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Description
Astronomer Cosmos Version
1.10.2
dbt-core version
1.8.9
Versions of dbt adapters
Athena 1.8.4
LoadMode
DBT_LS
ExecutionMode
LOCAL
InvocationMode
None
airflow version
2.11.0
Operating System
debian 12
If a you think it's an UI issue, what browsers are you seeing the problem on?
No response
Deployment
Docker-Compose
Deployment details
# 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:2.11.0
# 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.
---
x-airflow-common:
&airflow-common
# Use a custom image that bakes in dbt + cosmos.
# Build context is repo root containing the Dockerfile.
build: .
image: airflow-cosmos-local:2.11.0
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'
DBT_PROFILES_DIR: /opt/airflow/dbt
PIP_INDEX_URL: https://pypi.tuna.tsinghua.edu.cn/simple
PIP_TIMEOUT: '120'
AIRFLOW__CORE__DAGBAG_IMPORT_TIMEOUT: '300'
# 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'
# 日志配置
AIRFLOW__LOGGING__LOGGING_LEVEL: INFO
AIRFLOW__LOGGING__FAB_LOGGING_LEVEL: WARN
AIRFLOW__LOGGING__BASE_LOG_FOLDER: /opt/airflow/logs
AIRFLOW__LOGGING__REMOTE_LOGGING: 'false'
AIRFLOW__LOGGING__REMOTE_BASE_LOG_FOLDER: ''
AIRFLOW__LOGGING__REMOTE_LOG_CONN_ID: ''
AIRFLOW__LOGGING__ENCRYPT_S3_LOGS: 'false'
# 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
- ${AIRFLOW_PROJ_DIR:-.}/plugins:/opt/airflow/plugins
- /home/leiyang/work/unified-data-all/unified-data-dbt:/opt/airflow/dbt
- /home/leiyang/.aws:/home/airflow/.aws:ro
user: "${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.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 "$${HOSTNAME}"']
interval: 30s
timeout: 10s
retries: 5
start_period: 30s
restart: always
depends_on:
<<: *airflow-common-depends-on
airflow-init:
condition: service_completed_successfully
airflow-init:
<<: *airflow-common
entrypoint: /bin/bash
# yamllint disable rule:line-length
command:
- -c
- |
if [[ -z "${AIRFLOW_UID}" ]]; then
echo
echo -e "\033[1;33mWARNING!!!: AIRFLOW_UID not set!\e[0m"
echo "If you are on Linux, you SHOULD follow the instructions below to set "
echo "AIRFLOW_UID environment variable, otherwise files will be owned by root."
echo "For other operating systems you can get rid of the warning with manually created .env file:"
echo " See: https://airflow.apache.org/docs/apache-airflow/stable/howto/docker-compose/index.html#setting-the-right-airflow-user"
echo
fi
one_meg=1048576
mem_available=$$(($$(getconf _PHYS_PAGES) * $$(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.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_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.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:
and DCOKFILE:
FROM apache/airflow:2.11.0
# Switch to root to adjust apt sources and install minimal tools
USER root
RUN set -ex \
# Remove any extra sources to avoid slow/failing repos
&& rm -f /etc/apt/sources.list.d/* || true \
# Write a fresh sources.list using Aliyun mirrors (Debian 12/bookworm)
&& echo 'deb https://mirrors.aliyun.com/debian bookworm main contrib non-free non-free-firmware' > /etc/apt/sources.list \
&& echo 'deb https://mirrors.aliyun.com/debian bookworm-updates main contrib non-free non-free-firmware' >> /etc/apt/sources.list \
&& echo 'deb https://mirrors.aliyun.com/debian-security bookworm-security main contrib non-free non-free-firmware' >> /etc/apt/sources.list \
&& apt-get update \
&& apt-get install -y --no-install-recommends \
python3-venv \
build-essential \
&& rm -rf /var/lib/apt/lists/* \
&& mkdir -p /opt/airflow/.venvs \
&& chown -R airflow:0 /opt/airflow/.venvs
# Switch to airflow user for Python package installation
USER airflow
# Install Cosmos for Local execution into the image's Python env (venv)
RUN pip install --no-cache-dir -i https://pypi.tuna.tsinghua.edu.cn/simple "astronomer-cosmos[local]"
# Create a dedicated venv for dbt + athena and install packages there
ENV DBT_VENV=/opt/airflow/.venvs/dbt-athena
RUN python3 -m venv "$DBT_VENV" \
&& "$DBT_VENV/bin/pip" install --no-cache-dir -i https://pypi.tuna.tsinghua.edu.cn/simple --upgrade pip setuptools wheel \
&& "$DBT_VENV/bin/pip" install --no-cache-dir -i https://pypi.tuna.tsinghua.edu.cn/simple \
"dbt-core>=1.8,<1.9" \
"dbt-athena-community>=1.8,<1.9"
What happened?
should success process DAG file and find it in web ui,but process DAG faild. And it appears to have entered a loop, continuously retrying.
This is airflow config:
[core]
executor = CeleryExecutor
fernet_key =
dags_are_paused_at_creation = True
load_examples = True
dagbag_import_timeout = 300
[database]
sql_alchemy_conn = postgresql+psycopg2://airflow:airflow@postgres/airflow
[celery]
result_backend = db+postgresql://airflow:airflow@postgres/airflow
broker_url = redis://:@redis:6379/0
[api]
auth_backends = airflow.api.auth.backend.basic_auth,airflow.api.auth.backend.session
[scheduler]
enable_health_check = True
[logging]
logging_level = DEBUG
fab_logging_level = DEBUG
base_log_folder = /opt/airflow/logs
remote_logging = False
remote_base_log_folder =
remote_log_conn_id =
encrypt_s3_logs = False
Relevant log output
How to reproduce
DAG file:
from __future__ import annotations
from datetime import datetime
from cosmos import DbtDag
from cosmos.config import (
ProjectConfig,
ProfileConfig,
ExecutionConfig,
RenderConfig,
LoadMode,
ExecutionMode,
)
# Cosmos Local mode: call a fixed dbt binary inside a dedicated venv
# baked into the Airflow image, to keep global env clean while avoiding
# per-task venv overhead.
DBT_PROJECT_DIR = "/opt/airflow/dbt"
DBT_PROFILES_DIR = DBT_PROJECT_DIR
dag = DbtDag(
dag_id="ext_walmart_adgroup_aditem_report",
schedule_interval=None,
start_date=datetime(2024, 1, 1),
catchup=False,
default_args={"owner": "airflow"},
project_config=ProjectConfig(
dbt_project_path=DBT_PROJECT_DIR,
),
profile_config=ProfileConfig(
profile_name="athena",
target_name="dev",
profiles_yml_filepath=f"{DBT_PROFILES_DIR}/profiles.yml",
),
render_config=RenderConfig(
load_method=LoadMode.DBT_LS,
select=["ext_walmart_aditem_report"],
),
execution_config=ExecutionConfig(
execution_mode=ExecutionMode.LOCAL,
dbt_executable_path="/opt/airflow/.venvs/dbt-athena/bin/dbt",
),
)
It's a very simple model. Running these two commands directly inside the container is very fast:
/opt/airflow/.venvs/dbt-athena/bin/dbt deps --project-dir /tmp/tmpd96z2aj5 --profiles-dir /opt/airflow/dbt --profile athena --target dev
/opt/airflow/.venvs/dbt-athena/bin/dbt ls --output json --project-dir /tmp/tmpd96z2aj5 --profiles-dir /opt/airflow/dbt --profile athena --target dev --select ext_walmart_aditem_report
ext_walmart_aditem_report.sql:
{{ config(materialized='table') }}
select 1 as test_column
Anything else :)?
No response
Are you willing to submit PR?
- Yes I am willing to submit a PR!
Contact Details
No response
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