feat(infra): add airflow orchestration services
Add Apache Airflow infrastructure with webserver, scheduler, and metadata database to enable DAG-based pipeline orchestration. Includes optimized requirements file and Docker configuration for Airflow 2.9.3.
This commit is contained in:
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# Use the official Airflow image as base
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FROM apache/airflow:2.9.3
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# Set environment variables
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ENV AIRFLOW_HOME=/opt/airflow
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# Copy the project requirements file
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COPY --chown=airflow:0 requirements.txt ${AIRFLOW_HOME}/requirements.txt
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# Install the required Python packages
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RUN pip install --no-cache-dir -r ${AIRFLOW_HOME}/requirements.txt
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# Create necessary directories
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RUN mkdir -p /opt/airflow/dags /opt/airflow/logs /opt/airflow/config /opt/airflow/data
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# Set working directory
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WORKDIR ${AIRFLOW_HOME}
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# Expose the webserver port
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EXPOSE 8080
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# The image will use Airflow's default entrypoint
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# Commands will be passed at runtime
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# Optimized requirements for Airflow Docker setup
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# Only includes packages actually used in DAGs
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# Core database connector
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psycopg2-binary==2.9.9
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# Data processing (used in data_processing_dag.py and file_operations_dag.py)
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pandas==2.1.4
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# Data generation library (used in file_operations_dag.py)
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mimesis==15.1.0
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# Airflow PostgreSQL provider (used in sql_basic_dag.py and data_processing_dag.py)
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apache-airflow-providers-postgres==5.11.1
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@@ -1,3 +1,16 @@
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x-airflow-env: &airflow-default-env
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AIRFLOW__CORE__LOAD_EXAMPLES: "False"
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AIRFLOW__DATABASE__SQL_ALCHEMY_CONN: postgresql+psycopg2://airflow:airflow@postgres-metadata:5432/airflow
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AIRFLOW__CORE__EXECUTOR: LocalExecutor
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AIRFLOW__WEBSERVER__SECRET_KEY: replace-me-with-random-string
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POSTGRES_TRAINING_HOST: postgres-training
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POSTGRES_TRAINING_PORT: "5432"
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POSTGRES_TRAINING_DB: training
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POSTGRES_TRAINING_USER: student
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POSTGRES_TRAINING_PASSWORD: student
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AIRFLOW_CONN_POSTGRES_TRAINING: postgresql://student:student@postgres-training:5432/training
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services:
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clickhouse:
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image: clickhouse/clickhouse-server:25.1
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@@ -64,6 +77,100 @@ services:
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networks:
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- cs_dwh
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# PostgreSQL for Airflow metadata
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postgres-metadata:
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image: postgres:16
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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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ports:
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- "5434:5432"
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volumes:
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- pgmeta:/var/lib/postgresql/data
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networks:
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- cs_dwh
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healthcheck:
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test: ["CMD-SHELL", "pg_isready -U airflow -d airflow"]
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interval: 5s
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timeout: 5s
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retries: 20
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# Airflow webserver
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airflow-webserver:
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build: .
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image: airflow-optimized:2.9.2
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environment:
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<<: *airflow-default-env
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command: >
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bash -c "
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airflow webserver
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"
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ports:
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- "8080:8080"
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volumes:
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- ./dags:/opt/airflow/dags
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- ./data:/opt/airflow/data
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networks:
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- cs_dwh
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depends_on:
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airflow-init:
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condition: service_completed_successfully
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postgres-metadata:
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condition: service_healthy
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postgres-training:
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condition: service_healthy
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# Airflow scheduler
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airflow-scheduler:
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build: .
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# image: airflow-optimized:2.9.2
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environment:
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<<: *airflow-default-env
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command: >
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bash -c "
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airflow scheduler
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"
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volumes:
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- ./dags:/opt/airflow/dags
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- ./data:/opt/airflow/data
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networks:
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- cs_dwh
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depends_on:
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airflow-init:
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condition: service_completed_successfully
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postgres-metadata:
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condition: service_healthy
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postgres-training:
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condition: service_healthy
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# Airflow init to create admin user
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airflow-init:
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build: .
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user: "0:0"
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# image: airflow-optimized:2.9.3
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environment:
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<<: *airflow-default-env
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volumes:
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- ./dags:/opt/airflow/dags
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- ./data:/opt/airflow/data
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networks:
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- cs_dwh
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command: >
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bash -ceuo pipefail "
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mkdir -p /opt/airflow/data &&
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chmod -R 777 /opt/airflow/data || true &&
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chown -R airflow:0 /opt/airflow/data || true &&
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umask 000 &&
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su -s /bin/bash airflow -c 'airflow db migrate' &&
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su -s /bin/bash airflow -c 'airflow users create --username admin --password admin --firstname Admin --lastname User --role Admin --email admin@example.org' &&
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su -s /bin/bash airflow -c 'airflow connections delete postgres_training || true' &&
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su -s /bin/bash airflow -c \"airflow connections add 'postgres_training' --conn-uri \\\"$${AIRFLOW_CONN_POSTGRES_TRAINING}\\\" --conn-description 'Training exercises database'\"
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"
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depends_on:
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postgres-metadata:
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condition: service_healthy
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prometheus:
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image: prom/prometheus:v2.53.4
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volumes:
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@@ -127,6 +234,7 @@ networks:
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volumes:
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grafana_lib:
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kafka-data:
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pgmeta:
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superset_data:
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superset_config:
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