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

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

Install the CData JDBC Driver for PabblySubscriptions

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

Start a Spark Shell and Connect to PabblySubscriptions Data

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

   $ spark-shell --jars /CData/CData JDBC Driver for PabblySubscriptions/lib/cdata.jdbc.api.jar
   

2. With the shell running, you can connect to PabblySubscriptions 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 PabblySubscriptions Profile on disk (e.g. C:\profiles\PabblySubscriptions.apip). Next, set the ProfileSettings connection property to the connection string for PabblySubscriptions (see below).

   PabblySubscriptions API Profile Settings

   Navigate to Settings > API Settings > Regenerate API in your Pabbly Subscriptions account to obtain your API Key and Secret Key.

   Built-in Connection String Designer

   For assistance in constructing the JDBC URL, use the connection string designer built into the PabblySubscriptions 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.

   👁 Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)
   

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

   scala> val api_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:api:Profile=C:\profiles\PabblySubscriptions.apip;ProfileSettings='User=your_api_key;Password=your_secret_key';").option("dbtable","CustomerInvoices").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 PabblySubscriptions data as a temporary table:

   scala> api_df.registerTable("customerinvoices")

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

   scala> api_df.sqlContext.sql("SELECT CustomerId, Id FROM CustomerInvoices WHERE Status = paid").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 PabblySubscriptions in Apache Spark, you are able to perform fast and complex analytics on PabblySubscriptions 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.