Apache Airflow provides a variety of built-in operators that you can use to create tasks within your Directed Acyclic Graphs (DAGs).

Commonly Used Operators -

1. DummyOperator - It doesn't execute any task, but it can be useful to mark certain points within your workflow. It acts as a placeholder operator.

   Params & Definition - DummyOperator

2. BashOperator - It is used to execute a bash command.

   Params & Definition - BashOperator

3. PythonOperator - It is used to run the python callable or python function.

   Params & Definition - PythonOperator

4. EmailOperator - It is used to send emails to the receiver.

   Params & Definition - EmailOperator

5. MySqlOperator - It is used to run the SQL query for MySql Database.

   Params & Definition - MySqlOperator

6. S3ToHiveOperator - It transfers data from Amazon S3 to Hive.

   Params & Definition - S3ToHiveOperator

Lets get Coding -

1. DummyOperator -

    from airflow import DAG
    from airflow.operators.dummy import DummyOperator
    from datetime import datetime
   
    default_args = {
        'owner': 'airflow',
        'depends_on_past': False,
        'start_date': datetime(2022, 1, 1)
    }
   
    dag = DAG('dummy_operator_example_dag', default_args=default_args, schedule_interval='@daily')
   
    task_1 = DummyOperator(task_id='task_1', dag=dag)
    task_2 = DummyOperator(task_id='task_2', dag=dag)
   
    task_1 >> task_2
   

2. BashOperator -

    from airflow import DAG
    from airflow.operators.bash_operator import BashOperator
    from datetime import datetime
   
    default_args = {'owner': 'airflow', 'start_date': datetime(2021, 1, 1)}
   
    dag = DAG('bash_operator_example_dag', 
              default_args=default_args, schedule_interval='@daily')
   
    task1 = BashOperator(
        task_id='task1',
        bash_command='echo "Hello Bash Operator!"',
        dag=dag
    )
   

3. PythonOperator -

   ```python from datetime import datetime, timedelta from airflow import DAG from airflow.operators.python import PythonOperator from airflow.operators.empty import EmptyOperator from pathlib import Path

def our_python_function(): print("You can write your python function logic here")

Default parameters for the workflow

default_args = { 'depends_on_past': False, 'owner': 'airflow', 'start_date': datetime(2021, 1, 1) }

dag = DAG('dummy_operator_example_dag', default_args=default_args, schedule_interval='@daily')

task1 = BashOperator( task_id='task1', python_callable=our_python_function, dag=dag )

4. **EmailOperator -**

    Before using the `EmailOperator`, ensure that your Airflow configuration defines the SMTP server details:

    ```bash
    [email]
    smtp_host = smtp.example.com
    smtp_starttls = True
    smtp_ssl = False
    smtp_user = user@example.com
    smtp_password = password
    smtp_port = 25
    smtp_mail_from = airflow@example.com

    from airflow.operators.email import EmailOperator

    send_email = EmailOperator(
        task_id='send_email',
        to='user@example.com',
        subject='Airflow Alert',
        html_content='<p>Your Airflow job has finished.</p>'
    )

5. MySqlOperator -

    from datetime import datetime
    from airflow import DAG
    from airflow.operators.mysql_operator import MySqlOperator
    import logging
    import mysql.connector
    mydb = mysql.connector.connect(
    host=”localhost”,
    user=”(enter)”,
    passwd=”(enter)",
    database=”(enter)”
    )
   
    default_args = {'owner': 'airflow', 'start_date': datetime(2021, 1, 1)}
   
    dag = DAG('mysql_operator_example_dag', 
              default_args=default_args, schedule_interval='@daily')
   
    task1 = MySqlOperator(
        task_id='task1',
        sql='''CREATE TABLE employee( emp_id integer NOT NULL, emp_name VARCHAR (50) NOT NULL, emp_title VARCHAR(50));''',
    )
    task2 = MySqlOperator(
        task_id='task2',
        sql='INSERT INTO employee (emp_id,emp_name,emp_title) VALUES(%s, %s)',
        parameters=(1,"abc","HR")
    )
    task1 >> task2
   

6. HttpSensor -

    from airflow import DAG
    from airflow.sensors.http_sensor import HttpSensor
    from datetime import datetime
   
    default_args = {'owner': 'airflow', 'start_date': datetime(2024, 1, 1)}
   
    dag = DAG('http_sensor_example_dag', default_args=default_args, schedule_interval='@daily')
   
    http_sensor_task = HttpSensor(
        task_id='http_sensor_task',
        http_conn_id='http_conn_id',
        endpoint='http://example.com/health',
        poke_interval=60,
        timeout=120,
        dag=dag
    )