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

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

Install the CData JDBC Driver for Twitter

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

Start a Spark Shell and Connect to Twitter Data

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

   All tables require authentication. You can connect using your User and Password or OAuth. To authenticate using OAuth, you can use the embedded OAuthClientId, OAuthClientSecret, and CallbackURL or you can register an app to obtain your own.

   If you intend to communicate with Twitter only as the currently authenticated user, then you can obtain the OAuthAccessToken and OAuthAccessTokenSecret directly by registering an app.

   See the Getting Started chapter in 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 Twitter JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

   java -jar cdata.jdbc.twitter.jar

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

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

   scala> val twitter_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:twitter:").option("dbtable","Tweets").option("driver","cdata.jdbc.twitter.TwitterDriver").load()
3. Once you connect and the data is loaded you will see the table schema displayed.

4. Register the Twitter data as a temporary table:

   scala> twitter_df.registerTable("tweets")

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

   scala> twitter_df.sqlContext.sql("SELECT From_User_Name, Retweet_Count FROM Tweets WHERE From_User_Name = twitter").collect.foreach(println)

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

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