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

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

Install the CData JDBC Driver for Google Sheets

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

Start a Spark Shell and Connect to Google Sheets Data

1. Open a terminal and start the Spark shell with the CData JDBC Driver for Google Sheets JAR file as the jars parameter: $ spark-shell --jars /CData/CData JDBC Driver for Google Sheets/lib/cdata.jdbc.googlesheets.jar
2. With the shell running, you can connect to Google Sheets with a JDBC URL and use the SQL Context load() function to read a table.

   You can connect to a spreadsheet by providing authentication to Google and then setting the Spreadsheet connection property to the name or feed link of the spreadsheet. If you want to view a list of information about the spreadsheets in your Google Drive, execute a query to the Spreadsheets view after you authenticate.

   ClientLogin (username/password authentication) has been officially deprecated since April 20, 2012 and is now no longer available. Instead, use the OAuth 2.0 authentication standard. To access Google APIs on behalf on individual users, you can use the embedded credentials or you can register your own OAuth app.

   OAuth also enables you to use a service account to connect on behalf of users in a Google Apps domain. To authenticate with a service account, you will need to register an application to obtain the OAuth JWT values.

   See the Getting Started chapter in the help documentation to connect to Google Sheets from different types of accounts: Google accounts, Google Apps accounts, and accounts using two-step verification.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.googlesheets.jar

   Fill in the connection properties and copy the connection string to the clipboard.

   Configure the connection to Google Sheets, using the connection string generated above.

   scala> val googlesheets_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:googlesheets:Spreadsheet=MySheet;").option("dbtable","Orders").option("driver","cdata.jdbc.googlesheets.GoogleSheetsDriver").load()
3. Once you connect and the data is loaded you will see the table schema displayed.

4. Register the Google Sheets data as a temporary table:

   scala> googlesheets_df.registerTable("orders")

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

   scala> googlesheets_df.sqlContext.sql("SELECT Shipcountry, OrderPrice FROM Orders WHERE ShipCity = Madrid").collect.foreach(println)

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

Using the CData JDBC Driver for Google Sheets in Apache Spark, you are able to perform fast and complex analytics on Google Sheets data, combining the power and utility of Spark with your data. Download a free, 30 day trial of any of the 200+ CData JDBC Drivers and get started today.