Process & Analyze TaxJar 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 TaxJar data. This article walks through hosting the CData JDBC Driver in AWS, as well as connecting to and processing live TaxJar data in Databricks.

With built-in optimized data processing, the CData JDBC Driver offers unmatched performance for interacting with live TaxJar data. 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 client-side (often SQL functions and JOIN operations). Its built-in dynamic metadata querying allows you to work with and analyze TaxJar data using native data types.

Install the CData JDBC Driver in Databricks

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

Access TaxJar Data in your Notebook: Python

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

Configure the Connection to TaxJar

Connect to TaxJar by referencing the JDBC Driver class and constructing a connection string to use in the JDBC URL. Additionally, you will need to set the RTK 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.taxjar.TaxJarDriver"
url = "jdbc:taxjar:RTK=5246...;APIKey=3bb04218ef8t80efdf1739abf7257144;"

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.

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

To authenticate to the TaxJar API, you will need to 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.

Load TaxJar Data

Once you configure the connection, you can load TaxJar 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" , "Orders") \
	.load ()

Display TaxJar Data

Check the loaded TaxJar data by calling the display function.

Step 3: Checking the result

display (remote_table.select ("TransactionID"))

Analyze TaxJar 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 TaxJar data for reporting, visualization, and analysis.

% sql

SELECT TransactionID, UserID FROM SAMPLE_VIEW ORDER BY UserID DESC LIMIT 5

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