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