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

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

Install the CData JDBC Driver for Epicor Kinetic

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

Start a Spark Shell and Connect to Epicor Kinetic Data

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

   To successfully connect to your ERP instance, you must specify the following connection properties:

   • Url:the URL of the server hosting your ERP instance. For example, https://myserver.EpicorSaaS.com
   • ERPInstance: the name of your ERP instance.
   • User: the username of your account.
   • Password: the password of your account.
   • Service: the service you want to retrieve data from. For example, BaqSvc.

   In addition, you may also set the optional connection properties:

   • ApiKey: An optional key that may be required for connection to some services depending on your account configuration.
   • ApiVersion: Defaults to v1. May be set to v2 to use the newer Epicor API.
   • Company: Required if you set the ApiVersion to v2.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.epicorkinetic.jar

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

   Configure the connection to Epicor Kinetic, using the connection string generated above.

   scala> val epicorkinetic_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:epicorkinetic:Service=Erp.BO.CustomerSvc;ERPInstance=MyInstance;URL=https://myaccount.epicorsaas.com;User=username;Password=password;").option("dbtable","Customers").option("driver","cdata.jdbc.epicorkinetic.epicorKineticDriver").load()
3. Once you connect and the data is loaded you will see the table schema displayed.

4. Register the Epicor Kinetic data as a temporary table:

   scala> epicorkinetic_df.registerTable("customers")

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

   scala> epicorkinetic_df.sqlContext.sql("SELECT CustNum, Company FROM Customers WHERE CompanyName = CompanyName").collect.foreach(println)

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

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