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Work with Epicor ERP Data in Apache Spark Using SQL

Access and process Epicor ERP Data in Apache Spark using the CData JDBC Driver.

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

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

Install the CData JDBC Driver for Epicor ERP

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

Start a Spark Shell and Connect to Epicor ERP Data

  1. Open a terminal and start the Spark shell with the CData JDBC Driver for Epicor ERP JAR file as the jars parameter: $ spark-shell --jars /CData/CData JDBC Driver for Epicor ERP/lib/cdata.jdbc.epicorerp.jar
  2. With the shell running, you can connect to Epicor ERP 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,
    • 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 ERP JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

    java -jar cdata.jdbc.epicorerp.jar

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

    scala> val epicorerp_df ="jdbc").option("url", "jdbc:epicorerp:ervice=Erp.BO.CustomerSvc;ERPInstance=MyInstance;URL=;User=username;Password=password;").option("dbtable","Customers").option("driver","cdata.jdbc.epicorerp.EpicorERPDriver").load()
  3. Once you connect and the data is loaded you will see the table schema displayed.
  4. Register the Epicor ERP data as a temporary table:

    scala> epicorerp_df.registerTable("customers")
  5. Perform custom SQL queries against the Data using commands like the one below:

    scala> epicorerp_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 ERP in Apache Spark, you are able to perform fast and complex analytics on Epicor ERP data, combining the power and utility of Spark with your data. Download a free, 30 day trial of any of the 170+ CData JDBC Drivers and get started today.