I am using docker compose to run airflow, by using the yaml file from .10.5/docker-compose.yaml.
Here is the docker-compose yaml file that I used:
# 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
#
# .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:2.10.5
# 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 .html.
# Default: ''
#
# Feel free to modify this file to suit your needs.
---
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:2.10.5}
# build: .
environment:
&airflow-common-env
AIRFLOW__CORE__EXECUTOR: CeleryExecutor
AIRFLOW__DATABASE__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 .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:-}
# The following line can be used to set a custom config file, stored in the local config folder
# If you want to use it, outcomment it and replace airflow.cfg with the name of your config file
# AIRFLOW_CONFIG: '/opt/airflow/config/airflow.cfg'
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:
# Redis is limited to 7.2-bookworm due to licencing change
# /
image: redis:7.2-bookworm
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
ports:
- "8080:8080"
healthcheck:
test: ["CMD", "curl", "--fail", "http://localhost:8080/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
healthcheck:
# yamllint disable rule:line-length
test:
- "CMD-SHELL"
- 'celery --app airflow.providers.celery.executors.celery_executor.app inspect ping -d "celery@$${HOSTNAME}" || celery --app airflow.executors.celery_executor.app inspect ping -d "celery@$${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 .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 "$${HOSTNAME}"']
interval: 30s
timeout: 10s
retries: 5
start_period: 30s
restart: always
depends_on:
<<: *airflow-common-depends-on
airflow-init:
condition: service_completed_successfully
airflow-init:
<<: *airflow-common
entrypoint: /bin/bash
# yamllint disable rule:line-length
command:
- -c
- |
if [[ -z "${AIRFLOW_UID}" ]]; then
echo
echo -e "\033[1;33mWARNING!!!: AIRFLOW_UID not set!\e[0m"
echo "If you are on Linux, you SHOULD follow the instructions below to set "
echo "AIRFLOW_UID environment variable, otherwise files will be owned by root."
echo "For other operating systems you can get rid of the warning with manually created .env file:"
echo " See: .html#setting-the-right-airflow-user"
echo
fi
one_meg=1048576
mem_available=$$(($$(getconf _PHYS_PAGES) * $$(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 " .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_MIGRATE: '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:
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: /
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:
Here is the airflow dag that I used to run:
from airflow import DAG
from airflow.decorators import dag, task
from airflow.providers.mysql.hooks.mysql import MySqlHook
from airflow.providers.oracle.hooks.oracle import OracleHook
from airflow.models import Variable
from datetime import datetime
from include.dm_logger import DMLogger, create_dag_logger
def get_extract_start_date():
logger = create_dag_logger("data_extract_init")
data_extract_connection = Variable.get("data_extract_connection")
oracle_connection = Variable.get("oracle_connection")
mysql_hook = MySqlHook(mysql_conn_id=data_extract_connection)
oracle_hook = OracleHook(oracle_conn_id=oracle_connection)
table_names = ['repo_1', 'repo_2', 'tx_user_details']
for table_name in table_names:
sql = f"SELECT CREATE_DATE FROM {table_name} ORDER BY create_date FETCH FIRST 1 ROWS only"
result = oracle_hook.get_first(sql=sql)
start_time = result[0].isoformat()
mysql_sql = "update extract_preference set remarks = %s where table_name=%s; "
params = (start_time,table_name)
mysql_hook.run(mysql_sql, parameters=params)
with DAG(
'data_extract_init',
schedule=None,
start_date=datetime(2025,1,1),
schedule_interval=None,
catchup=False,
) as dag:
@task
def init_migration():
""""""
get_extract_start_date()
init_migration()
When I run it, it shows error:
Broken DAG: [/opt/airflow/dags/staging/data_extract_init_dag.py]
Traceback (most recent call last):
File "<frozen importlib._bootstrap>", line 488, in _call_with_frames_removed
File "/opt/airflow/dags/staging/data_extract_init_dag.py", line 96, in <module>
from airflow.providers.oracle.hooks.oracle import OracleHook
ModuleNotFoundError: No module named 'airflow.providers.oracle'
I follow the apache-airflow-providers-oracle installation guide (.html#provider-package), and used pip install apache-airflow-providers-oracle command to install it. After that I used docker compose restart to restart the container.
I did go into the airflow container (using docker exec -it <airflow-container-id> /bin/bash) to verify that I have installed the apache-airflow-providers-oracle, by using the airflow providers list | grep oracle command.
However, I still saw the same error.
Why is the airflow container unable to detect that I have installed the apache-airflow-providers-oracle? Am I missing any step?
I am using docker compose to run airflow, by using the yaml file from https://airflow.apache./docs/apache-airflow/2.10.5/docker-compose.yaml.
Here is the docker-compose yaml file that I used:
# 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./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:2.10.5
# 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./docs/docker-stack/build.html.
# Default: ''
#
# Feel free to modify this file to suit your needs.
---
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:2.10.5}
# build: .
environment:
&airflow-common-env
AIRFLOW__CORE__EXECUTOR: CeleryExecutor
AIRFLOW__DATABASE__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./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:-}
# The following line can be used to set a custom config file, stored in the local config folder
# If you want to use it, outcomment it and replace airflow.cfg with the name of your config file
# AIRFLOW_CONFIG: '/opt/airflow/config/airflow.cfg'
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:
# Redis is limited to 7.2-bookworm due to licencing change
# https://redis.io/blog/redis-adopts-dual-source-available-licensing/
image: redis:7.2-bookworm
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
ports:
- "8080:8080"
healthcheck:
test: ["CMD", "curl", "--fail", "http://localhost:8080/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
healthcheck:
# yamllint disable rule:line-length
test:
- "CMD-SHELL"
- 'celery --app airflow.providers.celery.executors.celery_executor.app inspect ping -d "celery@$${HOSTNAME}" || celery --app airflow.executors.celery_executor.app inspect ping -d "celery@$${HOSTNAME}"'
interval: 30s
timeout: 10s
retries: 5
start_period: 30s
environment:
<<: *airflow-common-env
# Required to handle warm shutdown of the celery workers properly
# See https://airflow.apache./docs/docker-stack/entrypoint.html#signal-propagation
DUMB_INIT_SETSID: "0"
restart: always
depends_on:
<<: *airflow-common-depends-on
airflow-init:
condition: service_completed_successfully
airflow-triggerer:
<<: *airflow-common
command: triggerer
healthcheck:
test: ["CMD-SHELL", 'airflow jobs check --job-type TriggererJob --hostname "$${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
- |
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./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 "\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./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_MIGRATE: '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/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/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:
Here is the airflow dag that I used to run:
from airflow import DAG
from airflow.decorators import dag, task
from airflow.providers.mysql.hooks.mysql import MySqlHook
from airflow.providers.oracle.hooks.oracle import OracleHook
from airflow.models import Variable
from datetime import datetime
from include.dm_logger import DMLogger, create_dag_logger
def get_extract_start_date():
logger = create_dag_logger("data_extract_init")
data_extract_connection = Variable.get("data_extract_connection")
oracle_connection = Variable.get("oracle_connection")
mysql_hook = MySqlHook(mysql_conn_id=data_extract_connection)
oracle_hook = OracleHook(oracle_conn_id=oracle_connection)
table_names = ['repo_1', 'repo_2', 'tx_user_details']
for table_name in table_names:
sql = f"SELECT CREATE_DATE FROM {table_name} ORDER BY create_date FETCH FIRST 1 ROWS only"
result = oracle_hook.get_first(sql=sql)
start_time = result[0].isoformat()
mysql_sql = "update extract_preference set remarks = %s where table_name=%s; "
params = (start_time,table_name)
mysql_hook.run(mysql_sql, parameters=params)
with DAG(
'data_extract_init',
schedule=None,
start_date=datetime(2025,1,1),
schedule_interval=None,
catchup=False,
) as dag:
@task
def init_migration():
""""""
get_extract_start_date()
init_migration()
When I run it, it shows error:
Broken DAG: [/opt/airflow/dags/staging/data_extract_init_dag.py]
Traceback (most recent call last):
File "<frozen importlib._bootstrap>", line 488, in _call_with_frames_removed
File "/opt/airflow/dags/staging/data_extract_init_dag.py", line 96, in <module>
from airflow.providers.oracle.hooks.oracle import OracleHook
ModuleNotFoundError: No module named 'airflow.providers.oracle'
I follow the apache-airflow-providers-oracle installation guide (https://airflow.apache./docs/apache-airflow-providers-oracle/stable/index.html#provider-package), and used pip install apache-airflow-providers-oracle command to install it. After that I used docker compose restart to restart the container.
I did go into the airflow container (using docker exec -it <airflow-container-id> /bin/bash) to verify that I have installed the apache-airflow-providers-oracle, by using the airflow providers list | grep oracle command.
However, I still saw the same error.
Why is the airflow container unable to detect that I have installed the apache-airflow-providers-oracle? Am I missing any step?
Share edited Mar 10 at 12:27 maantarng asked Mar 10 at 8:34 maantarngmaantarng 1711 gold badge4 silver badges17 bronze badges 1 |1 Answer
Reset to default 1After some try-and-error, I found a simple solution.
At the .env file, just add this
_PIP_ADDITIONAL_REQUIREMENTS=apache-airflow-providers-oracle
and run the
docker compose up -d
command will do.
importstatements into a Compose YAML file, so it will help to see a minimal reproducible example. – David Maze Commented Mar 10 at 10:39