Process & Analyze Adobe Analytics Data in Databricks (AWS)

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Adobe Analytics JDBC Driver

Rapidly create and deploy powerful Java applications that integrate with Adobe Analytics data including Metrics, Users, Reports, Segments, and more!



Host the CData JDBC Driver for Adobe Analytics in AWS and use Databricks to perform data engineering and data science on live Adobe Analytics data.

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

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

Install the CData JDBC Driver in Databricks

To work with live Adobe Analytics 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.adobeanalytics.jar) from the installation location (typically C:\Program Files\CData\CData JDBC Driver for Adobe Analytics\lib).

Access Adobe Analytics Data in your Notebook: Python

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

Configure the Connection to Adobe Analytics

Connect to Adobe Analytics by referencing the JDBC Driver class and constructing a connection string to use in the JDBC URL.

Step 1: Connection Information

driver = "cdata.jdbc.adobeanalytics.AdobeAnalyticsDriver"
url = "jdbc:adobeanalytics:GlobalCompanyId=myGlobalCompanyId; RSID=myRSID; OAuthClientId=myOauthClientId; OauthClientSecret=myOAuthClientSecret; CallbackURL=myCallbackURL;"

Built-in Connection String Designer

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

java -jar cdata.jdbc.adobeanalytics.jar

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

Adobe Analytics uses the OAuth authentication standard. To authenticate using OAuth, you will need to create an app to obtain the OAuthClientId, OAuthClientSecret, and CallbackURL connection properties. See the "Getting Started" section of the help documentation for a guide.

Retrieving GlobalCompanyId

GlobalCompanyId is a required connection property. If you do not know your Global Company ID, you can find it in the request URL for the users/me endpoint on the Swagger UI. After logging into the Swagger UI Url, expand the users endpoint and then click the GET users/me button. Click the Try it out and Execute buttons. Note your Global Company ID shown in the Request URL immediately preceding the users/me endpoint.

Retrieving Report Suite Id

Report Suite ID (RSID) is also a required connection property. In the Adobe Analytics UI, navigate to Admin -> Report Suites and you will get a list of your report suites along with their identifiers next to the name.

After setting the GlobalCompanyId, RSID and OAuth connection properties, you are ready to connect to Adobe Analytics.

Load Adobe Analytics Data

Once you configure the connection, you can load Adobe Analytics 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" , "AdsReport") \
	.load ()

Display Adobe Analytics Data

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

Step 3: Checking the result

display (remote_table.select ("Page"))

Analyze Adobe Analytics 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 Analytics data for reporting, visualization, and analysis.

% sql

SELECT Page, PageViews FROM SAMPLE_VIEW ORDER BY PageViews DESC LIMIT 5

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