Running Ballista on Raspberry Pi

The Raspberry Pi single-board computer provides a fun and relatively inexpensive way to get started with distributed computing.

These instructions have been tested using an Ubuntu Linux desktop as the host, and a Raspberry Pi 4 Model B with 4 GB RAM as the target.

Preparing the Raspberry Pi

We recommend installing the 64-bit version of Ubuntu for Raspberry Pi.

The Rust implementation of Arrow does not work correctly on 32-bit ARM architectures (issue).

Cross Compiling DataFusion for the Raspberry Pi

We do not yet publish official Docker images as part of the release process, although we do plan to do this in the future (issue #228).

Although it is technically possible to build DataFusion directly on a Raspberry Pi, it really isn’t very practical. It is much faster to use cross to cross-compile from a more powerful desktop computer.

Docker must be installed and the Docker daemon must be running before cross-compiling with cross. See the cross project for more detailed instructions.

Run the following command to install cross.

cargo install cross

From the root of the DataFusion project, run the following command to cross-compile for ARM 64 architecture.

cross build --release --target aarch64-unknown-linux-gnu

It is even possible to cross-test from your desktop computer:

cross test --target aarch64-unknown-linux-gnu

Deploying the binaries to Raspberry Pi

You should now be able to copy the executable to the Raspberry Pi using scp on Linux. You will need to change the IP address in these commands to be the IP address for your Raspberry Pi. The easiest way to find this is to connect a keyboard and monitor to the Pi and run ifconfig.

scp ./target/aarch64-unknown-linux-gnu/release/ballista-scheduler ubuntu@
scp ./target/aarch64-unknown-linux-gnu/release/ballista-executor ubuntu@

Finally, ssh into the Pi and make the binaries executable:

ssh ubuntu@
chmod +x ballista-scheduler ballista-executor

It is now possible to run the Ballista scheduler and executor natively on the Pi.


Using Docker’s buildx cross-platform functionality, we can also build a docker image targeting ARM64 from any desktop environment. This will require write access to a Docker repository on Docker Hub because the resulting Docker image will be pushed directly to the repo.

DOCKER_REPO=myrepo ./dev/

On the Raspberry Pi:

docker pull myrepo/ballista-arm64

Run a scheduler:

docker run -it myrepo/ballista-arm64 /ballista-scheduler

Run an executor:

docker run -it myrepo/ballista-arm64 /ballista-executor

Run the benchmarks:

docker run -it myrepo/ballista-arm64 \
  /tpch benchmark datafusion --query=1 --path=/path/to/data --format=parquet \
  --concurrency=24 --iterations=1 --debug --host=ballista-scheduler --bind-port=50050

Note that it will be necessary to mount appropriate volumes into the containers and also configure networking so that the Docker containers can communicate with each other. This can be achieved using Docker compose or Kubernetes.


With Docker images built using the instructions above, it is now possible to deploy Ballista to a Kubernetes cluster running on one of more Raspberry Pi computers. Refer to the instructions in the Kubernetes chapter for more information, and remember to change the Docker image name to myrepo/ballista-arm64.