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

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

Install the CData JDBC Driver for Drift

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

Start a Spark Shell and Connect to Drift Data

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

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

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

   Start by setting the Profile connection property to the location of the Drift Profile on disk (e.g. C:\profiles\Drift.apip). Next, set the ProfileSettings connection property to the connection string for Drift (see below).

   Drift API Profile Settings

   Drift uses OAuth-based authentication.

   You must first register an application here: https://dev.drift.com. Your app will be assigned a client ID and a client secret. Set these in your connection string via the OAuthClientId and OAuthClientSecret properties. More information on setting up an OAuth application can be found at https://devdocs.drift.com/docs/.

   After setting the following options in the ProfileSettings connection property, you are ready to connect:

   • AuthScheme: Set this to OAuth.
   • OAuthClientId: Set this to the Client Id that is specified in your app settings.
   • OAuthClientSecret: Set this to Client Secret that is specified in your app settings.
   • CallbackURL: Set this to the Redirect URI you specified in your app settings.
   • InitiateOAuth: Set this to GETANDREFRESH. You can use InitiateOAuth to manage the process to obtain the OAuthAccessToken.

   Built-in Connection String Designer

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

   scala> val api_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:api:Profile=C:\profiles\Drift.apip;Authscheme=OAuth;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;CallbackUrl=your_callback_url;").option("dbtable","Contacts").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 Drift data as a temporary table:

   scala> api_df.registerTable("contacts")

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

   scala> api_df.sqlContext.sql("SELECT Id, DisplayName FROM Contacts WHERE LastName = Stark").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 Drift in Apache Spark, you are able to perform fast and complex analytics on Drift 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.