To understand the primitive features that can be leveraged in yourĭAGs. It’s worth taking the time to understand the parameters of BaseOperator # Python Sensor for tracking a REST APU.All operators are derived from BaseOperator and acquire muchįunctionality through inheritance. # It can be later used for example in a BranchPythonOperator # Push the value of state as xcom key, value pair. If state = 'finished' or state = 'failed': # Keep polling the REST API to check state of application submission until a Res = requests.get(finalurl,headers=headers) # Construct the REST API endpoint dynamically based on the dataįinalurl = ae_url+instance_id+'/spark_applications/'+application_id+'/state' # Python callable for getting a Bearer Token api_key='CHANGEME' # Import statements and DAG definition import jsonįrom import PythonOperator Source code for serverless_spark_pipeline.py I had initially tried the SimpleHttpOperator – but found the PythonOperator to be more flexible! ) How to dynamically construct the REST API endpoint based on the value returned from a previous task ( NOTE: This is one use case where I found the power and simplicity of PythonOperator come into play.How to use PythonSensor operator to poll/wait for asynchronous task completion.Concept of passing data between tasks using xcom.And use that Bearer Token in subsequent API calls that call some business logic (in this case, it is calling a Spark application on a cloud provider API).How to use the PythonOperator and callable to make REST API calls to generate a Bearer Token.The following working code covers the following concepts. Note that all the operators are connected using the same “ dag” object reference. DummyOperator – which is a convenience operator to try out some POC flow quickly or in this case- gives a structure to the flow – start and end.BranchPythonOperator – which is useful when you want the workflow to take different paths based on some conditional logic.PythonOperator – which calls the Python callable or function which contains the actual task processing logic.Here is where we have the breakdown of tasks in the flow. Python_callable=_determine_production_dosage,Įnd = DummyOperator(task_id='end',trigger_rule='one_success', dag=dag) Task_id='run_analysis_on_all_patient_data_on_s3_dumps',ĭetermine_production_dosage = BranchPythonOperator( Task_id='fetch_data_from_upstream_cloudant_application3_and_dump_to_s3', Task_id='fetch_data_from_upstream_REST_application2_and_dump_to_s3', Task_id='watch_for_data_dump_on_s3_bucket_pushed_byx_upstream_application_1', Start = DummyOperator(task_id='start', dag=dag) Here’s where you give the name of the workflow process that you want to see in the UI, the default retries for tasks, etc dag = DAG( Then comes the definition of the DAG constructor/initialization. This is where the beauty of Airflow comes into play.įrom imp ort PythonOperatorįrom import BranchPythonOperatorįrom import PythonSensorįrom import DummyOperatorĢ. You need to now run your analytics application against the data from all these upstream systems before running the downstream app. One pushes data to an S3 bucket another gives a REST API-based interface from which you need to fetch data, and yet another in-house system dumps data to a database. Let’s say two more upstream hospitals get added to the fray. Initially, a simple cron job or a Jenkins-based job might suffice until things get bigger. A further requirement is that the output of that analysis needs to be pushed as input to a time-critical downstream application which determines the composition and quantity of factory production units for a test medicine for that day. You need that application run daily against the data that comes in from the hospital. You have developed that awesome Apache Spark-based application, which is working like a charm. So, where does a workflow management system fit? And how do you know you need to use it? Let’s say you are working for the IT division of a health care organization, and you need to run some analytics on patient records that you receive from a vendor hospital.
0 Comments
Leave a Reply. |