Process & Analyze Sage 200 Data in Databricks (AWS)

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 Sage 200 data. This article explains how to host the CData JDBC Driver in AWS, as well as connect to and process live Sage 200 data in Databricks.

With built-in optimized data processing, the CData JDBC Driver offers unmatched performance for interacting with live Sage 200 data. When you issue complex SQL queries to Sage 200, the driver pushes supported SQL operations, like filters and aggregations, directly to Sage 200 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 Sage 200 data using native data types.

Install the CData JDBC Driver in Databricks

To work with live Sage 200 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.sage200.jar) from the installation location (typically C:\Program Files\CData[product_name]\lib).

👁 Loading the JDBC JAR File into AWS

Access Sage 200 Data in your Notebook: Python

With the JAR file installed, we are ready to work with live Sage 200 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 Sage 200, and create a basic report.

Configure the Connection to Sage 200

Connect to Sage 200 by referencing the JDBC Driver class and constructing a connection string to use in the JDBC URL. Additionally, you will need to set the property in the JDBC URL (unless you are using a Beta driver). You can view the licensing file included in the installation for information on how to set this property.

Step 1: Connection Information

driver = "cdata.jdbc.sage200.Sage200Driver"
url = "jdbc:sage200:RTK=5246...;SubscriptionKey=12345;Schema=StandardUK;InitiateOAuth=GETANDREFRESH;"

Built-in Connection String Designer

For assistance in constructing the JDBC URL, use the connection string designer built into the Sage 200 JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

java -jar cdata.jdbc.sage200.jar

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

• Schema: Determines which Sage 200 edition you are connecting to. Specify either StandardUK or ProfessionalUK.
• Subscription Key: Provides access to the APIs that are used to establish a connection. You will first need to log into the Sage 200 API website and subscribe to the API edition that matches your account. You can do so here: https://developer.columbus.sage.com/docs/services/api/uk. Afterwards, the subscription key may be found in your profile after logging into Sage 200.

👁 Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)

Load Sage 200 Data

Once you configure the connection, you can load Sage 200 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" , "Banks") \
	.load ()

Display Sage 200 Data

Check the loaded Sage 200 data by calling the display function.

Step 3: Checking the result

display (remote_table.select ("Id"))

👁 Displaying Sage 200 Data

Analyze Sage 200 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 Sage 200 data for reporting, visualization, and analysis.

% sql

SELECT Id, Code FROM SAMPLE_VIEW ORDER BY Code DESC LIMIT 5

👁 Displaying Sage 200 Data

The data from Sage 200 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 Sage 200 and start working with your live Sage 200 data in Databricks. Reach out to our Support Team if you have any questions.