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

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

Install the CData JDBC Driver for Shippo

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

Start a Spark Shell and Connect to Shippo Data

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

   Start by setting the Profile connection property to the location of the Shippo Profile on disk (e.g. C:\profiles\Shippo.apip). Next, set the ProfileSettings connection property to the connection string for Shippo (see below).

   Shippo API Profile Settings

   In order to authenticate to Shippo, you will need an API Key. You can find this API key under 'Settings' > 'API' > 'Generate Token'. After generating your key, set it to the APIKey in ProfileSettings connection property.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.api.jar

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

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

   scala> val api_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:api:Profile=C:\profiles\Shippo.apip;ProfileSettings='APIKey=my_api_key';").option("dbtable","Orders").option("driver","cdata.jdbc.api.APIDriver").load()
3. Once you connect and the data is loaded you will see the table schema displayed.

4. Register the Shippo data as a temporary table:

   scala> api_df.registerTable("orders")

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

   scala> api_df.sqlContext.sql("SELECT ObjectId , OrderStatus FROM Orders WHERE ShopApp = Shippo").collect.foreach(println)

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

Using the CData JDBC Driver for Shippo in Apache Spark, you are able to perform fast and complex analytics on Shippo 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.