Analyze Hugging Face Data in R via JDBC

Access Hugging Face data with pure R script and standard SQL on any machine where R and Java can be installed. You can use the CData JDBC Driver for Hugging Face and the RJDBC package to work with remote Hugging Face data in R. By using the CData Driver, you are leveraging a driver written for industry-proven standards to access your data in the popular, open-source R language. This article shows how to use the driver to execute SQL queries to Hugging Face and visualize Hugging Face data by calling standard R functions.

Install R

You can match the driver's performance gains from multi-threading and managed code by running the multithreaded Microsoft R Open or by running open R linked with the BLAS/LAPACK libraries. This article uses Microsoft R Open 3.2.3, which is preconfigured to install packages from the Jan. 1, 2016 snapshot of the CRAN repository. This snapshot ensures reproducibility.

Load the RJDBC Package

To use the driver, download the RJDBC package. After installing the RJDBC package, the following line loads the package:

library(RJDBC)

Connect to Hugging Face as a JDBC Data Source

You will need the following information to connect to Hugging Face as a JDBC data source:

• Driver Class: Set this to cdata.jdbc.api.APIDriver
• Classpath: Set this to the location of the driver JAR. By default this is the lib subfolder of the installation folder.

The DBI functions, such as dbConnect and dbSendQuery, provide a unified interface for writing data access code in R. Use the following line to initialize a DBI driver that can make JDBC requests to the CData JDBC Driver for Hugging Face:

driver <- JDBC(driverClass = "cdata.jdbc.api.APIDriver", classPath = "MyInstallationDir\lib\cdata.jdbc.api.jar", identifier.quote = "'") 

You can now use DBI functions to connect to Hugging Face and execute SQL queries. Initialize the JDBC connection with the dbConnect function.

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.

Below is a sample dbConnect call, including a typical JDBC connection string:

conn <- dbConnect(driver,"jdbc:api:Profile=C:\profiles\HuggingFace.apip;ProfileSettings='APIKey=hf_xxxxxxxxxxxxxxxxxxxx';")

Schema Discovery

The driver models Hugging Face APIs as relational tables, views, and stored procedures. Use the following line to retrieve the list of tables:

dbListTables(conn)

Execute SQL Queries

You can use the dbGetQuery function to execute any SQL query supported by the Hugging Face API:

collections <- dbGetQuery(conn,"SELECT ,  FROM Collections WHERE  = ''")

You can view the results in a data viewer window with the following command:

View(collections)

Plot Hugging Face Data

You can now analyze Hugging Face data with any of the data visualization packages available in the CRAN repository. You can create simple bar plots with the built-in bar plot function:

par(las=2,ps=10,mar=c(5,15,4,2))
barplot(collections$, main="Hugging Face Collections", names.arg = collections$, horiz=TRUE)