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

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

Install the CData JDBC Driver for GitHub

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

Start a Spark Shell and Connect to GitHub Data

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

   GitHub uses the OAuth 2 authentication standard. To authenticate using OAuth, you will need to create an app to obtain the OAuthClientId, OAuthClientSecret, and CallbackURL connection properties. See the Getting Started chapter of the CData help documentation for an authentication guide.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.github.jar

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

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

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

4. Register the GitHub data as a temporary table:

   scala> github_df.registerTable("users")

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

   scala> github_df.sqlContext.sql("SELECT Name, Email FROM Users WHERE UserLogin = mojombo").collect.foreach(println)

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

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