docker-compose.yml

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# to you under the Apache License, Version 2.0 (the
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#
#   http://www.apache.org/licenses/LICENSE-2.0
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# 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: 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:2.7.1-python3.9}
  # 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: "false"
    AIRFLOW_HOME: "/opt/airflow"
    AIRFLOW__CORE_dags_folder: "/opt/airflow/dags"
    AIRFLOW__API__AUTH_BACKENDS: "airflow.api.auth.backend.basic_auth,airflow.api.auth.backend.session"
    _PIP_ADDITIONAL_REQUIREMENTS: ${_PIP_ADDITIONAL_REQUIREMENTS:-}
    DBT_PROFILES_DIR: /opt/airflow/dbt_profiles
  volumes:
    - ./datasets:/opt/airflow/dags/data
    - ./airflow/dags:/opt/airflow/dags
    - ./airflow/logs:/opt/airflow/logs
    - ./airflow/plugins:/opt/airflow/plugins
    - ./airflow/config/airflow.cfg:/opt/airflow/airflow.cfg
    - ./dbt/.dbt:/usr/app/.dbt
    - ./airflow/dags/data:/opt/airflow/dags/data
    - ./dbt:/usr/app/dbt_project
    - ./dbt/profiles:/opt/airflow/dbt_profiles

  user: "${AIRFLOW_UID:-50000}:${AIRFLOW_GID:-0}"
  depends_on:
    redis:
      condition: service_healthy
    postgres:
      condition: service_healthy

services:
  postgres:
    image: postgres:13
    ports:
      - 5432:5432
    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
    networks:
      - airflow-network

  redis:
    image: redis:latest
    ports:
      - 6379:6379
    healthcheck:
      test: ["CMD", "redis-cli", "ping"]
      interval: 5s
      timeout: 30s
      retries: 50
    restart: always
    networks:
      - airflow-network

  airflow-webserver:
    <<: *airflow-common
    command: webserver
    ports:
      - 8080:8080
    healthcheck:
      test: ["CMD", "curl", "--fail", "http://localhost:8080/health"]
      interval: 10s
      timeout: 10s
      retries: 5
    restart: always
    networks:
      - airflow-network

  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
    networks:
      - airflow-network

  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
    networks:
      - airflow-network

  airflow-init:
    <<: *airflow-common
    entrypoint: /bin/bash
    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_airlfow_version_comparable=$$(ver $${min_airflow_version})
        if (( airflow_version_comparable < min_airlfow_version_comparable )); then
          echo -e "\033[1;31mERROR!!!: Too old Airflow version $${airflow_version}!\e[0m"
          echo "The minimum Airflow version supported: $${min_airflow_version}. Only use this or higher!"
          exit 1
        fi
        if [[ -z "${AIRFLOW_UID}" ]]; then
          echo -e "\033[1;31mERROR!!!: AIRFLOW_UID not set!\e[0m"
          echo "Please follow these instructions to set AIRFLOW_UID and AIRFLOW_GID environment variables:
            https://airflow.apache.org/docs/apache-airflow/stable/start/docker.html#initializing-environment"
          exit 1
        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 -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)))"
          warning_resources="true"
        fi
        if (( cpus_available < 2 )); then
          echo -e "\033[1;33mWARNING!!!: Not enough CPUS available for Docker.\e[0m"
          echo "At least 2 CPUs recommended. You have $${cpus_available}"
          warning_resources="true"
        fi
        if (( disk_available < one_meg * 10 )); then
          echo -e "\033[1;33mWARNING!!!: Not enough Disk space available for Docker.\e[0m"
          echo "At least 10 GBs recommended. You have $$(numfmt --to iec $$((disk_available * 1024 )))"
          warning_resources="true"
        fi
        if [[ $${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/start/docker.html#before-you-begin"
        fi
        mkdir -p /sources/logs /sources/dags /sources/plugins
        chown -R "${AIRFLOW_UID}:${AIRFLOW_GID}" /sources/{logs,dags,plugins}
        exec /entrypoint airflow version
        airflow connections add --conn-id fs_default --conn-type filesystem
    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: ${_AIRFLOW_WWW_USER_PASSWORD:-airflow}
      _PIP_ADDITIONAL_REQUIREMENTS: ''
    user: "0:${AIRFLOW_GID:-0}"
    volumes:
      - .:/sources
      - ./dbt/.dbt:/usr/app/.dbt

  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
    networks:
      - airflow-network

  dbt:
#    image: ghcr.io/dbt-labs/dbt-postgres:1.8.2
    build:
      context: .
      dockerfile: Dockerfile dbt
    container_name: dbt
    tty: true
    ports:
      - "8081:8081"
    volumes:
      - ./dbt:/usr/app
      - ./dbt/.dbt:/root/.dbt   # DBT's default path for profiles
      - ./dbt/.dbt:/usr/app/.dbt # Alternative path for consistency
    networks:
      - airflow-network

  duckdb:
    container_name: duckdb
    build:
      context: .
      dockerfile: Dockerfile
    volumes:
#      - ./duckdb_data:/app/data
      - ./airflow/dags/data:/opt/airflow/dags/data
    tty: true
    stdin_open: true
    networks:
      - airflow-network

  iceberg_rest:
    image: tabulario/iceberg-rest:1.6.0
    container_name: iceberg_rest
    ports:
      - "8181:8181"
    environment:
      AWS_ACCESS_KEY_ID: minioadmin
      AWS_SECRET_ACCESS_KEY: minioadmin
      AWS_REGION: us-east-1
      CATALOG_WAREHOUSE: s3://warehouse/
      CATALOG_IO__IMPL: org.apache.iceberg.aws.s3.S3FileIO
      CATALOG_S3_ENDPOINT: http://minio:9000
    depends_on:
      - minio
    networks:
      - airflow-network

  minio:
    image: minio/minio:RELEASE.2024-10-13T13-34-11Z
    container_name: minio
    ports:
      - "9000:9000"   # MinIO API port
      - "9001:9001"   # MinIO Console port
    environment:
      MINIO_ROOT_USER: minioadmin
      MINIO_ROOT_PASSWORD: minioadmin
      MINIO_DOMAIN: minio
    command: server /data --console-address ":9001"
    volumes:
      - ./minio_data:/data
    networks:
      - airflow-network

  mc:
    depends_on:
      - minio
    image: minio/mc:RELEASE.2024-10-02T08-27-28Z
    container_name: mc
    networks:
      - airflow-network
    entrypoint: >
      /bin/sh -c "
      until (/usr/bin/mc config host add minio http://minio:9000 minioadmin minioadmin) do echo '...waiting...' && sleep 1; done;
      /usr/bin/mc rm -r --force minio/warehouse;
      /usr/bin/mc mb minio/warehouse;
      /usr/bin/mc policy set public minio/warehouse;
      /usr/bin/mc version enable local/warehouse;
      "

  sl:
    image: python:3.12.7-slim-bookworm
    container_name: sl
    volumes:
      - ./streamlit:/streamlit  # Mount Streamlit app files
      - ./datasets:/datasets  # Mount datasets containing DuckDB file
    working_dir: /streamlit
    networks:
      - airflow-network
    ports:
      - "8501:8501"  # Streamlit default port
      - "8502:8502"
    command: >
      sh -c "
      apt-get update && 
      apt-get install -y gdal-bin libgdal-dev python3-dev &&
      pip install geopandas pandas duckdb streamlit &&
      streamlit run app.py
      "

volumes:
  postgres-db-volume:
  duckdb_data:
  minio_data:

networks:
  airflow-network:
    driver: bridge