local/lib/python3.6/pathlib.py", line 387, in wrapped
airflow-webserver_1 | return strfunc(str(pathobj), *args)
airflow-webserver_1 | PermissionError: [Errno 13] Permission denied: '/opt/airflow/logs/scheduler'
airflow-webserver_1 |
airflow-webserver_1 | During handling of the above exception, another exception occurred:
airflow-webserver_1 |
airflow-webserver_1 | Traceback (most recent call last):
airflow-webserver_1 | File "/home/airflow/.local/bin/airflow", line 5, in <module>
airflow-webserver_1 | from airflow.__main__ import main
airflow-webserver_1 | File "/home/airflow/.local/lib/python3.6/site-packages/airflow/__init__.py", line 46, in <module>
airflow-webserver_1 | settings.initialize()
airflow-webserver_1 | File "/home/airflow/.local/lib/python3.6/site-packages/airflow/settings.py", line 444, in initialize
airflow-webserver_1 | LOGGING_CLASS_PATH = configure_logging()
airflow-webserver_1 | File "/home/airflow/.local/lib/python3.6/site-packages/airflow/logging_config.py", line 73, in configure_logging
airflow-webserver_1 | raise e
airflow-webserver_1 | File "/home/airflow/.local/lib/python3.6/site-packages/airflow/logging_config.py", line 68, in configure_logging
airflow-webserver_1 | dictConfig(logging_config)
airflow-webserver_1 | File "/usr/local/lib/python3.6/logging/config.py", line 802, in dictConfig
airflow-webserver_1 | dictConfigClass(config).configure()
airflow-webserver_1 | File "/usr/local/lib/python3.6/logging/config.py", line 573, in configure
airflow-webserver_1 | '%r: %s' % (name, e))
airflow-webserver_1 | ValueError: Unable to configure handler 'processor': [Errno 13] Permission denied: '/opt/airflow/logs/scheduler'
airflow-webserver_1 |
airflow-webserver_1 exited with code 1
我在 windows 10.
上使用 Docker 桌面我的 docker 容器的屏幕 -ps 显示 localhost 绑定在 8080 运行ning Unhealthy
编辑：
要检查 运行 已经在 docker 中的所有容器，您可以 运行 以下命令并检查是否有人在使用端口 8080：
docker container ls
通常与 Web 开发相关的所有内容都默认部署在 80/8080/443/8443 上，因此这里最好的解决方法是将 docker 容器的端口绑定更改为不同于 8080 的其他端口。
如果你使用“docker”命令，你会看到类似“-p local_port:container_port”的选项，你可以为“local_port”设置另一个端口为了不将容器 8080 绑定到您本地的 8080。这样您将获得所有内容 运行ning
为了帮助您多一点，我们需要您的 OS 至少向您发送一个有效的命令来检查您是否有任何进程使用 8080 端口以及如何唤醒您的 docker图像（参数、命令、docker-撰写...）
我使用以下命令检查容器运行状况日志：
docker inspect --format='{{json .State.Health}}' dags_airflow-webserver_1
显示错误：
0curl: (7) Failed to connect to localhost port 5000: Connection refused\n"
我在 Whosebug 上搜索并找到了 sammue 问题
我解决问题的方法是 运行 VSCode 和 Docker Desktop作为管理员
您服务器的日志显示
FileNotFoundError: [Errno 2] No such file or directory: '/opt/airflow/logs/scheduler/2021-09-20'
和
PermissionError: [Errno 13] Permission denied: '/opt/airflow/logs/scheduler'
您的撰写文件包含
volumes:
- ./dags:/opt/airflow/dags
- ./logs:/opt/airflow/logs
- ./plugins:/opt/airflow/plugins
user: "${AIRFLOW_UID:-50000}:${AIRFLOW_GID:-0}"
这意味着您的所有容器都共享主机中的多个文件夹，并且 运行 作为环境变量 AIRFLOW_UID 的任何用户。可能发生了两件事之一-
- 该环境变量已更改。它已设置，现在未设置，或类似的东西或
- 您与您的用户对这些文件夹进行了
chown。这可能是问题所在。特别是dags文件夹几乎肯定归您的个人用户所有，并且uid 50000没有读取这些文件的权限。如果这些文件归 50000 人所有，您将无法自己读取它们。对于本地工作，我会推荐 运行 这些命令，将AIRFLOW_UID设置为您的用户 ID，例如AIRFLOW_UID=$(id -u) docker-compose up.
现在......我不在 Windows 上开发，我知道我刚刚给你的行在 Windows 上不起作用，并且文件系统权限与 docker-desktop 甚至在它的不同版本之间。但是您的问题将归结为这些共享绑定装载文件夹的权限。