**Description**

A guide that describes how to use all the operators for Azure (https://github.com/apache/airflow/tree/master/airflow/providers/databricks/operators) would be useful.

Other guides are available:
https://airflow.readthedocs.io/en/latest/howto/operator/index.html

Source code for those guides are at:
https://github.com/apache/airflow/tree/master/docs/howto/operator

Are you wondering how to start contributing to this project? Start by reading our [contributor guide](https://github.com/apache/airflow/blob/master/CONTRIBUTING.rst)

Best regards,
Kaxil﻿

airflow/providers/databricks/example_dags/example_databricks.py
dag_id='example_databricks_operator',
    default_args=default_args,
    schedule_interval='@daily',
    start_date=days_ago(2),
    tags=['example'],
) as dag:
    new_cluster = {
        'spark_version': '2.1.0-db3-scala2.11',
        'node_type_id': 'r3.xlarge',
        'aws_attributes': {'availability': 'ON_DEMAND'},
        'num_workers': 8,
    }
    notebook_task_params = {
        'new_cluster': new_cluster,
        'notebook_task': {
            'notebook_path': '/Users/airflow@example.com/PrepareData',
        },
    }
    
    notebook_task = DatabricksSubmitRunOperator(task_id='notebook_task', json=notebook_task_params)
    
    
    spark_jar_task = DatabricksSubmitRunOperator(
        task_id='spark_jar_task',
        new_cluster=new_cluster,
        spark_jar_task={'main_class_name': 'com.example.ProcessData'},
        libraries=[{'jar': 'dbfs:/lib/etl-0.1.jar'}],
    )
    notebook_task >> spark_jar_task