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

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

Install the CData JDBC Driver in Databricks

To work with live Outlook 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).

👁 Loading the JDBC JAR File into AWS

Access Outlook Data in your Notebook: Python

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

Configure the Connection to Outlook

Connect to Outlook by referencing the JDBC Driver class and constructing a connection string to use in the JDBC URL. Additionally, you will need to set the 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\Outlook.apip;AuthScheme=OAuth;InitiateOAuth=GETANDREFRESH;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;TenantId=your_tenant_id;CallbackUrl=http://localhost:33333;"

Built-in Connection String Designer

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

Using OAuth Authentication

Microsoft Graph API uses OAuth 2.0 for authentication. You must register an application in the Microsoft Azure Portal to obtain OAuth credentials (Client ID and Client Secret).

Obtaining OAuth Credentials

1. Log in to the Azure Portal.
2. Navigate to Azure Active Directory > App registrations.
3. Click New registration to create a new application.
4. Enter an application name and select the appropriate account types.
5. Set the Redirect URI to your application's callback URL (e.g., http://localhost:33333 for desktop apps).
6. Click Register to create the application.
7. On the application overview page, copy the Application (client) ID - this is your OAuthClientId.
8. Navigate to Certificates & secrets and create a new client secret.
9. Copy the client secret value - this is your OAuthClientSecret.
10. Navigate to API permissions and add the required Microsoft Graph API permissions:
    • Mail.Read - For accessing email messages
    • Contacts.Read - For accessing contacts
    • Calendars.Read - For accessing calendar events
    • Tasks.Read - For accessing To Do tasks
    • offline_access - For obtaining refresh tokens
11. Click Grant admin consent to grant these permissions.

Connecting with OAuth

After setting the following connection properties, you are ready to connect:

• AuthScheme: Set this to OAuth.
• InitiateOAuth: Set this to GETANDREFRESH. The CData API Profile for Outlook will automatically walk through the OAuth process in order to obtain the access token.
• OAuthClientId: Set this to the Application (client) ID from Azure Portal.
• OAuthClientSecret: Set this to the client secret value from Azure Portal.
• TenantId: Set this to your Azure AD tenant identifier (GUID or domain name like 'contoso.onmicrosoft.com').
• CallbackURL: Set this to the Redirect URI you specified in your app registration (e.g., http://localhost:33333 for desktop apps).

Example connection string

Profile=C:\profiles\Outlook.apip;AuthScheme=OAuth;InitiateOAuth=GETANDREFRESH;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;TenantId=your_tenant_id;CallbackUrl=http://localhost:33333;

👁 Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)

Load Outlook Data

Once you configure the connection, you can load Outlook 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" , "CalendarGroupCalendars") \
	.load ()

Display Outlook Data

Check the loaded Outlook data by calling the display function.

Step 3: Checking the result

display (remote_table.select (""))

👁 Displaying Outlook Data

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

% sql

SELECT , FROM SAMPLE_VIEW ORDER BY DESC LIMIT 5

👁 Displaying Outlook Data

The data from Outlook 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 Outlook data in Databricks. Reach out to our Support Team if you have any questions.