Many Docker Apache Spark images are based on heavy-weight Debian images. This is based on Alpine Linux which is optimized for containers and light-weight.
A Spark container. Use it in a standalone cluster with the accompanying docker-compose.yml, or as a base for more complex recipes.
To run SparkPi, run the image with Docker:
docker run --rm -it -p 4040:4040 riyadparvez/spark bin/run-example SparkPi 10
To start spark-shell with your AWS credentials:
docker run --rm -it -e "AWS_ACCESS_KEY_ID=YOURKEY" -e "AWS_SECRET_ACCESS_KEY=YOURSECRET" -p 4040:4040 riyadparvez/spark bin/spark-shell
To do a thing with Pyspark
echo "import pyspark\nprint(pyspark.SparkContext().parallelize(range(0, 10)).count())" > count.py
docker run --rm -it -p 4040:4040 -v $(pwd)/count.py:/count.py riyadparvez/spark bin/pyspark /count.py
To create a simplistic standalone cluster with docker-compose:
docker-compose up
The SparkUI will be running at http://${YOUR_DOCKER_HOST}:8080 with one worker listed. To run pyspark, exec into a container:
docker exec -it dockerspark_master_1 /bin/bash
bin/pyspark
To run SparkPi, exec into a container:
docker exec -it dockerspark_master_1 /bin/bash
bin/run-example SparkPi 10
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