How to connect and process Authorize.Net Data from Azure Databricks

Databricks is a cloud-based service that provides data processing capabilities through Apache Spark. When paired with the CData JDBC Driver, customers can use Databricks to perform data engineering and data science on live Authorize.Net data. This article walks through hosting the CData JDBC Driver in Azure, as well as connecting to and processing live Authorize.Net data in Databricks.

With built-in optimized data processing, the CData JDBC Driver offers unmatched performance for interacting with live Authorize.Net data. When you issue complex SQL queries to Authorize.Net, the driver pushes supported SQL operations, like filters and aggregations, directly to Authorize.Net 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 Authorize.Net data using native data types.

Install the CData JDBC Driver in Azure

To work with live Authorize.Net data in Databricks, install the driver on your Azure cluster.

1. Navigate to your Databricks administration screen and select the target cluster.
2. On the Libraries tab, click "Install New."
3. Select "Upload" as the Library Source and "Jar" as the Library Type.
4. Upload the JDBC JAR file (cdata.jdbc.authorizenet.jar) from the installation location (typically C:\Program Files\CData[product_name]\lib).

Connect to Authorize.Net from Databricks

With the JAR file installed, we are ready to work with live Authorize.Net data in Databricks. Start by creating a new notebook in your workspace. Name the notebook, select Python as the language (though Scala is available as well), and choose the cluster where you installed the JDBC driver. When the notebook launches, we can configure the connection, query Authorize.Net, and create a basic report.

Configure the Connection to Authorize.Net

Connect to Authorize.Net by referencing the class for the JDBC Driver and constructing a connection string to use in the JDBC URL. Additionally, you will need to set the RTK property in the JDBC URL (unless you are using a Beta driver). You can view the licensing file included in the installation for information on how to set this property.

driver = "cdata.jdbc.authorizenet.AuthorizeNetDriver"
url = "jdbc:authorizenet:RTK=5246...;LoginId=MyLoginId;TransactionKey=MyTransactionKey;"

Built-in Connection String Designer

For assistance in constructing the JDBC URL, use the connection string designer built into the Authorize.Net 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.

You can obtain the necessary connection properties on the Security Settings -> General Settings page after logging into your Merchant Account.

• UseSandbox: The Authorize.Net API to be used to process transactions. If you are using a production account, this property can be left blank. If you are using a developer test account, set this to 'TRUE'.
• LoginID: The API login Id associated with your payment gateway account. This property is used to authenticate that you are authorized to submit website transactions. Note that this value is not the same as the login Id that you use to log in to the Merchant Interface.
• TransactionKey: The transaction key associated with your payment gateway account. This property is used to authenticate that you are authorized to submit website transactions.

Load Authorize.Net Data

Once the connection is configured, you can load Authorize.Net data as a dataframe using the CData JDBC Driver and the connection information.

remote_table = spark.read.format ( "jdbc" ) \
	.option ( "driver" , driver) \
	.option ( "url" , url) \
	.option ( "dbtable" , "SettledBatchList") \
	.load ()

Display Authorize.Net Data

Check the loaded Authorize.Net data by calling the display function.

display (remote_table.select ("MarketType"))

Analyze Authorize.Net Data in Azure Databricks

If you want to process data with Databricks SparkSQL, register the loaded data as a Temp View.

remote_table.createOrReplaceTempView ( "SAMPLE_VIEW" )

The SparkSQL below retrieves the Authorize.Net data for analysis.

% sql

SELECT MarketType, TotalCharge FROM SettledBatchList

The data from Authorize.Net is only available in the target notebook. If you want to use it with other users, save it as a table.

remote_table.write.format ( "parquet" ) .saveAsTable ( "SAMPLE_TABLE" )

Download a free, 30-day trial of the CData JDBC Driver for Authorize.Net and start working with your live Authorize.Net data in Azure Databricks. Reach out to our Support Team if you have any questions.