Process & Analyze Gong 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 Gong data. This article explains how to host the CData JDBC Driver in AWS, as well as connect to and process live Gong data in Databricks.

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

Install the CData JDBC Driver in Databricks

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

Access Gong Data in your Notebook: Python

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

Configure the Connection to Gong

Connect to Gong 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.api.APIDriver"
url = "jdbc:api:RTK=5246...;Profile=C:\profiles\Gong.apip;AuthScheme=APIKey;ProfileSettings='APIKey=your_api_key;APISecret=your_api_secret;Domain=your-tenant.api.gong.io';"

Built-in Connection String Designer

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

java -jar cdata.jdbc.api.jar

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

To authenticate to Gong, you can use API Key authentication with your Gong API Key and API Secret.

Authentication

To authenticate to Gong, you must provide your Gong API Key and API Secret, along with your tenant Domain. These credentials are combined and Base64-encoded to form the Basic authentication header used for all API requests.

Using API Key Authentication

To authenticate using an API Key, you need to obtain your API Key and API Secret from your Gong account settings.

You can then connect by setting the AuthScheme to APIKey and providing your credentials:

• AuthScheme: Set this to APIKey.
• APIKey: Set this to your Gong API Key.
• APISecret: Set this to your Gong API Secret.
• Domain: Set this to your Gong tenant domain (e.g., us-36533.api.gong.io).

Example connection string

Profile=C:\profiles\Gong.apip;AuthScheme=APIKey;ProfileSettings='APIKey=your_api_key;APISecret=your_api_secret;Domain=your-tenant.api.gong.io';

Load Gong Data

Once you configure the connection, you can load Gong 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" , "AnsweredScorecards") \
	.load ()

Display Gong Data

Check the loaded Gong data by calling the display function.

Step 3: Checking the result

display (remote_table.select (""))

Analyze Gong 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 Gong data for reporting, visualization, and analysis.

% sql

SELECT ,  FROM SAMPLE_VIEW ORDER BY  DESC LIMIT 5

The data from Gong 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 API Driver for JDBC and start working with your live Gong data in Databricks. Reach out to our Support Team if you have any questions.