Parallelize R code using user-defined functions in sparklyr

If you’re an Apache Spark user, you benefit from its speed and scalability for big data processing.

However, you might still want to leverage R’s extensive ecosystem of packages and intuitive syntax. One effective way to do this is by writing user-defined functions (UDFs) with sparklyr.

UDFs enable you to execute R functions within Spark, harnessing Spark’s processing power and combining the strengths of both tools.

In this tutorial, you'll learn how to:
- Open Posit Workbench as a Databricks user
- Start a Databricks cluster within Posit Workbench
- Connect to a cluster within Posit Workbench
- View Databricks data in RStudio
- Create a prediction function
- Create a user-defined function with sparklyr

✨ Read our most recent blog that covers parallelizing R code using user-defined functions (UDFs) in sparklyr: https://posit.co/blog/databricks-udfs/

💡 Learn more about our Databricks partnership: https://posit.co/solutions/databricks/

📺 Watch other tutorials on using Databricks and RStudio:    • Using Databricks and RStudio