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

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

Install the CData JDBC Driver for Box

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

Start a Spark Shell and Connect to Box Data

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

   Box uses the OAuth standard to authenticate. To authenticate to Box, you will need to obtain the OAuthClientId, OAuthClientSecret, and CallbackURL by registering an app. See the "Getting Started" chapter of the help documentation for a guide to using OAuth.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.box.jar

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

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

   scala> val box_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:box:OAuthClientId=MyOAuthClientId;OAuthClientSecret=MyOAuthClientSecret;CallbackURL=http://localhost:33333;").option("dbtable","Files").option("driver","cdata.jdbc.box.BoxDriver").load()
3. Once you connect and the data is loaded you will see the table schema displayed.

4. Register the Box data as a temporary table:

   scala> box_df.registerTable("files")

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

   scala> box_df.sqlContext.sql("SELECT Name, Size FROM Files WHERE Id = 123").collect.foreach(println)

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

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