Question: I am new to Apache airflow and DAG. There are total 6 tasks in the DAG (task1, task2, task3, task4, task5, task6). But at the time of running the DAG we are getting the error below. DAG unsupported operand type(s) for >>: 'list' and 'list' Below is my code for the DAG. Please help. I am new to airflow. from airflow import DAG from datetime import datetime from airflow.providers.databricks.operators.databricks import DatabricksSubmitRunOperator default_args = { 'owner': 'airflow', 'depends_on_past': False } dag = DAG('DAG_FOR_TEST',default_args=default_args,schedule_interval=None,max_active_runs=3, start_date=datetime(2020, 7, 14)) #################### CREATE TASK ##################################### task_1 = DatabricksSubmitRunOperator( task_id='task_1', databricks_conn_id='connection_id_details', existing_cluster_id='{{ dag_run.conf.clusterId }}', libraries= [ { 'jar': 'dbfs:/task_1/task_1.jar' } ], spark_jar_task={ 'main_class_name': 'com.task_1.driver.TestClass1', 'parameters' : [ '{{ dag_run.conf.json }}' ] } ) task_2 = DatabricksSubmitRunOperator( task_id='task_2', databricks_conn_id='connection_id_details', existing_cluster_id='{{ dag_run.conf.clusterId }}', libraries= [ { 'jar': 'dbfs:/task_2/task_2.jar' } ], spark_jar_task={ 'main_class_name': 'com.task_2.driver.TestClass2', 'parameters' : [ '{{ dag_run.conf.json }}' ] } ) task_3 = DatabricksSubmitRunOperator( task_id='task_3', databricks_conn_id='connection_id_details', existing_cluster_id='{{ dag_run.conf.clusterId }}', libraries= [ { 'jar': 'dbfs:/task_3/task_3.jar' } ], spark_jar_task={ 'main_class_name': 'com.task_3.driver.TestClass3', 'parameters' : [ '{{ dag_run.conf.json }}' ] } ) task_4 = DatabricksSubmitRunOperator( task_id='task_4', databricks_conn_id='connection_id_details', existing_cluster_id='{{ dag_run.conf.clusterId }}', libraries= [ { 'jar': 'dbfs:/task_4/task_4.jar' } ], spark_jar_task={ 'main_class_name': 'com.task_4.driver.TestClass4', 'parameters' : [ '{{ dag_run.conf.json }}' ] } ) task_5 = DatabricksSubmitRunOperator( task_id='task_5', databricks_conn_id='connection_id_details', existing_cluster_id='{{ dag_run.conf.clusterId }}', libraries= [ { 'jar': 'dbfs:/task_5/task_5.jar' } ], spark_jar_task={ 'main_class_name': 'com.task_5.driver.TestClass5', 'parameters' : [ 'json ={{ dag_run.conf.json }}' ] } ) task_6 = DatabricksSubmitRunOperator( task_id='task_6', databricks_conn_id='connection_id_details', existing_cluster_id='{{ dag_run.conf.clusterId }}', libraries= [ { 'jar': 'dbfs:/task_6/task_6.jar' } ], spark_jar_task={ 'main_class_name': 'com.task_6.driver.TestClass6', 'parameters' : ['{{ dag_run.conf.json }}' ] } ) #################### ORDER OF OPERATORS ########################### task_1.dag = dag task_2.dag = dag task_3.dag = dag task_4.dag = dag task_5.dag = dag task_6.dag = dag task_1 >> [task_2 , task_3] >> [ task_4 , task_5 ] >> task_6 

Answer: What is your desired Task Dependency? Do you want to run task_4 after task_2 only or after task_2 and task_3 Based on that answer, use one of the following: (use this if task_4 should run after both task_2 and task_3 are completed) task_1 >> [task_2 , task_3] task_2 >> [task_4, task_5] >> task_6 task_3 >> [task_4, task_5]  OR (use this if task_4 should run after task_2 is completed and task_5 should run after task_3 is completed) task_1 >> [task_2 , task_3] task_2 >> task_4 task_3 >> task_5 [task_4, task_5] >> task_6  A tip, you don't need to do the following:  task_1.dag = dag task_2.dag = dag task_3.dag = dag task_4.dag = dag task_5.dag = dag task_6.dag = dag  You can pass the dag parameter to your task itself, example: task_6 = DatabricksSubmitRunOperator( task_id='task_6', dag=dag, databricks_conn_id='connection_id_details', existing_cluster_id='{{ dag_run.conf.clusterId }}', libraries= [ { 'jar': 'dbfs:/task_6/task_6.jar' } ], spark_jar_task={ 'main_class_name': 'com.task_6.driver.TestClass6', 'parameters' : ['{{ dag_run.conf.json }}' ] } )  or use DAG as your context manager as documented in https://airflow.apache.org/docs/stable/concepts.html#context-manager and Point (1) in https://medium.com/datareply/airflow-lesser-known-tips-tricks-and-best-practises-cf4d4a90f8f