https://github.com/renardeinside/databricks-apps-shiny-with-r
Example of running Shiny for R on Databricks Apps
https://github.com/renardeinside/databricks-apps-shiny-with-r
databricks-apps r-language shiny
Last synced: 9 days ago
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Example of running Shiny for R on Databricks Apps
- Host: GitHub
- URL: https://github.com/renardeinside/databricks-apps-shiny-with-r
- Owner: renardeinside
- Created: 2026-05-08T16:24:16.000Z (about 1 month ago)
- Default Branch: main
- Last Pushed: 2026-05-08T16:42:56.000Z (about 1 month ago)
- Last Synced: 2026-05-08T18:39:33.982Z (about 1 month ago)
- Topics: databricks-apps, r-language, shiny
- Language: R
- Homepage:
- Size: 203 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 📊 Shiny for R on Databricks Apps
A sample [Shiny](https://shiny.posit.co/) app written in **R** that runs natively on [Databricks Apps](https://docs.databricks.com/en/apps/index.html) — deployed via DABs (Databricks Asset Bundles).
## 🤔 What's the approach?
Databricks Apps instances are shipped with **Python and `uv`**, but unfortunately doesn't have a preinstalled R runtime.
This project shows how to use a lightweight Python launcher that bootstraps an R environment at startup using [micromamba](https://mamba.readthedocs.io/en/latest/user_guide/micromamba.html), then hands off execution to a Shiny app.
## 🏗️ How it works
```
Databricks App Instance
=========================
uv run scripts/launcher.py
|-- 1. Downloads micromamba
|-- 2. Creates conda env from environment.yml
|-- 3. Installs R + packages
'-- 4. Starts Shiny app via Rscript
app/app.R --> serves on $DATABRICKS_APP_PORT
```
The Shiny app queries **Databricks SQL** using the forwarded user token (`HTTP_X_FORWARDED_ACCESS_TOKEN`), so each user sees data scoped to their own permissions.
## 📁 Project structure
```
├── app/
│ └── app.R # Shiny app (UI + server)
├── scripts/
│ └── launcher.py # Python bootstrap script
├── environment.yml # Conda env: R + packages
└── databricks.yml # DABs bundle definition
```
## ✅ Prerequisites
- [Databricks CLI](https://docs.databricks.com/en/dev-tools/cli/install.html) installed and authenticated
- A Databricks SQL Warehouse ID
- Access to a Databricks workspace
## 🚀 Deploy
**1. Validate the bundle**
```bash
databricks bundle validate
```
**2. Deploy to your workspace**
```bash
databricks bundle deploy -var="sql_warehouse_id="
```
**3. Launch the app**
```bash
databricks bundle run shiny-app-r
```
That's it — the app will be live on your workspace's Apps URL. 🎉
## 🔧 Configuration
The bundle is defined in `databricks.yml`. Key settings:
| Setting | Value |
| --------------- | --------------------------------------------------------- |
| App name | `shiny-app-r` |
| Start command | `uv run scripts/launcher.py` |
| User API scopes | `sql` |
| Variable | `sql_warehouse_id` — passed as `SQL_WAREHOUSE_ID` env var |
R dependencies live in `environment.yml` and are installed at container startup via micromamba.
## 🔑 Authentication
Databricks Apps handle auth automatically. The app reads the user's token from the `X-Forwarded-Access-Token` header injected by the Apps proxy — no secrets management needed.
## 💡 Adapting this for your own Shiny app
1. Replace `app/app.R` with your Shiny application
2. Add any new R packages to `environment.yml`
3. Update the SQL query or data source as needed
4. Re-deploy with `databricks bundle deploy`
## 📚 References
- [Databricks Apps](https://docs.databricks.com/en/apps/index.html)
- [micromamba](https://mamba.readthedocs.io/en/latest/user_guide/micromamba.html)
- [Shiny](https://shiny.posit.co/)
- [R](https://www.r-project.org/)
- [uv](https://docs.astral.sh/uv/)