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

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

Install the CData JDBC Driver for DocuSign

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

Start a Spark Shell and Connect to DocuSign Data

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

   $ spark-shell --jars /CData/CData JDBC Driver for DocuSign/lib/cdata.jdbc.docusign.jar
   

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

   To connect to DocuSign, set the following connection properties:

   • UseSandbox: indicates whether current user account is sandbox or not (FALSE by default)
   • AccountId (optional): set it in the connection string if you have access to multiple Account Ids

   Authenticating to DocuSign

   DocuSign uses the OAuth authentication standard. To authenticate using OAuth, create an app to obtain the OAuthClientId, OAuthClientSecret, and CallbackURL connection properties. See the Help documentation more information.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.docusign.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 DocuSign, using the connection string generated above.

   scala> val docusign_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:docusign:OAuthClientId=MyClientId; OAuthClientSecret=MyClientSecret; 
   CallbackURL=http://localhost:33333;
   ").option("dbtable","Documents").option("driver","cdata.jdbc.docusign.DocuSignDriver").load()
   

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

4. Register the DocuSign data as a temporary table:

   scala> docusign_df.registerTable("documents")

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

   scala> docusign_df.sqlContext.sql("SELECT DocumentId, DocumentName FROM Documents WHERE DocumentName = TPSReport").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 DocuSign in Apache Spark, you are able to perform fast and complex analytics on DocuSign 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.