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

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

Install the CData JDBC Driver for Bitly

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

Start a Spark Shell and Connect to Bitly Data

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

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

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

   Bitly API Profile Settings

   Log into your Bitly account, go to Settings > Developer Settings, and generate a Generic Access Token.

   Built-in Connection String Designer

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

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

   scala> api_df.registerTable("bitlinkcities")

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

   scala> api_df.sqlContext.sql("SELECT City, Clicks FROM BitlinkCities WHERE Country = United States").collect.foreach(println)

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

   

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