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

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

Install the CData JDBC Driver for Clarifai

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

Start a Spark Shell and Connect to Clarifai Data

1. Open a terminal and start the Spark shell with the CData JDBC Driver for Clarifai JAR file as the jars parameter:

   
   $ spark-shell --jars /CData/CData JDBC Driver for Clarifai/lib/cdata.jdbc.api.jar
   

2. With the shell running, you can connect to Clarifai with a JDBC URL and use the SQL Context load() function to read a table.

   Start by setting the Profile connection property to the location of the Clarifai Profile on disk (e.g. C:\profiles\Clarifai.apip). Next, set the ProfileSettings connection property to the connection string for Clarifai (see below).

   Clarifai API Profile Settings

   Clarifai uses Personal Access Tokens (PATs) for authentication. To obtain a PAT:

   1. Log in to your Clarifai account at https://clarifai.com.
   2. Navigate to your profile settings and select Security.
   3. Click Create Personal Access Token.
   4. Select the required scopes and click Create Token.
   5. Copy the generated token (it will only be shown once).

   After obtaining your Personal Access Token, set the following connection properties:

   • AuthScheme: Set this to APIKey.

   Set the following in the ProfileSettings connection property:

   • APIKey: Set this to your Clarifai Personal Access Token (PAT).

   Built-in Connection String Designer

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

   
   java -jar cdata.jdbc.api.jar
   

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

   

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

   
   scala> val api_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:api:Profile=C:\profiles\Clarifai.apip;AuthScheme=APIKey;ProfileSettings='APIKey=your_personal_access_token';").option("dbtable","Apps").option("driver","cdata.jdbc.api.APIDriver").load()
   

3. Once you connect and the data is loaded you will see the table schema displayed.

4. Register the Clarifai data as a temporary table:

   scala> api_df.registerTable("apps")

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

   scala> api_df.sqlContext.sql("SELECT Id, Name FROM Apps WHERE UserId = my-user-id").collect.foreach(println)

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

   

Using the CData JDBC Driver for Clarifai in Apache Spark, you are able to perform fast and complex analytics on Clarifai data, combining the power and utility of Spark with your data. Download a free, 30 day trial of any of the hundreds of CData JDBC Drivers and get started today.