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Work with DigitalOcean Data in Apache Spark Using SQL

Access and process DigitalOcean 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 DigitalOcean, Spark can work with live DigitalOcean data. This article describes how to connect to and query DigitalOcean data from a Spark shell.

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

Install the CData JDBC Driver for DigitalOcean

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

Start a Spark Shell and Connect to DigitalOcean Data

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

    DigitalOcean uses OAuth 2.0 authentication. To authenticate using OAuth, you can use the embedded credentials or register an app with DigitalOcean.

    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 DigitalOcean JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

    java -jar cdata.jdbc.digitalocean.jar

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

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

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

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

    scala> digitalocean_df.sqlContext.sql("SELECT Id, Name FROM Droplets 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 DigitalOcean in Apache Spark, you are able to perform fast and complex analytics on DigitalOcean 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.