ExecutionSpeed opened a new issue #16803:
URL: https://github.com/apache/airflow/issues/16803


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   **Apache Airflow version**: 2.1.1 -- Docker Image: 
`apache/airflow:2.1.1-python3.8`
   
   
   **Kubernetes version (if you are using kubernetes)** (use `kubectl 
version`): Not running on k8s.
   
   **Environment**:
   
   - **Cloud provider or hardware configuration**: DigitalOcean
   - **OS** (e.g. from /etc/os-release): Ubuntu
   - **Kernel** (e.g. `uname -a`): `Linux airflow 5.11.0-22-generic #23-Ubuntu 
SMP Thu Jun 17 00:34:23 UTC 2021 x86_64 x86_64 x86_64 GNU/Linux`
   - **Install tools**: Installed via Docker & Docker Compose following 
instructions from [official docker-compose installation 
docs](https://airflow.apache.org/docs/apache-airflow/stable/start/docker.html#docker-compose-yaml).
   - **Others**: N/A
   
   **What happened**:
   
   <!-- (please include exact error messages if you can) -->
   
   **What you expected to happen**:
   
   <!-- What do you think went wrong? -->
   
   **How to reproduce it**:
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   Running with the `DockerOperator` causes the following error:
   ```
   *** Reading local file: 
/opt/airflow/logs/docker_eod_us_equities/docker_command_sleep/2021-07-04T23:19:48.431208+00:00/2.log
   [2021-07-04 23:49:53,886] {taskinstance.py:896} INFO - Dependencies all met 
for <TaskInstance: docker_eod_us_equities.docker_command_sleep 
2021-07-04T23:19:48.431208+00:00 [queued]>
   [2021-07-04 23:49:53,902] {taskinstance.py:896} INFO - Dependencies all met 
for <TaskInstance: docker_eod_us_equities.docker_command_sleep 
2021-07-04T23:19:48.431208+00:00 [queued]>
   [2021-07-04 23:49:53,903] {taskinstance.py:1087} INFO - 
   
--------------------------------------------------------------------------------
   [2021-07-04 23:49:53,903] {taskinstance.py:1088} INFO - Starting attempt 2 
of 2
   [2021-07-04 23:49:53,903] {taskinstance.py:1089} INFO - 
   
--------------------------------------------------------------------------------
   [2021-07-04 23:49:53,911] {taskinstance.py:1107} INFO - Executing 
<Task(DockerOperator): docker_command_sleep> on 2021-07-04T23:19:48.431208+00:00
   [2021-07-04 23:49:53,914] {standard_task_runner.py:52} INFO - Started 
process 3583 to run task
   [2021-07-04 23:49:53,920] {standard_task_runner.py:76} INFO - Running: 
['***', 'tasks', 'run', 'docker_eod_us_equities', 'docker_command_sleep', 
'2021-07-04T23:19:48.431208+00:00', '--job-id', '52', '--pool', 'default_pool', 
'--raw', '--subdir', 'DAGS_FOLDER/eod_us_equities.py', '--cfg-path', 
'/tmp/tmp5iz14yg9', '--error-file', '/tmp/tmpleaymjfa']
   [2021-07-04 23:49:53,920] {standard_task_runner.py:77} INFO - Job 52: 
Subtask docker_command_sleep
   [2021-07-04 23:49:54,016] {logging_mixin.py:104} INFO - Running 
<TaskInstance: docker_eod_us_equities.docker_command_sleep 
2021-07-04T23:19:48.431208+00:00 [running]> on host 0dff7922cb76
   [2021-07-04 23:49:54,172] {taskinstance.py:1300} INFO - Exporting the 
following env vars:
   AIRFLOW_CTX_DAG_OWNER=***
   AIRFLOW_CTX_DAG_ID=docker_eod_us_equities
   AIRFLOW_CTX_TASK_ID=docker_command_sleep
   AIRFLOW_CTX_EXECUTION_DATE=2021-07-04T23:19:48.431208+00:00
   AIRFLOW_CTX_DAG_RUN_ID=manual__2021-07-04T23:19:48.431208+00:00
   [2021-07-04 23:49:54,205] {docker.py:231} INFO - Starting docker container 
from image alpine
   [2021-07-04 23:49:54,216] {taskinstance.py:1501} ERROR - Task failed with 
exception
   Traceback (most recent call last):
     File 
"/home/airflow/.local/lib/python3.8/site-packages/docker/api/client.py", line 
268, in _raise_for_status
       response.raise_for_status()
     File 
"/home/airflow/.local/lib/python3.8/site-packages/requests/models.py", line 
943, in raise_for_status
       raise HTTPError(http_error_msg, response=self)
   requests.exceptions.HTTPError: 400 Client Error: Bad Request for url: 
http+docker://localhost/v1.30/containers/create?name=docker_command_sleep
   
   During handling of the above exception, another exception occurred:
   
   Traceback (most recent call last):
     File 
"/home/airflow/.local/lib/python3.8/site-packages/airflow/models/taskinstance.py",
 line 1157, in _run_raw_task
       self._prepare_and_execute_task_with_callbacks(context, task)
     File 
"/home/airflow/.local/lib/python3.8/site-packages/airflow/models/taskinstance.py",
 line 1331, in _prepare_and_execute_task_with_callbacks
       result = self._execute_task(context, task_copy)
     File 
"/home/airflow/.local/lib/python3.8/site-packages/airflow/models/taskinstance.py",
 line 1361, in _execute_task
       result = task_copy.execute(context=context)
     File 
"/home/airflow/.local/lib/python3.8/site-packages/airflow/providers/docker/operators/docker.py",
 line 319, in execute
       return self._run_image()
     File 
"/home/airflow/.local/lib/python3.8/site-packages/airflow/providers/docker/operators/docker.py",
 line 237, in _run_image
       self.container = self.cli.create_container(
     File 
"/home/airflow/.local/lib/python3.8/site-packages/docker/api/container.py", 
line 430, in create_container
       return self.create_container_from_config(config, name)
     File 
"/home/airflow/.local/lib/python3.8/site-packages/docker/api/container.py", 
line 441, in create_container_from_config
       return self._result(res, True)
     File 
"/home/airflow/.local/lib/python3.8/site-packages/docker/api/client.py", line 
274, in _result
       self._raise_for_status(response)
     File 
"/home/airflow/.local/lib/python3.8/site-packages/docker/api/client.py", line 
270, in _raise_for_status
       raise create_api_error_from_http_exception(e)
     File "/home/airflow/.local/lib/python3.8/site-packages/docker/errors.py", 
line 31, in create_api_error_from_http_exception
       raise cls(e, response=response, explanation=explanation)
   docker.errors.APIError: 400 Client Error for 
http+docker://localhost/v1.30/containers/create?name=docker_command_sleep: Bad 
Request ("invalid mount config for type "bind": bind source path does not 
exist: /tmp/airflowtmpw5gvv6dj")
   [2021-07-04 23:49:54,222] {taskinstance.py:1544} INFO - Marking task as 
FAILED. dag_id=docker_eod_us_equities, task_id=docker_command_sleep, 
execution_date=20210704T231948, start_date=20210704T234953, 
end_date=20210704T234954
   [2021-07-04 23:49:54,297] {local_task_job.py:151} INFO - Task exited with 
return code 1
   ```
   
   I have even tried with Docker API v1.41 (latest) and same issue. I have 
bound the `/var/run/docker.sock` as a bind mount into the container.
   
   **Docker Compose:**
   ```yaml
   # 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:master-python3.8
   # AIRFLOW_UID                  - User ID in Airflow containers
   #                                Default: 50000
   # AIRFLOW_GID                  - Group 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
     image: ${AIRFLOW_IMAGE_NAME:-apache/airflow:2.1.1-python3.8}
     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: 'false'
       AIRFLOW__SCHEDULER__DAG_DIR_LIST_INTERVAL: 300 # Just to have a fast 
load in the front-end. Do not use it in production with those configurations.
       AIRFLOW__API__AUTH_BACKEND: 'airflow.api.auth.backend.basic_auth'
       AIRFLOW__CORE__ENABLE_XCOM_PICKLING: 'true' # "_run_image of the 
DockerOperator returns now a python string, not a byte string" Ref: 
https://github.com/apache/airflow/issues/13487
       _PIP_ADDITIONAL_REQUIREMENTS: ${_PIP_ADDITIONAL_REQUIREMENTS:-}
     volumes:
       - ./dags:/opt/airflow/dags
       - ./logs:/opt/airflow/logs
       - ./plugins:/opt/airflow/plugins
       - '/var/run/docker.sock:/var/run/docker.sock' # We will pass the Docker 
Deamon as a volume to allow the webserver containers start docker images. Ref: 
https://stackoverflow.com/q/51342810/7024760
     user: '${AIRFLOW_UID:-50000}:${AIRFLOW_GID:-50000}'
     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
       ports:
         - 6379:6379
       healthcheck:
         test: ['CMD', 'redis-cli', 'ping']
         interval: 5s
         timeout: 30s
         retries: 50
       restart: always
   
     airflow-webserver:
       <<: *airflow-common
       command: webserver
       ports:
         - 80:8080
       healthcheck:
         test: ['CMD', 'curl', '--fail', 'http://localhost:80/health']
         interval: 10s
         timeout: 10s
         retries: 5
       restart: always
   
     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
   
     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
       restart: always
   
     airflow-init:
       <<: *airflow-common
       command: version
       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}
   
     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
   
   volumes:
     postgres-db-volume:
   
   ```
   
   **DAG:**
   ```python
   from datetime import datetime, timedelta
   
   import pendulum
   from airflow import DAG
   from airflow.operators.bash_operator import BashOperator
   from airflow.providers.docker.operators.docker import DockerOperator
   from airflow.operators.dummy_operator import DummyOperator
   
   AMERICA_NEW_YORK_TIMEZONE = pendulum.timezone('US/Eastern')
   
   default_args = {
       'owner': 'airflow',
       'description': 'Docker testing',
       'depend_on_past': False,
       'start_date': datetime(2021, 5, 1, tzinfo=AMERICA_NEW_YORK_TIMEZONE),
       'retries': 1,
       'retry_delay': timedelta(minutes=30),
   }
   
   with DAG(
       'docker_test',
       default_args=default_args,
       schedule_interval="15 20 * * *",
       catchup=False,
   ) as dag:
       start_dag = DummyOperator(task_id='start_dag')
   
       end_dag = DummyOperator(task_id='end_dag')
   
       t1 = BashOperator(task_id='print_current_date', bash_command='date')
   
       t2 = DockerOperator(
           task_id='docker_command_sleep',
           image='alpine',
           container_name='docker_command_sleep',
           api_version='1.30',
           auto_remove=True,
           command="/bin/sleep 3",
           docker_url="unix://var/run/docker.sock",
           network_mode="bridge",
           do_xcom_push=True,
       )
   
       start_dag >> t1
   
       t1 >> t2
   
       t2 >> end_dag
   ```
   
   
   **Anything else we need to know**: Problem happens anything `DockerOperator` 
is being used. Not entirely sure why this happening given that the docker sock 
is fully permissive (has `777`) and is bind mounted into the container. When I 
test via *docker-py* client in Python shell under `airflow` user inside the 
container, it works perfectly fine to run all docker-py operations like listing 
running containers and such confirming the mounted docker UNIX socket is 
available and working. However, even with the `docker_url` pointing to the 
docker socket in the above DAG, I am getting this error thrown in above trace.
   
   <!--
   
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   Any relevant logs to include? Put them here in side a detail tag:
   <details><summary>x.log</summary> lots of stuff </details>
   
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