How to work with Microsoft Dataverse Data in Apache Spark using SQL

Apache Spark is a fast and general engine for large-scale data processing. When paired with the CData JDBC Driver for Microsoft Dataverse, Spark can work with live Microsoft Dataverse data. This article describes how to connect to and query Microsoft Dataverse data from a Spark shell.

The CData JDBC Driver offers unmatched performance for interacting with live Microsoft Dataverse data due to optimized data processing built into the driver. When you issue complex SQL queries to Microsoft Dataverse, the driver pushes supported SQL operations, like filters and aggregations, directly to Microsoft Dataverse and utilizes the embedded SQL engine to process unsupported operations (often SQL functions and JOIN operations) client-side. With built-in dynamic metadata querying, you can work with and analyze Microsoft Dataverse data using native data types.

Getting Started

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Install the CData JDBC Driver for Microsoft Dataverse

Download the CData JDBC Driver for Microsoft Dataverse installer, unzip the package, and run the JAR file to install the driver.

Start a Spark Shell and Connect to Microsoft Dataverse Data

1. Open a terminal and start the Spark shell with the CData JDBC Driver for Microsoft Dataverse JAR file as the jars parameter:

   $ spark-shell --jars /CData/CData JDBC Driver for Microsoft Dataverse/lib/cdata.jdbc.cds.jar
   

2. With the shell running, you can connect to Microsoft Dataverse with a JDBC URL and use the SQL Context load() function to read a table.

   You can connect without setting any connection properties for your user credentials. Below are the minimum connection properties required to connect.

   • InitiateOAuth: Set this to GETANDREFRESH. You can use InitiateOAuth to avoid repeating the OAuth exchange and manually setting the OAuthAccessToken.
   • OrganizationUrl: Set this to the organization URL you are connecting to, such as https://myorganization.crm.dynamics.com.
   • Tenant (optional): Set this if you wish to authenticate to a different tenant than your default. This is required to work with an organization not on your default Tenant.

   When you connect the Common Data Service OAuth endpoint opens in your default browser. Log in and grant permissions. The OAuth process completes automatically.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.cds.jar
   

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

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

   Configure the connection to Microsoft Dataverse, using the connection string generated above.

   scala> val cds_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:cds:OrganizationUrl=https://myaccount.crm.dynamics.com/;InitiateOAuth=GETANDREFRESH;").option("dbtable","Accounts").option("driver","cdata.jdbc.cds.CDSDriver").load()
   

3. Once you connect and the data is loaded you will see the table schema displayed.

4. Register the Microsoft Dataverse data as a temporary table:

   scala> cds_df.registerTable("accounts")

5. Perform custom SQL queries against the Data using commands like the one below:

   scala> cds_df.sqlContext.sql("SELECT AccountId, Name FROM Accounts WHERE Name = MyAccount").collect.foreach(println)

   You will see the results displayed in the console, similar to the following:

   👁 Data in Apache Spark (Salesforce is shown)
   

Using the CData JDBC Driver for Microsoft Dataverse in Apache Spark, you are able to perform fast and complex analytics on Microsoft Dataverse data, combining the power and utility of Spark with your data. Download a free, 30 day trial of any of the hundreds of CData JDBC Drivers and get started today.