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Work with YouTube Data in Apache Spark Using SQL

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

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

Install the CData JDBC Driver for YouTube

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

Start a Spark Shell and Connect to YouTube Data

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

    YouTube uses the OAuth authentication standard. To access Google APIs on behalf on individual users, you can use the embedded CData credentials or you can register your own OAuth app.

    OAuth also enables you to use a service account to connect on behalf of users in a Google Apps domain. To authenticate with a service account, you will need to register an application to obtain the OAuth JWT values.

    Built-in Connection String Designer

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

    java -jar cdata.jdbc.youtube.jar

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

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

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

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

    scala> youtube_df.sqlContext.sql("SELECT Title, ViewCount FROM Videos WHERE MyRating = like").collect.foreach(println)

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

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