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

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

Install the CData JDBC Driver for Hugging Face

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

Start a Spark Shell and Connect to Hugging Face Data

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

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

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

   HuggingFace Hub uses token-based authentication to enable access to its API. The API provides access to machine learning models, datasets, spaces, papers, and other resources on the HuggingFace Hub platform.

   Using API Key Authentication

   To authenticate to HuggingFace Hub, you will need to provide an API Key (Access Token). To obtain your access token:

   1. Log in to your HuggingFace account at https://huggingface.co
   2. Navigate to Settings > Access Tokens
   3. Click "New token" to create a new access token
   4. Select the appropriate permissions (read or write)
   5. Copy the token value

   After obtaining your access token, set the following connection properties:

   • AuthScheme: Set this to APIKey.
   • APIKey: Set this to your HuggingFace access token.

   Example connection string

   Profile=C:\profiles\HuggingFace.apip;ProfileSettings='APIKey=hf_xxxxxxxxxxxxxxxxxxxx';
   

   Built-in Connection String Designer

   For assistance in constructing the JDBC URL, use the connection string designer built into the Hugging Face 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.

   👁 Using the built-in connection string designer to generate a JDBC URL (Salesforce is shown.)
   

   Configure the connection to Hugging Face, using the connection string generated above.

   scala> val api_df = spark.sqlContext.read.format("jdbc").option("url", "jdbc:api:Profile=C:\profiles\HuggingFace.apip;ProfileSettings='APIKey=hf_xxxxxxxxxxxxxxxxxxxx';").option("dbtable","Collections").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 Hugging Face data as a temporary table:

   scala> api_df.registerTable("collections")

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

   scala> api_df.sqlContext.sql("SELECT , FROM Collections WHERE = ").collect.foreach(println)

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

   👁 Data in Apache Spark (Salesforce is shown)
   

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