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

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

Install the CData JDBC Driver for TaxJar

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

Start a Spark Shell and Connect to TaxJar Data

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

   $ spark-shell --jars /CData/CData JDBC Driver for TaxJar/lib/cdata.jdbc.taxjar.jar
   

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

   To authenticate to the TaxJar API, first obtain the API Key from the TaxJar UI.

   NOTE: the API is available only for Professional and Premium TaxJar plans.

   If you already have a Professional or Premium plan you can find the API Key by logging in the TaxJar UI and navigating to Account -> TaxJar API. After obtaining the API Key, you can set it in the APIKey connection property.

   Additional Notes

   • By default, the CData connector will retrieve data of the last 3 months in cases where the entity support date range filtering. You can set StartDate to specify the minimum creation date of the data retrieved.
   • If the API Key has been created for a sandbox API account please set UseSandbox to true, but not all endpoints will work as expected. For more information, refer to the TaxJar developer documentation.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.taxjar.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 TaxJar, using the connection string generated above.

   scala> val taxjar_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:taxjar:APIKey=3bb04218ef8t80efdf1739abf7257144;").option("dbtable","Orders").option("driver","cdata.jdbc.taxjar.TaxJarDriver").load()
   

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

4. Register the TaxJar data as a temporary table:

   scala> taxjar_df.registerTable("orders")

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

   scala> taxjar_df.sqlContext.sql("SELECT TransactionID, UserID FROM Orders WHERE TransactionID = 123").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 TaxJar in Apache Spark, you are able to perform fast and complex analytics on TaxJar 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.