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

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

Install the CData JDBC Driver for FreshBooks

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

Start a Spark Shell and Connect to FreshBooks Data

1. Open a terminal and start the Spark shell with the CData JDBC Driver for FreshBooks JAR file as the jars parameter: $ spark-shell --jars /CData/CData JDBC Driver for FreshBooks/lib/cdata.jdbc.freshbooks.jar
2. With the shell running, you can connect to FreshBooks with a JDBC URL and use the SQL Context load() function to read a table.

   To connect to FreshBooks, you can set the CompanyName and Token connection properties. Alternatively, you can use the OAuth authentication standard.

   OAuth can be used to enable other users to access their own company data. To authenticate using OAuth, you will need to obtain the OAuthClientId and OAuthClientSecret by registering an app. See the "Getting Started" chapter of the help documentation for a guide to using OAuth.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.freshbooks.jar

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

   Configure the connection to FreshBooks, using the connection string generated above.

   scala> val freshbooks_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:freshbooks:CompanyName=CData;Token=token;").option("dbtable","Clients").option("driver","cdata.jdbc.freshbooks.FreshBooksDriver").load()
3. Once you connect and the data is loaded you will see the table schema displayed.

4. Register the FreshBooks data as a temporary table:

   scala> freshbooks_df.registerTable("clients")

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

   scala> freshbooks_df.sqlContext.sql("SELECT Username, Credit FROM Clients WHERE Email = Captain Hook").collect.foreach(println)

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

Using the CData JDBC Driver for FreshBooks in Apache Spark, you are able to perform fast and complex analytics on FreshBooks data, combining the power and utility of Spark with your data. Download a free, 30 day trial of any of the 200+ CData JDBC Drivers and get started today.