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Add a notebook to demonstrate a real life use case for py iceberg

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Spark + Iceberg Quickstart Image

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

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

Usage

Start up the notebook server by running the following.

docker-compose up

The notebook server will then be available at http://localhost:8888

While the notebook server is running, you can use any of the following commands if you prefer to use spark-shell, spark-sql, or pyspark.

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.

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