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

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

Install the CData JDBC Driver for Blackbaud FE NXT

Download the CData JDBC Driver for Blackbaud FE NXT installer, unzip the package, and run the JAR file to install the driver.

Start a Spark Shell and Connect to Blackbaud FE NXT Data

1. Open a terminal and start the Spark shell with the CData JDBC Driver for Blackbaud FE NXT JAR file as the jars parameter:

   $ spark-shell --jars /CData/CData JDBC Driver for Blackbaud FE NXT/lib/cdata.jdbc.financialedgenxt.jar
   

2. With the shell running, you can connect to Blackbaud FE NXT with a JDBC URL and use the SQL Context load() function to read a table.

   Blackbaud Financial Edge NXT uses the OAuth authentication standard. To authenticate using OAuth, create an app to obtain the OAuthClientId, OAuthClientSecret, and CallbackURL connection properties.

   See the Getting Started guide in the CData driver documentation for more information.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.financialedgenxt.jar
   

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

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

   Configure the connection to Blackbaud FE NXT, using the connection string generated above.

   scala> val financialedgenxt_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:financialedgenxt:SubscriptionKey=MySubscriptionKey;InitiateOAuth=GETANDREFRESH;").option("dbtable","Accounts").option("driver","cdata.jdbc.financialedgenxt.FinancialEdgeNXTDriver").load()
   

3. Once you connect and the data is loaded you will see the table schema displayed.

4. Register the Blackbaud FE NXT data as a temporary table:

   scala> financialedgenxt_df.registerTable("accounts")

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

   scala> financialedgenxt_df.sqlContext.sql("SELECT AccountId, AccountNumber FROM Accounts WHERE ModifiedBy = System").collect.foreach(println)

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

   👁 Data in Apache Spark (Salesforce is shown)
   

Using the CData JDBC Driver for Blackbaud FE NXT in Apache Spark, you are able to perform fast and complex analytics on Blackbaud FE NXT data, combining the power and utility of Spark with your data. Download a free, 30 day trial of any of the hundreds of CData JDBC Drivers and get started today.