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

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

Install the CData JDBC Driver for Tableau CRM Analytics

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

Start a Spark Shell and Connect to Tableau CRM Analytics Data

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

   Tableau CRM Analytics uses the OAuth 2 authentication standard. You will need to obtain the OAuthClientId and OAuthClientSecret by registering an app with Tableau CRM Analytics.

   See the Getting Started section of the 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 Tableau CRM Analytics JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

   java -jar cdata.jdbc.tableaucrm.jar

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

   Configure the connection to Tableau CRM Analytics, using the connection string generated above.

   scala> val tableaucrm_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:tableaucrm:OAuthClientId=MyConsumerKey;OAuthClientSecret=MyConsumerSecret;CallbackURL=http://localhost:portNumber;").option("dbtable","Dataset_Opportunity").option("driver","cdata.jdbc.tableaucrm.TableauCRMDriver").load()
3. Once you connect and the data is loaded you will see the table schema displayed.

4. Register the Tableau CRM Analytics data as a temporary table:

   scala> tableaucrm_df.registerTable("dataset_opportunity")

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

   scala> tableaucrm_df.sqlContext.sql("SELECT Name, CloseDate FROM Dataset_Opportunity WHERE StageName = Closed Won").collect.foreach(println)

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

Using the CData JDBC Driver for Tableau CRM Analytics in Apache Spark, you are able to perform fast and complex analytics on Tableau CRM Analytics 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.