Process & Analyze Dynamics NAV Data in Databricks (AWS)

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Dynamics NAV JDBC Driver

Rapidly create and deploy powerful Java applications that integrate with Dynamics NAV account data including Items, Sales Orders, Purchase Orders, and more!



Host the CData JDBC Driver for Dynamics NAV in AWS and use Databricks to perform data engineering and data science on live Dynamics NAV 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 Dynamics NAV data. This article walks through hosting the CData JDBC Driver in AWS, as well as connecting to and processing live Dynamics NAV data in Databricks.

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

Install the CData JDBC Driver in Databricks

To work with live Dynamics NAV 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.dynamicsnav.jar) from the installation location (typically C:\Program Files\CData\CData JDBC Driver for Dynamics NAV\lib).

Access Dynamics NAV Data in your Notebook: Python

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

Configure the Connection to Dynamics NAV

Connect to Dynamics NAV by referencing the JDBC Driver class and constructing a connection string to use in the JDBC URL.

Step 1: Connection Information

driver = "cdata.jdbc.dynamicsnav.DynamicsNAVDriver"
url = "jdbc:dynamicsnav:http://myserver:7048;User=myserver\Administrator;Password=admin;ServerInstance=DYNAMICSNAV71;"

Built-in Connection String Designer

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

java -jar cdata.jdbc.dynamicsnav.jar

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

Before you can connect, OData Services will need to be enabled on the server. Once OData Services are enabled, you will be able to query any Services that are published on the server.

The User and Password properties, under the Authentication section, must be set to valid Dynamics NAV user credentials. In addition, you will need to specify a URL to a valid Dynamics NAV server organization root and a ServerInstance. If there is not a Service Default Company for the server, you will need to set the Company as well.

Load Dynamics NAV Data

Once you configure the connection, you can load Dynamics NAV 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" , "Customer") \
	.load ()

Display Dynamics NAV Data

Check the loaded Dynamics NAV data by calling the display function.

Step 3: Checking the result

display (remote_table.select ("Name"))

Analyze Dynamics NAV 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 Dynamics NAV data for reporting, visualization, and analysis.

% sql

SELECT Name, Prices_Including_VAT FROM SAMPLE_VIEW ORDER BY Prices_Including_VAT DESC LIMIT 5

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