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

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

Install the CData JDBC Driver for Browse AI

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

Start a Spark Shell and Connect to Browse AI Data

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

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

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

   BrowseAI API Profile Settings

   BrowseAI is a web scraping and automation platform that allows you to train robots to extract and monitor data from websites. Authentication is performed using an API key that is sent as a Bearer token in the Authorization header.

   The BrowseAI API key has the format {userId}:{apiKey}, where both parts are UUIDs separated by a colon. This full string is provided as a single value in the BrowseAI dashboard.

   To obtain your API key:

   1. Log in to your BrowseAI account at https://app.browse.ai
   2. Navigate to Settings in the dashboard
   3. Locate the API section
   4. Copy the full API key string displayed (format: userId:apiKey)

   After obtaining your API key, set the following connection properties:

   • AuthScheme: Set this to APIKey.

   Set the following in the ProfileSettings connection property:

   • APIKey: Set this to your BrowseAI API key (format: userId:apiKey).

   Built-in Connection String Designer

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

   
   scala> val api_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:api:Profile=C:\profiles\BrowseAI.apip;AuthScheme=APIKey;ProfileSettings='APIKey=your_user_id:your_api_key';").option("dbtable","RobotTasks").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 Browse AI data as a temporary table:

   scala> api_df.registerTable("robottasks")

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

   scala> api_df.sqlContext.sql("SELECT Id, Status FROM RobotTasks WHERE RobotId = your-robot-id").collect.foreach(println)

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

   

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