Alejandro_DR
07/02/2024, 1:05 PMMarvin
07/02/2024, 1:05 PMKubeCluster
by overriding the necessary Kubernetes configuration. This typically involves customizing the pod_template
within your Dask setup.
Here's an example of how you might achieve this:
python
from dask_kubernetes import KubeCluster, make_pod_spec
from prefect import flow, task
from prefect_dask import DaskTaskRunner
@task
def dummy_task():
return "Task is running"
# Define a pod spec with a custom name
pod_template = make_pod_spec(image='your-docker-image', labels={"custom_label": "label_value"})
pod_template.metadata.name = 'custom-pod-name' # Set your custom pod name here
# Define the Dask Task Runner with the custom pod spec
task_runner = DaskTaskRunner(
cluster_class=KubeCluster,
cluster_kwargs={"pod_template": pod_template},
adapt_kwargs={"minimum": 2, "maximum": 4} # Adjust adapt_kwargs as per your requirement
)
@flow(task_runner=task_runner)
def demo_flow():
dummy_task()
if __name__ == "__main__":
demo_flow()
Adjust the pod_template
attributes to fit your requirements. This example sets a static pod name, but for dynamic naming, you could generate the name based on runtime parameters within your flow or tasks.
For more detailed integration into your specific use case, refer to the Prefect and Dask documentation and Dask Kubernetes documentation.
If you have further requirements or encounter specific issues, please provide additional context so we can assist you better.