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

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

Install the CData JDBC Driver for Instagram

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

Start a Spark Shell and Connect to Instagram Data

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

   Instagram uses the OAuth 2 authentication standard. You will need to obtain the OAuthClientId, OAuthClientSecret, and CallbackURL by registering an app with Instagram. See the help documentation for a guide.

   Built-in Connection String Designer

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

   java -jar cdata.jdbc.instagram.jar

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

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

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

4. Register the Instagram data as a temporary table:

   scala> instagram_df.registerTable("media")

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

   scala> instagram_df.sqlContext.sql("SELECT Link, LikesCount FROM Media WHERE TagName = goldfish").collect.foreach(println)

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

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