How to connect and process Smartsheet 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 Smartsheet data. This article walks through hosting the CData JDBC Driver in Azure, as well as connecting to and processing live Smartsheet data in Databricks.

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

Install the CData JDBC Driver in Azure

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

Connect to Smartsheet from Databricks

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

Configure the Connection to Smartsheet

Connect to Smartsheet 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.smartsheet.SmartsheetDriver"
url = "jdbc:smartsheet:RTK=5246...;OAuthClientId=MyOauthClientId;OAuthClientSecret=MyOAuthClientSecret;CallbackURL=http://localhost:33333;InitiateOAuth=GETANDREFRESH"

Built-in Connection String Designer

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

Smartsheet uses the OAuth authentication standard. To authenticate using OAuth, you will need to register an app to obtain the OAuthClientId, OAuthClientSecret, and CallbackURL connection properties.

However, for testing purposes you can instead use the Personal Access Token you get when you create an application; set this to the OAuthAccessToken connection property.

Load Smartsheet Data

Once the connection is configured, you can load Smartsheet 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" , "Sheet_Event_Plan_Budget") \
	.load ()

Display Smartsheet Data

Check the loaded Smartsheet data by calling the display function.

display (remote_table.select ("TaskName"))

Analyze Smartsheet 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 Smartsheet data for analysis.

% sql

SELECT TaskName, Progress FROM Sheet_Event_Plan_Budget

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