Process & Analyze Reckon Accounts Hosted 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 Reckon Accounts Hosted data. This article explains how to host the CData JDBC Driver in AWS, as well as connect to and process live Reckon Accounts Hosted data in Databricks.

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

Install the CData JDBC Driver in Databricks

To work with live Reckon Accounts Hosted 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.reckonaccountshosted.jar) from the installation location (typically C:\Program Files\CData[product_name]\lib).

👁 Loading the JDBC JAR File into AWS

Access Reckon Accounts Hosted Data in your Notebook: Python

With the JAR file installed, we are ready to work with live Reckon Accounts Hosted 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 Reckon Accounts Hosted, and create a basic report.

Configure the Connection to Reckon Accounts Hosted

Connect to Reckon Accounts Hosted 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.reckonaccountshosted.ReckonAccountsHostedDriver"
url = "jdbc:reckonaccountshosted:RTK=5246...;SubscriptionKey=my_subscription_key;CountryVersion=2021.R2.AU;CompanyFile=Q:/CompanyName.QBW;User=my_user;Password=my_password;CallbackURL=http://localhost:33333;OAuthClientId=my_oauth_client_id;OAuthClientSecret=my_oauth_client_secret;InitiateOAuth=GETANDREFRESH;"

Built-in Connection String Designer

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

java -jar cdata.jdbc.reckonaccountshosted.jar

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

The connector makes requests to Reckon Accounts Hosted through OAuth. Specify the following connection properties:

• SubscriptionKey: Required. You get this value when you created your developer account.
• CountryVersion: Defaults to 2021.R2.AU.
• CompanyFile: Required. The path to the company file.
• User: Required. The username of the company file.
• Password: Required. The password of the company file.
• InitiateOAuth: Set this to GETANDREFRESH to let the driver handle access tokens.
• CallbackURL: The redirectURI of your Custom OAuth App.
• OAuthClientId: The client id of your Custom OAuth App.
• OAuthClientSecret: The client secret of your Custom OAuth App.

CData provides an embedded OAuth application that simplifies OAuth desktop authentication. See the Help documentation for information on other OAuth authentication methods (web, headless, etc.), creating custom OAuth applications, and reasons for doing so.

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

Load Reckon Accounts Hosted Data

Once you configure the connection, you can load Reckon Accounts Hosted 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" , "Accounts") \
	.load ()

Display Reckon Accounts Hosted Data

Check the loaded Reckon Accounts Hosted data by calling the display function.

Step 3: Checking the result

display (remote_table.select ("Name"))

👁 Displaying Reckon Accounts Hosted Data

Analyze Reckon Accounts Hosted 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 Reckon Accounts Hosted data for reporting, visualization, and analysis.

% sql

SELECT Name, Balance FROM SAMPLE_VIEW ORDER BY Balance DESC LIMIT 5

👁 Displaying Reckon Accounts Hosted Data

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