This Docker images are intended to deploy the following services:

• airflow-webserver
• airflow-worker
• airflow-scheduler
• spark-master
• spark-worker-1
• kafka
• zookeper

To launch the servers in docker conatiners run the following

Only the first time:

docker-compose up -d airflow-init

After thi initialization is done you can run the following command every time you need to test the full project

docker-compose up -d

It will take some minutes depending on the RAM and CPU of the machine where it is executed
so probably you would like to check the Logs in order to know if the services have finished the inisialization or not

In order to check the logs you can run

docker-compose logs

After everything is correctly loaded you can login to the Airflow UI in order to turn on the DAG that will execute the pipeline To access the Airflow UI you have to navigate in the browser to the url:

http://localhost:8282/

And login with the username: airflow and password: airflow

If the DAG is failing because it can't connect to spark then execute in airflow-webserver service the following command:

airflow connections add 'spark_local' --conn-json '{"conn_type": "spark", "host": "spark://spark-master", "port": 7077}'