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

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

Install the CData JDBC Driver for WooCommerce

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

Start a Spark Shell and Connect to WooCommerce Data

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

   $ spark-shell --jars /CData/CData JDBC Driver for WooCommerce/lib/cdata.jdbc.woocommerce.jar
   

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

   WooCommerce supports the following authentication methods: one-legged OAuth1.0 Authentication and standard OAuth2.0 Authentication.

   Connecting using one-legged OAuth 1.0 Authentication

   Specify the following properties (NOTE: the below credentials are generated from WooCommerce settings page and should not be confused with the credentials generated by using WordPress OAuth2.0 plugin):

   • ConsumerKey
   • ConsumerSecret

   Connecting using WordPress OAuth 2.0 Authentication

   After having configured the

   • OAuthClientId
   • OAuthClientSecret
   • CallbackURL
   • InitiateOAuth - Set this to either GETANDREFRESH or REFRESH

   In either case, set the Url property to the URL of the WooCommerce instance.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.woocommerce.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 WooCommerce, using the connection string generated above.

   scala> val woocommerce_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:woocommerce:Url=https://example.com/; ConsumerKey=ck_ec52c76185c088ecaa3145287c8acba55a6f59ad; ConsumerSecret=cs_9fde14bf57126156701a7563fc87575713c355e5;InitiateOAuth=GETANDREFRESH;").option("dbtable","Orders").option("driver","cdata.jdbc.woocommerce.WooCommerceDriver").load()
   

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

4. Register the WooCommerce data as a temporary table:

   scala> woocommerce_df.registerTable("orders")

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

   scala> woocommerce_df.sqlContext.sql("SELECT ParentId, Total FROM Orders WHERE ParentId = 3").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 WooCommerce in Apache Spark, you are able to perform fast and complex analytics on WooCommerce 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.