How to work with Google Search Results 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 Google Search, Spark can work with live Google Search results. This article describes how to connect to and query Google Search results from a Spark shell.

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

Install the CData JDBC Driver for Google Search

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

Start a Spark Shell and Connect to Google Search Results

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

   $ spark-shell --jars /CData/CData JDBC Driver for Google Search/lib/cdata.jdbc.googlesearch.jar
   

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

   To search with a Google custom search engine, you need to set the CustomSearchId and ApiKey connection properties.

   To obtain the CustomSearchId property, sign into Google Custom Search Engine and create a new search engine.

   To obtain the ApiKey property, you must enable the Custom Search API in the Google API Console.

   Built-in Connection String Designer

   For assistance in constructing the JDBC URL, use the connection string designer built into the Google Search JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

   java -jar cdata.jdbc.googlesearch.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 Google Search, using the connection string generated above.

   scala> val googlesearch_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:googlesearch:CustomSearchId=def456;ApiKey=abc123;").option("dbtable","VideoSearch").option("driver","cdata.jdbc.googlesearch.GoogleSearchDriver").load()
   

3. Once you connect and the data is loaded you will see the table schema displayed.

4. Register the Google Search results as a temporary table:

   scala> googlesearch_df.registerTable("videosearch")

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

   scala> googlesearch_df.sqlContext.sql("SELECT Title, ViewCount FROM VideoSearch WHERE SearchTerms = WayneTech").collect.foreach(println)

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

   👁 Results in Apache Spark (Salesforce is shown)
   

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