Process & Analyze Epicor ERP Data in Databricks (AWS)

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Epicor ERP JDBC Driver

Rapidly create and deploy powerful Java applications that integrate with Epicor ERP ERP data, including Sales Orders, Purchase Orders, Accounts, and more!



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

With built-in optimized data processing, the CData JDBC Driver offers unmatched performance for interacting with live Epicor ERP data. 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 client-side (often SQL functions and JOIN operations). Its built-in dynamic metadata querying allows you to work with and analyze Epicor ERP data using native data types.

Install the CData JDBC Driver in Databricks

To work with live Epicor ERP 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.epicorerp.jar) from the installation location (typically C:\Program Files\CData\CData JDBC Driver for Epicor ERP\lib).

Access Epicor ERP Data in your Notebook: Python

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

Configure the Connection to Epicor ERP

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

Step 1: Connection Information

driver = "cdata.jdbc.epicorerp.EpicorERPDriver"
url = "jdbc:epicorerp:Service=Erp.BO.CustomerSvc;ERPInstance=MyInstance;URL=https://myaccount.epicorsaas.com;User=username;Password=password;InitiateOAuth=GETANDREFRESH"

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.

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.

Load Epicor ERP Data

Once you configure the connection, you can load Epicor ERP 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" , "Customers") \
	.load ()

Display Epicor ERP Data

Check the loaded Epicor ERP data by calling the display function.

Step 3: Checking the result

display (remote_table.select ("CustNum"))

Analyze Epicor ERP 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 Epicor ERP data for reporting, visualization, and analysis.

% sql

SELECT CustNum, Company FROM SAMPLE_VIEW ORDER BY Company DESC LIMIT 5

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