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

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

Install the CData JDBC Driver for Veeva Vault

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

Start a Spark Shell and Connect to Veeva Vault Data

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

   You are ready to connect after specifying the following connection properties:

   • Url: The host you see in the URL after you login to your account. For example: https://my-veeva-domain.veevavault.com
   • User: The username you use to login to your account.
   • Password: The password you use to login to your account.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.veevavault.jar

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

   Configure the connection to Veeva Vault, using the connection string generated above.

   scala> val veevavault_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:veevavault:User=myuser;Password=mypassword;Server=localhost;Database=mydatabase;").option("dbtable","NorthwindProducts").option("driver","cdata.jdbc.veevavault.VeevaVaultDriver").load()
3. Once you connect and the data is loaded you will see the table schema displayed.

4. Register the Veeva Vault data as a temporary table:

   scala> veevavault_df.registerTable("northwindproducts")

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

   scala> veevavault_df.sqlContext.sql("SELECT ProductId, ProductName FROM NorthwindProducts WHERE CategoryId = 5").collect.foreach(println)

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

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