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Get the Report →How to connect and process Google Search Results from Azure Databricks
Use CData, Azure, and Databricks to perform data engineering and data science on live Google Search Results
Databricks is a cloud-based service that provides data processing capabilities through Apache Spark. When paired with the CData JDBC Driver, customers can use Databricks to perform data engineering and data science on live Google Search results. This article walks through hosting the CData JDBC Driver in Azure, as well as connecting to and processing live Google Search results in Databricks.
With built-in optimized data processing, the CData JDBC driver offers unmatched performance for interacting with live Google Search results. 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 client-side (often SQL functions and JOIN operations). Its built-in dynamic metadata querying allows you to work with and analyze Google Search results using native data types.
Install the CData JDBC Driver in Azure
To work with live Google Search results in Databricks, install the driver on your Azure cluster.
- Navigate to your Databricks administration screen and select the target cluster.
- On the Libraries tab, click "Install New."
- Select "Upload" as the Library Source and "Jar" as the Library Type.
- Upload the JDBC JAR file (cdata.jdbc.googlesearch.jar) from the installation location (typically C:\Program Files\CData[product_name]\lib).
Connect to Google Search from Databricks
With the JAR file installed, we are ready to work with live Google Search results in Databricks. Start by creating a new notebook in your workspace. Name the notebook, select Python as the language (though Scala is available as well), and choose the cluster where you installed the JDBC driver. When the notebook launches, we can configure the connection, query Google Search, and create a basic report.
Configure the Connection to Google Search
Connect to Google Search by referencing the class for the JDBC Driver and constructing a connection string to use in the JDBC URL. Additionally, you will need to set the RTK property in the JDBC URL (unless you are using a Beta driver). You can view the licensing file included in the installation for information on how to set this property.
driver = "cdata.jdbc.googlesearch.GoogleSearchDriver" url = "jdbc:googlesearch:RTK=5246...;CustomSearchId=def456;ApiKey=abc123;"
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.
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.
Load Google Search Results
Once the connection is configured, you can load Google Search results as a dataframe using the CData JDBC Driver and the connection information.
remote_table = spark.read.format ( "jdbc" ) \ .option ( "driver" , driver) \ .option ( "url" , url) \ .option ( "dbtable" , "VideoSearch") \ .load ()
Display Google Search Results
Check the loaded Google Search results by calling the display function.
display (remote_table.select ("Title"))
Analyze Google Search Results in Azure Databricks
If you want to process data with Databricks SparkSQL, register the loaded data as a Temp View.
remote_table.createOrReplaceTempView ( "SAMPLE_VIEW" )
The SparkSQL below retrieves the Google Search results for analysis.
% sql SELECT Title, ViewCount FROM VideoSearch WHERE SearchTerms = 'WayneTech'
The data from Google Search is only available in the target notebook. If you want to use it with other users, save it as a table.
remote_table.write.format ( "parquet" ) .saveAsTable ( "SAMPLE_TABLE" )
Download a free, 30-day trial of the CData JDBC Driver for Google Search and start working with your live Google Search results in Azure Databricks. Reach out to our Support Team if you have any questions.