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- # Example command to start a cluster with this config:
- #
- # ray start --autoscaling-config=default.yaml --head --block
- #
- cluster_name: spark
- max_workers: 8
- provider:
- type: spark
- # This must be true since the nodes share the same ip!
- use_node_id_as_ip: True
- disable_node_updaters: True
- disable_launch_config_check: True
- available_node_types:
- ray.head.default:
- # You must set this manually to your "head" node resources!! The head
- # node is launched via `ray start` and hence the autoscaler cannot
- # configure its resources. The resources specified for its node type
- # must line up with what Ray detects/is configured with on start.
- resources:
- CPU: 8 # <-- set this to num CPUs used/detected in `ray start`
- GPU: 0 # <-- set this to num GPUs used/detected in `ray start`
- node_config: {}
- max_workers: 0
- ray.worker:
- resources:
- CPU: 1
- object_store_memory: 1000000000
- node_config: {}
- min_workers: 0
- max_workers: 4
- head_node_type: ray.head.default
- upscaling_speed: 1.0
- idle_timeout_minutes: 1.0
- #
- # !!! Configurations below are not supported in spark cluster mode
- #
- auth: {}
- docker: {}
- initialization_commands: []
- setup_commands: []
- head_setup_commands: []
- worker_setup_commands: []
- head_start_ray_commands: []
- worker_start_ray_commands: []
- file_mounts: {}
- cluster_synced_files: []
- file_mounts_sync_continuously: false
- rsync_exclude: []
- rsync_filter: []
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