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Get the Report →How to connect and process Smartsheet Data from Azure Databricks
Use CData, Azure, and Databricks to perform data engineering and data science on live Smartsheet 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 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.
About Smartsheet Data Integration
CData provides the easiest way to access and integrate live data from Smartsheet. Customers use CData connectivity to:
- Read and write attachments, columns, comments and discussions.
- View the data in individuals cells, report on cell history, and more.
- Perform Smartsheet-specific actions like deleting or downloading attachments, creating, copying, deleting, or moving sheets, and moving or copying rows to another sheet.
Users frequently integrate Smartsheet with analytics tools such as Tableau, Crystal Reports, and Excel. Others leverage our tools to replicate Smartsheet data to databases or data warehouses.
Getting Started
Install the CData JDBC Driver in Azure
To work with live Smartsheet data in Databricks, install the driver on your Azure cluster.
- Navigate to your Databricks administration screen and select the target cluster.
- On the Libraries tab, click "Install New."
- Select "DBFS" as the Library Source and "JAR" as the Library Type.
- Upload the JDBC JAR file (cdata.jdbc.smartsheet.jar) from the installation location (typically C:\Program Files\CData\CData JDBC Driver for Smartsheet\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 workbook, make sure Python is selected as the language (which should be by default), click on Connect and under General Compute select the cluster where you installed the JDBC driver (should be selected by default).

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.
java -jar cdata.jdbc.smartsheet.jar
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.
result = spark.sql("SELECT TaskName, Progress FROM SAMPLE_VIEW")
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.