How to work with Dynamics 365 Business Central 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 Dynamics 365 Business Central, Spark can work with live Dynamics 365 Business Central data. This article describes how to connect to and query Dynamics 365 Business Central data from a Spark shell.

The CData JDBC Driver offers unmatched performance for interacting with live Dynamics 365 Business Central data due to optimized data processing built into the driver. When you issue complex SQL queries to Dynamics 365 Business Central, the driver pushes supported SQL operations, like filters and aggregations, directly to Dynamics 365 Business Central 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 Dynamics 365 Business Central data using native data types.

Install the CData JDBC Driver for Dynamics 365 Business Central

Download the CData JDBC Driver for Dynamics 365 Business Central installer, unzip the package, and run the JAR file to install the driver.

Start a Spark Shell and Connect to Dynamics 365 Business Central Data

1. Open a terminal and start the Spark shell with the CData JDBC Driver for Dynamics 365 Business Central JAR file as the jars parameter: $ spark-shell --jars /CData/CData JDBC Driver for Dynamics 365 Business Central/lib/cdata.jdbc.d365businesscentral.jar
2. With the shell running, you can connect to Dynamics 365 Business Central with a JDBC URL and use the SQL Context load() function to read a table.

   To authenticate to Dynamics 365 Business Central, you must provide the User and AccessKey properties.

   To obtain the User and AccessKey values, navigate to the Users page in Dynamics 365 Business Central and then click on Edit. The User Name and Web Service Access Key values are what you will enter as the User and AccessKey connection string properties. Note that the User Name is not your email address. It is a shortened user name.

   To connect to data, specify OrganizationUrl. If you have multiple companies in your organization, you must also specify the Company to indicate which company you would like to connect to. Company does not need to be specified if you have only one company.

   Built-in Connection String Designer

   For assistance in constructing the JDBC URL, use the connection string designer built into the Dynamics 365 Business Central JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

   java -jar cdata.jdbc.d365businesscentral.jar

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

   Configure the connection to Dynamics 365 Business Central, using the connection string generated above.

   scala> val d365businesscentral_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:d365businesscentral:OrganizationUrl=https://myaccount.financials.dynamics.com/;").option("dbtable","Accounts").option("driver","cdata.jdbc.d365businesscentral.D365BusinessCentralDriver").load()
3. Once you connect and the data is loaded you will see the table schema displayed.

4. Register the Dynamics 365 Business Central data as a temporary table:

   scala> d365businesscentral_df.registerTable("accounts")

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

   scala> d365businesscentral_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:

Using the CData JDBC Driver for Dynamics 365 Business Central in Apache Spark, you are able to perform fast and complex analytics on Dynamics 365 Business Central data, combining the power and utility of Spark with your data. Download a free, 30 day trial of any of the 200+ CData JDBC Drivers and get started today.