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Work with Dropbox Data in Apache Spark Using SQL

Access and process Dropbox Data in Apache Spark using the CData JDBC Driver.

Apache Spark is a fast and general engine for large-scale data processing. When paired with the CData JDBC Driver for Dropbox, Spark can work with live Dropbox data. This article describes how to connect to and query Dropbox data from a Spark shell.

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

Install the CData JDBC Driver for Dropbox

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

Start a Spark Shell and Connect to Dropbox Data

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

    Dropbox uses the OAuth authentication standard. To authenticate using OAuth, you can use the embedded credentials or register an app with Dropbox.

    See the Getting Started guide in the CData driver documentation for more information.

    Built-in Connection String Designer

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

    java -jar cdata.jdbc.dropbox.jar

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

    scala> val dropbox_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:dropbox:").option("dbtable","Files").option("driver","cdata.jdbc.dropbox.DropboxDriver").load()
  3. Once you connect and the data is loaded you will see the table schema displayed.
  4. Register the Dropbox data as a temporary table:

    scala> dropbox_df.registerTable("files")
  5. Perform custom SQL queries against the Data using commands like the one below:

    scala> dropbox_df.sqlContext.sql("SELECT Id, Name FROM Files WHERE Id = 1").collect.foreach(println)

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

Using the CData JDBC Driver for Dropbox in Apache Spark, you are able to perform fast and complex analytics on Dropbox data, combining the power and utility of Spark with your data. Download a free, 30 day trial of any of the 170+ CData JDBC Drivers and get started today.