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

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

Install the CData JDBC Driver for Suadeo

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

Start a Spark Shell and Connect to Suadeo Data

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

   $ spark-shell --jars /CData/CData JDBC Driver for Suadeo/lib/cdata.jdbc.suadeo.jar
   

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

   The driver uses the OAuth 2.0 Resource Owner Password Credentials (ROPC) grant to authenticate to Suadeo. Authentication occurs directly using your credentials; there is no browser-based authorization flow or refresh token.

   Set the following connection properties:

   • URL: The base URL of your Suadeo instance.
   • User: Your Suadeo username.
   • Password: Your Suadeo password.
   • AuthenticationName: The name identifier for the authentication configuration in your Suadeo instance. Different authentication names can be configured for different environments or use cases.

   When you connect, the driver sends your credentials to the Suadeo OAuth token endpoint, receives an access token, and uses it for all subsequent requests. A new access token is obtained automatically when needed during the session.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.suadeo.jar
   

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

   

   Configure the connection to Suadeo, using the connection string generated above.

   scala> val suadeo_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:suadeo:URL=https://mysuadeoinstance;User=username;Password=password;AuthenticationName=your_auth_name;").option("dbtable","Customers").option("driver","cdata.jdbc.suadeo.SuadeoDriver").load()
   

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

4. Register the Suadeo data as a temporary table:

   scala> suadeo_df.registerTable("customers")

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

   scala> suadeo_df.sqlContext.sql("SELECT Id, Name FROM Customers WHERE Status = Active").collect.foreach(println)

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

   

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