@Glime does the experimental map_task have to run on the same node or can the tasks be scheduled across nodes?

The experimental

map_task

in Flyte does not necessarily have to run on the same node; it can schedule tasks across different nodes. This is because

map_task

is designed to parallelize the execution of tasks over a collection of inputs, allowing each task to be executed independently. The primary purpose of

map_task

is to enable efficient parallel execution of homogeneous operations, which can be distributed across multiple nodes in a Flyte cluster. Moreover, the introduction of ArrayNode, as mentioned in the provided context, enhances the capabilities of

map_task

by extending mapping support beyond Kubernetes tasks to include tasks such as Python tasks, container tasks, and pod tasks. This implies that tasks can indeed be scheduled across different nodes, leveraging the distributed nature of Flyte's execution environment to achieve parallelism and scalability. It's important to note that while

map_task

facilitates the distribution of tasks across nodes, the specific scheduling and execution details depend on the underlying infrastructure and the configuration of the Flyte cluster. The Flyte scheduler is responsible for distributing tasks across available resources to optimize execution efficiency. --- This is an AI-generated response, take its recommendations with caution. Please help us improve the model accuracy by giving this response a thumbs up/thumbs down reaction. Sources https://github.com/flyteorg/flyte/blob/master/docs/user_guide/advanced_composition/map_tasks.md/ https://flyte.org/blog/flyte-1-9-arraynode-execution-tags-new-navigation-and-more/ 👍 button 👎 button