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

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

Install the CData JDBC Driver for Google Ad Manager

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

Start a Spark Shell and Connect to Google Ad Manager Data

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

   $ spark-shell --jars /CData/CData JDBC Driver for Google Ad Manager/lib/cdata.jdbc.googleadsmanager.jar
   

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

   Google Ads Manager uses the OAuth authentication standard. You can authorize the data provider to access Google Ads Manager as an individual user or with a service account that you create in the Google APIs Console. See the Getting Started section in the data provider help documentation for an authentication guide.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.googleadsmanager.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 Ad Manager, using the connection string generated above.

   scala> val googleadsmanager_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:googleadsmanager:InitiateOAuth=GETANDREFRESH;").option("dbtable","Orders").option("driver","cdata.jdbc.googleadsmanager.GoogleAdsManagerDriver").load()
   

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

4. Register the Google Ad Manager data as a temporary table:

   scala> googleadsmanager_df.registerTable("orders")

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

   scala> googleadsmanager_df.sqlContext.sql("SELECT Id, Name FROM Orders WHERE Id = 2112976978").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 Google Ad Manager in Apache Spark, you are able to perform fast and complex analytics on Google Ad Manager 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.