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

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

Install the CData JDBC Driver in Databricks

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

Access Monday.com Data in your Notebook: Python

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

Configure the Connection to Monday.com

Connect to Monday.com 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.monday.MondayDriver"
url = "jdbc:monday:RTK=5246...;APIToken=eyJhbGciOiJIUzI1NiJ9.yJ0aWQiOjE0MTc4NzIxMiwidWlkIjoyNzI3ODM3OSwiaWFkIjoiMjAyMi0wMS0yMFQxMDo0NjoxMy45NDFaIiwicGV;"

Built-in Connection String Designer

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

You can connect to Monday.com using either API Token authentication or OAuth authentication.

Connecting with an API Token

Connect to Monday.com by specifying the APIToken. Set the AuthScheme to Token and obtain the APIToken as follows:

• API tokens for admin users
  1. Log in to your Monday.com account and click on your avatar in the bottom left corner.
  2. Select Admin.
  3. Select "API" on the left side of the Admin page.
  4. Click the "Copy" button to copy the user's API token.
• API tokens for non-admin users
  1. Click on your profile picture in the bottom left of your screen.
  2. Select "Developers"
  3. Click "Developer" and then "My Access Tokens" at the top.
  4. Select "Show" next to the API token, where you'll be able to copy it.

Connecting with OAuth Authentication

Alternatively, you can establish a connection using OAuth (refer to the OAuth section of the Help documentation).

Load Monday.com Data

Once you configure the connection, you can load Monday.com 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" , "Invoices") \
	.load ()

Display Monday.com Data

Check the loaded Monday.com data by calling the display function.

Step 3: Checking the result

display (remote_table.select ("Id"))

Analyze Monday.com 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 Monday.com data for reporting, visualization, and analysis.

% sql

SELECT Id, DueDate FROM SAMPLE_VIEW ORDER BY DueDate DESC LIMIT 5

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