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

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

Install the CData JDBC Driver for ScrapingBee

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

Start a Spark Shell and Connect to ScrapingBee Data

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

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

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

   Using API Key Authentication

   ScrapingBee uses API key authentication. To obtain an API key:

   1. Sign in to your ScrapingBee account at https://app.scrapingbee.com
   2. Navigate to the Dashboard and locate your API key in the top section.
   3. Copy the API key for use in the connection string.

   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 ScrapingBee API key.

   Example Connection String

   Profile=C:\profiles\ScrapingBee.apip;AuthScheme=APIKey;ProfileSettings="APIKey=your_api_key";
   

   Connecting to ScrapingBee

   Once the authentication is configured, you can connect to ScrapingBee and query data from any of the available tables. All tables require at least one input parameter (such as a search query or product ID) to retrieve data.

   Built-in Connection String Designer

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

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

   scala> api_df.registerTable("googlesearchresults")

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

   scala> api_df.sqlContext.sql("SELECT , FROM GoogleSearchResults WHERE SearchQuery = cdata drivers").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 ScrapingBee in Apache Spark, you are able to perform fast and complex analytics on ScrapingBee 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.