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

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

Install the CData JDBC Driver for Browserless

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

Start a Spark Shell and Connect to Browserless Data

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

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

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

   Browserless uses HTTP API token authentication. Your Browserless API token is sent as the token query parameter on every request. You can generate or view your token in the Browserless dashboard at https://account.browserless.io/.

   Using ApiKey Authentication

   After setting the following connection properties, you are ready to connect:

   • AuthScheme: Set this to APIKey.
   • APIKey: Set this to your Browserless API token.

   Example connection string:

   Profile=C:\profiles\Browserless.apip;AuthScheme=APIKey;ProfileSettings="ApiKey=your_api_token";
   

   Built-in Connection String Designer

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

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

   scala> api_df.registerTable("map")

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

   scala> api_df.sqlContext.sql("SELECT ,  FROM Map WHERE Url = https://www.example.com").collect.foreach(println)

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

   

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