---
type: concept
x-llmwiki:
  schemaVersion: "0.1"
  contentHash: 8243f31110aaa7e5cc0268b1d1fdca80618b40f2e2355aeec09059828a19cf95
  pageDirectory: concepts
  sources:
    - databricks-connect-for-r-databricks-on-aws.md
  confidence: 0.85
  provenanceState: inferred
  freshnessStatus: unverified
  aliases:
    - renv-package-integration-with-databricks-connect
    - RPIWDC
  citations:
    - file: databricks-connect-for-r-databricks-on-aws.md
title: renv Package Integration with Databricks Connect
description: The use of the renv R package for creating reproducible R project environments when working with Databricks Connect, ensuring consistent package dependencies across sessions.
tags:
  - r
  - package-management
  - reproducibility
timestamp: "2026-06-19T14:47:02.513Z"
---

# renv Package Integration with Databricks Connect

The **renv package** is used in the [Databricks Connect for R](/concepts/databricks-connect-for-r.md) workflow to manage project-level R dependencies. When a user creates a new RStudio Desktop project for Databricks Connect, they are prompted to select **“Use renv with this project”**, which initializes an isolated, reproducible R package library for that project. ^[databricks-connect-for-r-databricks-on-aws.md]

## Role in the Databricks Connect Setup

During the project creation step of the official tutorial (Step 2), RStudio offers the option to enable `renv`. If selected, `renv` installs any required updated version of itself and thereafter controls the installation of all R packages—such as `sparklyr`, `pysparklyr`, `reticulate`, and others—within a project-specific library. This ensures that the R environment used for Databricks Connect is self-contained and reproducible across different machines. ^[databricks-connect-for-r-databricks-on-aws.md]

The `renv` integration is part of the broader pattern of using [sparklyr](/concepts/sparklyr.md) and [pysparklyr](/concepts/pysparklyr.md) to connect an RStudio session to a Databricks cluster via Databricks Connect. The project’s `.Renviron` file stores sensitive credentials (workspace URL, personal access token, cluster ID), while `renv` manages the package dependencies declared by the user. ^[databricks-connect-for-r-databricks-on-aws.md]

## Support and Maintenance

The `renv` integration for Databricks Connect is **neither provided nor directly supported by Databricks**. It is a community-maintained capability documented by Posit (formerly RStudio). Users encountering issues should refer to the [Posit Community](https://community.rstudio.com/) or file issues in the [sparklyr GitHub repository](https://github.com/sparklyr/sparklyr). ^[databricks-connect-for-r-databricks-on-aws.md]

## Related Concepts

- [Databricks Connect](/concepts/databricks-connect.md) – The underlying remote connection framework.
- [sparklyr](/concepts/sparklyr.md) – R interface to Apache Spark used with Databricks Connect.
- [pysparklyr](/concepts/pysparklyr.md) – Bridge package for installing the Databricks Connect Python environment.
- reticulate – R package that enables R‑Python interoperability, required by Databricks Connect for R.
- RStudio Desktop – The most commonly used IDE for this workflow.

## Sources

- databricks-connect-for-r-databricks-on-aws.md

# Citations

1. [databricks-connect-for-r-databricks-on-aws.md](/references/databricks-connect-for-r-databricks-on-aws-29a91e1a.md)
