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Add java yaml example (#10835)
* java example * Update python/ray/autoscaler/aws/example-java.yaml Co-authored-by: Eric Liang <ekhliang@gmail.com>
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# An unique identifier for the head node and workers of this cluster.
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cluster_name: java
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# The minimum number of workers nodes to launch in addition to the head
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# node. This number should be >= 0.
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min_workers: 1
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# The maximum number of workers nodes to launch in addition to the head
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# node. This takes precedence over min_workers.
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max_workers: 1
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# Cloud-provider specific configuration.
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provider:
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type: aws
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region: us-west-2
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# Availability zone(s), comma-separated, that nodes may be launched in.
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# Nodes are currently spread between zones by a round-robin approach,
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# however this implementation detail should not be relied upon.
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availability_zone: us-west-2a,us-west-2b
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# How Ray will authenticate with newly launched nodes.
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auth:
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ssh_user: ubuntu
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# Provider-specific config for the head node, e.g. instance type. By default
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# Ray will auto-configure unspecified fields such as SubnetId and KeyName.
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# For more documentation on available fields, see:
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# http://boto3.readthedocs.io/en/latest/reference/services/ec2.html#EC2.ServiceResource.create_instances
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head_node:
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InstanceType: m4.4xlarge
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ImageId: ami-06d51e91cea0dac8d # Ubuntu 18.04
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# You can provision additional disk space with a conf as follows
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BlockDeviceMappings:
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- DeviceName: /dev/sda1
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Ebs:
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VolumeSize: 20
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# Additional options in the boto docs.
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# Provider-specific config for worker nodes, e.g. instance type. By default
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# Ray will auto-configure unspecified fields such as SubnetId and KeyName.
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# For more documentation on available fields, see:
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# http://boto3.readthedocs.io/en/latest/reference/services/ec2.html#EC2.ServiceResource.create_instances
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worker_nodes:
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InstanceType: m4.4xlarge
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ImageId: ami-06d51e91cea0dac8d # Ubuntu 18.04
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# Run workers on spot by default. Comment this out to use on-demand.
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InstanceMarketOptions:
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MarketType: spot
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# Additional options can be found in the boto docs, e.g.
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# SpotOptions:
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# MaxPrice: MAX_HOURLY_PRICE
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# Files or directories to copy to the head and worker nodes. The format is a
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# dictionary from REMOTE_PATH: LOCAL_PATH, e.g.
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file_mounts: {
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# "/path1/on/remote/machine": "/path1/on/local/machine",
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# "/path2/on/remote/machine": "/path2/on/local/machine",
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}
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# List of commands that will be run before `setup_commands`. If docker is
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# enabled, these commands will run outside the container and before docker
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# is setup.
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initialization_commands:
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- sudo apt-get update
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- sudo apt-get install -y maven
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- git clone https://github.com/wuisawesome/ray-word-count.git || (pushd ray-word-count; git pull; popd)
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- pushd ray-word-count; mvn clean package; popd
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- cp -rv ray-word-count/files ./
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# List of shell commands to run to set up nodes.
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setup_commands:
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- sudo apt-get install -y python3 python3-pip
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- python3 -m pip install --upgrade pip
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- python3 -m pip install https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-0.9.0.dev0-cp36-cp36m-manylinux1_x86_64.whl
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# Custom commands that will be run on the head node after common setup.
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head_setup_commands:
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- python3 -m pip install boto3==1.4.8 # 1.4.8 adds InstanceMarketOptions
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# Custom commands that will be run on worker nodes after common setup.
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worker_setup_commands: []
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# Command to start ray on the head node. You don't need to change this.
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head_start_ray_commands:
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- ray stop
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- ulimit -n 65536; ray start --head --port=6379 --object-manager-port=8076 --autoscaling-config=~/ray_bootstrap_config.yaml --code-search-path=~/ray-word-count/target
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# Command to start ray on worker nodes. You don't need to change this.
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worker_start_ray_commands:
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- ray stop
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- ulimit -n 65536; ray start --address=$RAY_HEAD_IP:6379 --object-manager-port=8076 --code-search-path=ray-word-count/target
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# To run the program, run `ray exec java.yaml "java -jar ray-word-count/target/ray-word-count-1.0-SNAPSHOT-jar-with-dependencies.jar"`
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