Scaling Out with Dask¶

airflow.executors.dask_executor.DaskExecutor allows you to run Airflow tasks in a Dask Distributed cluster.

Dask clusters can be run on a single machine or on remote networks. For complete details, consult the Distributed documentation.

To create a cluster, first start a Scheduler:

# default settings for a local cluster
DASK_HOST=127.0.0.1
DASK_PORT=8786

dask-scheduler --host $DASK_HOST --port $DASK_PORT

Next start at least one Worker on any machine that can connect to the host:

dask-worker $DASK_HOST:$DASK_PORT

Edit your airflow.cfg to set your executor to airflow.executors.dask_executor.DaskExecutor and provide the Dask Scheduler address in the [dask] section.

Please note:

Each Dask worker must be able to import Airflow and any dependencies you require.
Dask does not support queues. If an Airflow task was created with a queue, a warning will be raised but the task will be submitted to the cluster.