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

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

Install the CData JDBC Driver for Dynamics GP

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

Start a Spark Shell and Connect to Dynamics GP Data

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

   To authenticate set the User and Password connection properties.

   To connect set the URL to the Web services endpoint; for example, http://{servername}:{port}/Dynamics/GPService. Additionally, set CompanyId; you can obtain this value in the company setup window: Click Tools -> Setup -> Company.

   By default, data summaries are not returned to save performance. Set LookupIds to true to return details such as line items; however, note that entities must be retrieved one at a time.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.dynamicsgp.jar

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

   Configure the connection to Dynamics GP, using the connection string generated above.

   scala> val dynamicsgp_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:dynamicsgp:CompanyId=mycompanyId;user=myuser;password=mypassword;URL= http://{servername}:{port}/Dynamics/GPService;").option("dbtable","SalesInvoice").option("driver","cdata.jdbc.dynamicsgp.DynamicsGPDriver").load()
3. Once you connect and the data is loaded you will see the table schema displayed.

4. Register the Dynamics GP data as a temporary table:

   scala> dynamicsgp_df.registerTable("salesinvoice")

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

   scala> dynamicsgp_df.sqlContext.sql("SELECT CustomerName, TotalAmount FROM SalesInvoice WHERE CustomerName = Bob").collect.foreach(println)

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

Using the CData JDBC Driver for Dynamics GP in Apache Spark, you are able to perform fast and complex analytics on Dynamics GP 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.