Nimtable Quickstart Image

Nimtable helps you easily manage and explore Apache Iceberg catalogs. With a web-based platform designed for clarity and simplicity, Nimtable makes it easy to browse tables, run queries, analyze file distributions, and optimize storage layouts.

This is a docker compose environment to quickly get up and running with a Spark environment and a local REST catalog, MinIO as a storage backend, and Nimtable for Iceberg lakehouse management.

note: If you don't have docker installed, you can head over to the Get Docker page for installation instructions.

Usage

docker-compose up

Wait for all services to start.

The services available are:

• Jupyter Notebooks: http://localhost:8888 (create and manage data)
• Nimtable Web Interface: http://localhost:3000 (explore and analyze data)
• MinIO Console: http://localhost:9001 (view storage)

The environment comes with a collection of pre-built Jupyter notebooks that demonstrate various Iceberg features and capabilities. Use these notebooks to learn Iceberg concepts hands-on, while using Nimtable to visualize and monitor the tables you create.

How to Use the Notebooks

1. Open both interfaces: Access Jupyter at http://localhost:8888 and Nimtable at http://localhost:3000
2. Start learning: Browse the available notebooks in Jupyter and choose one to start with.
3. Run and observe: Execute notebook cells (Shift+Enter) and immediately check Nimtable to see table changes
4. Compare states: After each major operation in the notebook, refresh Nimtable to observe:
   • New tables being created
   • Schema evolution
   • Snapshot history
   • File organization
5. Experiment: Modify notebook code and see the real-time impact in Nimtable

💡 Pro Tip: Keep both Jupyter and Nimtable open in separate browser tabs for the best learning experience. As you create, modify, and optimize tables in the notebooks, you can immediately see the results in Nimtable's intuitive interface.

Alternative Access Methods

While the notebook server is running, you can also use these command-line tools:

docker exec -it spark-iceberg spark-shell

docker exec -it spark-iceberg spark-sql

docker exec -it spark-iceberg pyspark

To stop everything, just run docker-compose down.

Troubleshooting & Maintenance

Refreshing Docker Image

The prebuilt spark image is uploaded to Dockerhub. Out of convenience, the image tag defaults to latest.

If you have an older version of the image, you might need to remove it to upgrade.

docker image rm tabulario/spark-iceberg && docker-compose pull

Building the Docker Image locally

If you want to make changes to the local files, and test them out, you can build the image locally and use that instead:

docker image rm tabulario/spark-iceberg && docker-compose build

Use Dockerfile In This Repo

To directly use the Dockerfile in this repo (as opposed to pulling the pre-build tabulario/spark-iceberg image), you can use docker-compose build.

Deploying Changes

To deploy changes to the hosted docker image tabulario/spark-iceberg, run the following. (Requires access to the tabulario docker hub account)

cd spark
docker buildx build -t tabulario/spark-iceberg --platform=linux/amd64,linux/arm64 . --push

---

For more information on getting started with using Iceberg, checkout the Quickstart guide in the official docs.

The repository for the docker image is located on dockerhub.