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

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

Install the CData JDBC Driver for Pushbullet

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

Start a Spark Shell and Connect to Pushbullet Data

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

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

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

   Using API Key Authentication

   Pushbullet uses token-based authentication (Access Token). To obtain an Access Token:

   1. Log in to your Pushbullet account at https://www.pushbullet.com
   2. Navigate to Settings > Account
   3. Click "Create Access Token"
   4. Copy the generated token

   After obtaining your Access Token, set the following connection properties:

   • AuthScheme: Set this to APIKey.
   Set the following in the ProfileSettings connection property:
   • APIKey: Set this to your Pushbullet Access Token.

   Example Connection String

   Profile=C:\profiles\Pushbullet.apip;ProfileSettings='APIKey=your_access_token;';AuthScheme=APIKey;
   

   Connecting to Pushbullet

   Once the authentication is configured, you can connect to Pushbullet and query data from any of the available tables such as Users, Pushes, Devices, Chats, Subscriptions, and Channels.

   Built-in Connection String Designer

   For assistance in constructing the JDBC URL, use the connection string designer built into the Pushbullet 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 Pushbullet, using the connection string generated above.

   scala> val api_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:api:Profile=C:\profiles\Pushbullet.apip;ProfileSettings='APIKey=your_access_token;';AuthScheme=APIKey;").option("dbtable","Users").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 Pushbullet data as a temporary table:

   scala> api_df.registerTable("users")

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

   scala> api_df.sqlContext.sql("SELECT ,  FROM Users WHERE  = ").collect.foreach(println)

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

   

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