384 lines
12 KiB
YAML
384 lines
12 KiB
YAML
---
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x-airflow-common:
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&airflow-common
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# In order to add custom dependencies or upgrade provider packages you can use your extended image.
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# Comment the image line, place your Dockerfile in the directory where you placed the docker-compose.yaml
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# and uncomment the "build" line below, Then run `docker-compose build` to build the images.
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#image: ${AIRFLOW_IMAGE_NAME:-apache/airflow:2.6.0}
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build: ./docker/airflow
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# build: .
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environment:
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&airflow-common-env
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AIRFLOW__CORE__EXECUTOR: CeleryExecutor
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AIRFLOW__DATABASE__SQL_ALCHEMY_CONN: postgresql+psycopg2://airflow:airflow@postgres/airflow
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AIRFLOW__CELERY__RESULT_BACKEND: db+postgresql://airflow:airflow@postgres/airflow
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AIRFLOW__CELERY__BROKER_URL: redis://:@redis:6379/0
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AIRFLOW__CORE__FERNET_KEY: ''
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AIRFLOW__CORE__DAGS_ARE_PAUSED_AT_CREATION: 'true'
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AIRFLOW__CORE__LOAD_EXAMPLES: 'False'
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AIRFLOW__API__AUTH_BACKENDS: 'airflow.api.auth.backend.basic_auth,airflow.api.auth.backend.session'
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AIRFLOW_CONN_RAW_DATA: 'mysql://${MYSQL_USER}:${MYSQL_PASSWORD}@db_raw:${MYSQL_RAW_PORT}/${MYSQL_RAW_DATABASE}'
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AIRFLOW_CONN_CLEAN_DATA: 'mysql://${MYSQL_USER}:${MYSQL_PASSWORD}@db_clean:${MYSQL_CLEAN_PORT}/${MYSQL_CLEAN_DATABASE}'
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# yamllint disable rule:line-length
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# Use simple http server on scheduler for health checks
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# See https://airflow.apache.org/docs/apache-airflow/stable/administration-and-deployment/logging-monitoring/check-health.html#scheduler-health-check-server
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# yamllint enable rule:line-length
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AIRFLOW__SCHEDULER__ENABLE_HEALTH_CHECK: 'true'
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# WARNING: Use _PIP_ADDITIONAL_REQUIREMENTS option ONLY for a quick checks
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# for other purpose (development, test and especially production usage) build/extend Airflow image.
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_PIP_ADDITIONAL_REQUIREMENTS: ${_PIP_ADDITIONAL_REQUIREMENTS:-}
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volumes:
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- ${AIRFLOW_PROJ_DIR:-.}/dags:/opt/airflow/dags
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- ${AIRFLOW_PROJ_DIR:-.}/logs:/opt/airflow/logs
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- ${AIRFLOW_PROJ_DIR:-.}/plugins:/opt/airflow/plugins
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user: "${AIRFLOW_UID:-50000}:0"
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depends_on:
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&airflow-common-depends-on
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redis:
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condition: service_healthy
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postgres:
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condition: service_healthy
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services:
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db:
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restart: always
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image: mysql/mysql-server:5.7.28
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container_name: mlflow_db
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ports:
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- "${MYSQL_PORT}:3306"
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networks:
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- backend
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environment:
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- MYSQL_DATABASE=${MYSQL_DATABASE}
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- MYSQL_USER=${MYSQL_USER}
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- MYSQL_PASSWORD=${MYSQL_PASSWORD}
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- MYSQL_ROOT_PASSWORD=${MYSQL_ROOT_PASSWORD}
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volumes:
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- ./db_ml_data:/var/lib/mysql
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db_raw:
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restart: always
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image: mysql/mysql-server:5.7.28
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container_name: raw_data_db
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ports:
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- "${MYSQL_RAW_PORT}:3306"
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networks:
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- backend
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environment:
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- MYSQL_DATABASE=${MYSQL_RAW_DATABASE}
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- MYSQL_USER=${MYSQL_USER}
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- MYSQL_PASSWORD=${MYSQL_PASSWORD}
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- MYSQL_ROOT_PASSWORD=${MYSQL_ROOT_PASSWORD}
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volumes:
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- ./db_raw_data:/var/lib/mysql
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db_clean:
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restart: always
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image: mysql/mysql-server:5.7.28
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container_name: clean_data_db
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ports:
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- "${MYSQL_CLEAN_PORT}:3306"
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networks:
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- backend
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environment:
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- MYSQL_DATABASE=${MYSQL_CLEAN_DATABASE}
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- MYSQL_USER=${MYSQL_USER}
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- MYSQL_PASSWORD=${MYSQL_PASSWORD}
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- MYSQL_ROOT_PASSWORD=${MYSQL_ROOT_PASSWORD}
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volumes:
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- ./db_clean_data:/var/lib/mysql
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fast_api:
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build: ./docker/fast_api
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ports:
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- 8086:8086
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container_name: fast_api
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depends_on:
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- db_raw
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- db_clean
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networks:
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- backend
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volumes:
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- ./src/back:/opt/code/
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command: "uvicorn opt.code.main:app --host 0.0.0.0 --port 8086 --reload"
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minio:
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container_name: minio
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command: server /data --console-address ":${MINIO_CONSOLE_PORT}" --address ':${MINIO_PORT}'
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environment:
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- MINIO_ROOT_USER=${MINIO_ROOT_USER}
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- MINIO_ROOT_PASSWORD=${MINIO_ROOT_PASSWORD}
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image: quay.io/minio/minio:latest
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ports:
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- "${MINIO_PORT}:8081"
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- "${MINIO_CONSOLE_PORT}:8082"
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networks:
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- backend
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volumes:
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- ./minio_data:/data
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restart: unless-stopped
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mlflow:
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restart: always
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build: ./docker/mlflow
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image: mlflow
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container_name: mlflow
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depends_on:
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- db
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- minio
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ports:
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- "${MLFLOW_PORT}:8083"
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networks:
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- backend
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environment:
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- AWS_ACCESS_KEY_ID=${MINIO_ACCESS_KEY}
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- AWS_SECRET_ACCESS_KEY=${MINIO_SECRET_ACCESS_KEY}
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- MLFLOW_S3_ENDPOINT_URL=http://minio:${MINIO_PORT}
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- MLFLOW_TRACKING_URI=http://mlflow:${MLFLOW_PORT}
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- BACKEND_STORE_URI=mysql+pymysql://${MYSQL_USER}:${MYSQL_PASSWORD}@db:${MYSQL_PORT}/${MYSQL_DATABASE}
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- DEFAULT_ARTIFACT_ROOT=s3://minio:${MINIO_PORT}
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- MLFLOW_S3_IGNORE_TLS=true
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command: >
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mlflow server
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--backend-store-uri mysql+pymysql://${MYSQL_USER}:${MYSQL_PASSWORD}@db:${MYSQL_PORT}/${MYSQL_DATABASE}
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--host 0.0.0.0
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--port ${MLFLOW_PORT}
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--serve-artifacts
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--artifacts-destination s3://${MLFLOW_BUCKET_NAME}/
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--default-artifact-root s3://${MLFLOW_BUCKET_NAME}/
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work_jupyter:
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build: ./docker/jupyter
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volumes:
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- ./:/home/jovyan/work
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ports:
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- 8085:8888
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container_name: jupyter
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networks:
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- backend
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command: "jupyter lab --ip=0.0.0.0 --allow-root --NotebookApp.token='' --NotebookApp.password=''"
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postgres:
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image: postgres:13
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environment:
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POSTGRES_USER: airflow
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POSTGRES_PASSWORD: airflow
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POSTGRES_DB: airflow
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volumes:
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- postgres-db-volume:/var/lib/postgresql/data
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healthcheck:
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test: ["CMD", "pg_isready", "-U", "airflow"]
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interval: 10s
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retries: 5
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start_period: 5s
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restart: always
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networks:
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- backend
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redis:
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image: redis:7.2-bookworm
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expose:
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- 6379
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healthcheck:
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test: ["CMD", "redis-cli", "ping"]
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interval: 10s
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timeout: 30s
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retries: 50
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start_period: 30s
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restart: always
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networks:
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- backend
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airflow-webserver:
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<<: *airflow-common
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command: webserver
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ports:
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- "8080:8080"
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healthcheck:
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test: ["CMD", "curl", "--fail", "http://localhost:8080/health"]
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interval: 30s
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timeout: 10s
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retries: 5
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start_period: 30s
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restart: always
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depends_on:
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<<: *airflow-common-depends-on
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airflow-init:
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condition: service_completed_successfully
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networks:
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- backend
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airflow-scheduler:
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<<: *airflow-common
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command: scheduler
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healthcheck:
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test: ["CMD", "curl", "--fail", "http://localhost:8974/health"]
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interval: 30s
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timeout: 10s
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retries: 5
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start_period: 30s
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restart: always
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depends_on:
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<<: *airflow-common-depends-on
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airflow-init:
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condition: service_completed_successfully
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networks:
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- backend
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airflow-worker:
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<<: *airflow-common
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command: celery worker
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healthcheck:
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test:
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- "CMD-SHELL"
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- '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}"'
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interval: 30s
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timeout: 10s
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retries: 5
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start_period: 30s
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environment:
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<<: *airflow-common-env
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# Required to handle warm shutdown of the celery workers properly
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# See https://airflow.apache.org/docs/docker-stack/entrypoint.html#signal-propagation
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DUMB_INIT_SETSID: "0"
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restart: always
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depends_on:
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<<: *airflow-common-depends-on
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airflow-init:
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condition: service_completed_successfully
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networks:
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- backend
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airflow-triggerer:
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<<: *airflow-common
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command: triggerer
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healthcheck:
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test: ["CMD-SHELL", 'airflow jobs check --job-type TriggererJob --hostname "$${HOSTNAME}"']
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interval: 30s
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timeout: 10s
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retries: 5
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start_period: 30s
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restart: always
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depends_on:
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<<: *airflow-common-depends-on
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airflow-init:
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condition: service_completed_successfully
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networks:
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- backend
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airflow-init:
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<<: *airflow-common
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entrypoint: /bin/bash
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# yamllint disable rule:line-length
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command:
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- -c
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- |
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if [[ -z "${AIRFLOW_UID}" ]]; then
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echo
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echo -e "\033[1;33mWARNING!!!: AIRFLOW_UID not set!\e[0m"
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echo "If you are on Linux, you SHOULD follow the instructions below to set "
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echo "AIRFLOW_UID environment variable, otherwise files will be owned by root."
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echo "For other operating systems you can get rid of the warning with manually created .env file:"
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echo " See: https://airflow.apache.org/docs/apache-airflow/stable/howto/docker-compose/index.html#setting-the-right-airflow-user"
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echo
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fi
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one_meg=1048576
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mem_available=$$(($$(getconf _PHYS_PAGES) * $$(getconf PAGE_SIZE) / one_meg))
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cpus_available=$$(grep -cE 'cpu[0-9]+' /proc/stat)
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disk_available=$$(df / | tail -1 | awk '{print $$4}')
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warning_resources="false"
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if (( mem_available < 4000 )) ; then
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echo
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echo -e "\033[1;33mWARNING!!!: Not enough memory available for Docker.\e[0m"
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echo "At least 4GB of memory required. You have $$(numfmt --to iec $$((mem_available * one_meg)))"
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echo
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warning_resources="true"
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fi
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if (( cpus_available < 2 )); then
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echo
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echo -e "\033[1;33mWARNING!!!: Not enough CPUS available for Docker.\e[0m"
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echo "At least 2 CPUs recommended. You have $${cpus_available}"
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echo
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warning_resources="true"
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fi
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if (( disk_available < one_meg * 10 )); then
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echo
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echo -e "\033[1;33mWARNING!!!: Not enough Disk space available for Docker.\e[0m"
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echo "At least 10 GBs recommended. You have $$(numfmt --to iec $$((disk_available * 1024 )))"
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echo
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warning_resources="true"
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fi
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if [[ $${warning_resources} == "true" ]]; then
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echo
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echo -e "\033[1;33mWARNING!!!: You have not enough resources to run Airflow (see above)!\e[0m"
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echo "Please follow the instructions to increase amount of resources available:"
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echo " https://airflow.apache.org/docs/apache-airflow/stable/howto/docker-compose/index.html#before-you-begin"
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echo
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fi
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mkdir -p /sources/logs /sources/dags /sources/plugins
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chown -R "${AIRFLOW_UID}:0" /sources/{logs,dags,plugins}
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exec /entrypoint airflow version
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# yamllint enable rule:line-length
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environment:
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<<: *airflow-common-env
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_AIRFLOW_DB_UPGRADE: 'true'
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_AIRFLOW_WWW_USER_CREATE: 'true'
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_AIRFLOW_WWW_USER_USERNAME: ${_AIRFLOW_WWW_USER_USERNAME:-airflow}
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_AIRFLOW_WWW_USER_PASSWORD: ${_AIRFLOW_WWW_USER_PASSWORD:-airflow}
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_PIP_ADDITIONAL_REQUIREMENTS: ''
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user: "0:0"
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volumes:
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- ${AIRFLOW_PROJ_DIR:-.}:/sources
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networks:
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- backend
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airflow-cli:
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<<: *airflow-common
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profiles:
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- debug
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environment:
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<<: *airflow-common-env
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CONNECTION_CHECK_MAX_COUNT: "0"
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# Workaround for entrypoint issue. See: https://github.com/apache/airflow/issues/16252
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command:
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- bash
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- -c
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- airflow
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networks:
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- backend
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# You can enable flower by adding "--profile flower" option e.g. docker-compose --profile flower up
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# or by explicitly targeted on the command line e.g. docker-compose up flower.
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# See: https://docs.docker.com/compose/profiles/
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flower:
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<<: *airflow-common
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command: celery flower
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profiles:
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- flower
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ports:
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- "5555:5555"
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healthcheck:
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test: ["CMD", "curl", "--fail", "http://localhost:5555/"]
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interval: 30s
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timeout: 10s
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retries: 5
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start_period: 30s
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restart: always
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depends_on:
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<<: *airflow-common-depends-on
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airflow-init:
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condition: service_completed_successfully
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networks:
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- backend
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volumes:
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postgres-db-volume:
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db_ml_data:
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db_raw_data:
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db_clean_data:
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minio_data:
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networks:
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backend:
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driver: bridge
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