Process & Analyze Adobe Commerce Data in Databricks (AWS)

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 Adobe Commerce data. This article walks through hosting the CData JDBC Driver in AWS, as well as connecting to and processing live Adobe Commerce data in Databricks.

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

Install the CData JDBC Driver in Databricks

To work with live Adobe Commerce data in Databricks, install the driver on your Databricks 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.adobe commerce.jar) from the installation location (typically C:\Program Files\CData[product_name]\lib).

Access Adobe Commerce Data in your Notebook: Python

With the JAR file installed, we are ready to work with live Adobe Commerce 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 Adobe Commerce, and create a basic report.

Configure the Connection to Adobe Commerce

Connect to Adobe Commerce by referencing the JDBC Driver class 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.

Step 1: Connection Information

driver = "cdata.jdbc.adobe commerce.Adobe CommerceDriver"
url = "jdbc:adobe commerce:RTK=5246...;OAuthClientId=MyConsumerKey;OAuthClientSecret=MyConsumerSecret;CallbackURL=http://127.0.0.1:33333;Url=https://myAdobe Commercehost.com;InitiateOAuth=GETANDREFRESH"

Built-in Connection String Designer

For assistance in constructing the JDBC URL, use the connection string designer built into the Adobe Commerce 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.

Adobe Commerce uses the OAuth 1 authentication standard. To connect to the Adobe Commerce REST API, you will need to obtain values for the OAuthClientId, OAuthClientSecret, and CallbackURL connection properties by registering an app with your Adobe Commerce system. See the "Getting Started" section in the help documentation for a guide to obtaining the OAuth values and connecting.

You will also need to provide the URL to your Adobe Commerce system. The URL depends on whether you are using the Adobe Commerce REST API as a customer or administrator.

• Customer: To use Adobe Commerce as a customer, make sure you have created a customer account in the Adobe Commerce homepage. To do so, click Account -> Register. You can then set the URL connection property to the endpoint of your Adobe Commerce system.

• Administrator: To access Adobe Commerce as an administrator, set CustomAdminPath instead. This value can be obtained in the Advanced settings in the Admin menu, which can be accessed by selecting System -> Configuration -> Advanced -> Admin -> Admin Base URL.

  If the Use Custom Admin Path setting on this page is set to YES, the value is inside the Custom Admin Path text box; otherwise, set the CustomAdminPath connection property to the default value, which is "admin".

Load Adobe Commerce Data

Once you configure the connection, you can load Adobe Commerce data as a dataframe using the CData JDBC Driver and the connection information.

Step 2: Reading the data

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

Display Adobe Commerce Data

Check the loaded Adobe Commerce data by calling the display function.

Step 3: Checking the result

display (remote_table.select ("Name"))

Analyze Adobe Commerce Data in Databricks

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

Step 4: Create a view or table

remote_table.createOrReplaceTempView ( "SAMPLE_VIEW" )

With the Temp View created, you can use SparkSQL to retrieve the Adobe Commerce data for reporting, visualization, and analysis.

% sql

SELECT Name, Price FROM SAMPLE_VIEW ORDER BY Price DESC LIMIT 5

The data from Adobe Commerce 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 Adobe Commerce and start working with your live Adobe Commerce data in Databricks. Reach out to our Support Team if you have any questions.