How to integrate SAP Netweaver Gateway with Apache Airflow

Apache Airflow supports the creation, scheduling, and monitoring of data engineering workflows. When paired with the CData JDBC Driver for SAP Netweaver Gateway, Airflow can work with live SAP Netweaver Gateway data. This article describes how to connect to and query SAP Netweaver Gateway data from an Apache Airflow instance and store the results in a CSV file.

With built-in optimized data processing, the CData JDBC Driver offers unmatched performance for interacting with live SAP Netweaver Gateway data. When you issue complex SQL queries to SAP Netweaver Gateway, the driver pushes supported SQL operations, like filters and aggregations, directly to SAP Netweaver Gateway and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations). Its built-in dynamic metadata querying allows you to work with and analyze SAP Netweaver Gateway data using native data types.

Configuring the Connection to SAP Netweaver Gateway

Built-in Connection String Designer

For assistance in constructing the JDBC URL, use the connection string designer built into the SAP Netweaver Gateway JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

Fill in the connection properties and copy the connection string to the clipboard.

SAP Gateway allows both basic and OAuth 2.0 authentication. You can use basic authentication to connect to your own account, or you can use OAuth to enable other users to retrieve data from your service with their accounts. In addition to authenticating, set the following connection properties to access SAP Gateway tables.

• Url: Set this to the URL of your environment, or to the full URL of the service. For example, the full URL might appear as: https://sapes5.sapdevcenter.com/sap/opu/odata/IWBEP/GWSAMPLE_BASIC/. In this example, the environment URL would just be: https://sapes5.sapdevcenter.com.
• Namespace: Set the appropriate Service Namespace. In the example above, IWBEP is the namespace. It is optional if the full URL to the service is specified.
• Service: Set this to the service you want to retrieve data from. In the example above, the service is GWSAMPLE_BASIC. It is not required if the full URL is specified.

Authenticate via Basic Authentication

In basic authentication, you use your login credentials to connect. Set the following properties:

• User: This is the username you use to log in to SAP Gateway.
• Password: This is the password you use to log in to SAP Gateway.

Authenticate via OAuth Authentication

You can connect to SAP Gateway using the embedded OAuth connectivity (without setting any additional authentication connection properties). When you connect, the OAuth endpoint opens in your browser. Log in and grant permissions to complete the OAuth process. See the OAuth section in the online Help documentation for more information on other OAuth authentication flows.

To host the JDBC driver in clustered environments or in the cloud, you will need a license (full or trial) and a Runtime Key (RTK). For more information on obtaining this license (or a trial), contact our sales team.

The following are essential properties needed for our JDBC connection.

Establishing a JDBC Connection within Airflow

1. Log into your Apache Airflow instance.
2. On the navbar of your Airflow instance, hover over Admin and then click Connections.
3. Next, click the + sign on the following screen to create a new connection.
4. In the Add Connection form, fill out the required connection properties:
   • Connection Id: Name the connection, i.e.: sapgateway_jdbc
   • Connection Type: JDBC Connection
   • Connection URL: The JDBC connection URL from above, i.e.: jdbc:sapgateway:RTK=5246...;User=user;Password=password;URL=https://sapes5.sapdevcenter.com/sap/opu/odata/IWBEP/GWSAMPLE_BASIC/;InitiateOAuth=GETANDREFRESH)
   • Driver Class: cdata.jdbc.sapgateway.SAPGatewayDriver
   • Driver Path: PATH/TO/cdata.jdbc.sapgateway.jar
5. Test your new connection by clicking the Test button at the bottom of the form.
6. After saving the new connection, on a new screen, you should see a green banner saying that a new row was added to the list of connections:

Creating a DAG

A DAG in Airflow is an entity that stores the processes for a workflow and can be triggered to run this workflow. Our workflow is to simply run a SQL query against SAP Netweaver Gateway data and store the results in a CSV file.

1. To get started, in the Home directory, there should be an "airflow" folder. Within there, we can create a new directory and title it "dags". In here, we store Python files that convert into Airflow DAGs shown on the UI.
2. Next, create a new Python file and title it sap netweaver gateway_hook.py. Insert the following code inside of this new file:

   	import time
   	from datetime import datetime
   	from airflow.decorators import dag, task
   	from airflow.providers.jdbc.hooks.jdbc import JdbcHook
   	import pandas as pd
   
   	# Declare Dag
   	@dag(dag_id="sap netweaver gateway_hook", schedule_interval="0 10 * * *", start_date=datetime(2022,2,15), catchup=False, tags=['load_csv'])
   	
   	# Define Dag Function
   	def extract_and_load():
   	# Define tasks
   		@task()
   		def jdbc_extract():
   			try:
   				hook = JdbcHook(jdbc_conn_id="jdbc")
   				sql = """ select * from Account """
   				df = hook.get_pandas_df(sql)
   				df.to_csv("/{some_file_path}/{name_of_csv}.csv",header=False, index=False, quoting=1)
   				# print(df.head())
   				print(df)
   				tbl_dict = df.to_dict('dict')
   				return tbl_dict
   			except Exception as e:
   				print("Data extract error: " + str(e))
               
   		jdbc_extract()
       
   	sf_extract_and_load = extract_and_load()
   

3. Save this file and refresh your Airflow instance. Within the list of DAGs, you should see a new DAG titled "sap netweaver gateway_hook".
4. Click on this DAG and, on the new screen, click on the unpause switch to make it turn blue, and then click the trigger (i.e. play) button to run the DAG. This executes the SQL query in our sap netweaver gateway_hook.py file and export the results as a CSV to whichever file path we designated in our code.
5. After triggering our new DAG, we check the Downloads folder (or wherever you chose within your Python script), and see that the CSV file has been created - in this case, account.csv.
6. Open the CSV file to see that your SAP Netweaver Gateway data is now available for use in CSV format thanks to Apache Airflow.

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