Process & Analyze Google Ads 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 Google Ads data. This article walks through hosting the CData JDBC Driver in AWS, as well as connecting to and processing live Google Ads data in Databricks.

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

Install the CData JDBC Driver in Databricks

To work with live Google Ads 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.googleads.jar) from the installation location (typically C:\Program Files\CData[product_name]\lib).

Access Google Ads Data in your Notebook: Python

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

Configure the Connection to Google Ads

Connect to Google Ads 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.googleads.GoogleAdsDriver"
url = "jdbc:googleads:RTK=5246...;DeveloperToken=MyDeveloperToken;ClientCustomerId=MyClientCustomerId;InitiateOAuth=GETANDREFRESH"

Built-in Connection String Designer

For assistance in constructing the JDBC URL, use the connection string designer built into the Google Ads 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.

Google uses the OAuth authentication standard. To access Google APIs on behalf on individual users, you can use the embedded credentials or you can register your own OAuth app.

OAuth also enables you to use a service account to connect on behalf of users in a Google Apps domain. To authenticate with a service account, you will need to register an application to obtain the OAuth JWT values.

In addition to the OAuth values, specify the DeveloperToken and ClientCustomerId.

See the "Getting Started" chapter of the help documentation for a guide to using OAuth.

Load Google Ads Data

Once you configure the connection, you can load Google Ads 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" , "CampaignPerformance") \
	.load ()

Display Google Ads Data

Check the loaded Google Ads data by calling the display function.

Step 3: Checking the result

display (remote_table.select ("Device"))

Analyze Google Ads 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 Google Ads data for reporting, visualization, and analysis.

% sql

SELECT Device, Clicks FROM SAMPLE_VIEW ORDER BY Clicks DESC LIMIT 5

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