From 9d0a9e73de7d8daf2f0056dd7f89786db240aa5d Mon Sep 17 00:00:00 2001 From: Alex Wu Date: Wed, 16 Sep 2020 14:35:10 -0700 Subject: [PATCH] Add java yaml example (#10835) * java example * Update python/ray/autoscaler/aws/example-java.yaml Co-authored-by: Eric Liang --- python/ray/autoscaler/aws/example-java.yaml | 81 +++++++++++++++++++++ 1 file changed, 81 insertions(+) create mode 100644 python/ray/autoscaler/aws/example-java.yaml diff --git a/python/ray/autoscaler/aws/example-java.yaml b/python/ray/autoscaler/aws/example-java.yaml new file mode 100644 index 000000000..a217c4009 --- /dev/null +++ b/python/ray/autoscaler/aws/example-java.yaml @@ -0,0 +1,81 @@ +# An unique identifier for the head node and workers of this cluster. +cluster_name: java +# The minimum number of workers nodes to launch in addition to the head +# node. This number should be >= 0. +min_workers: 1 +# The maximum number of workers nodes to launch in addition to the head +# node. This takes precedence over min_workers. +max_workers: 1 + +# Cloud-provider specific configuration. +provider: + type: aws + region: us-west-2 + # Availability zone(s), comma-separated, that nodes may be launched in. + # Nodes are currently spread between zones by a round-robin approach, + # however this implementation detail should not be relied upon. + availability_zone: us-west-2a,us-west-2b +# How Ray will authenticate with newly launched nodes. +auth: + ssh_user: ubuntu +# Provider-specific config for the head node, e.g. instance type. By default +# Ray will auto-configure unspecified fields such as SubnetId and KeyName. +# For more documentation on available fields, see: +# http://boto3.readthedocs.io/en/latest/reference/services/ec2.html#EC2.ServiceResource.create_instances +head_node: + InstanceType: m4.4xlarge + ImageId: ami-06d51e91cea0dac8d # Ubuntu 18.04 + # You can provision additional disk space with a conf as follows + BlockDeviceMappings: + - DeviceName: /dev/sda1 + Ebs: + VolumeSize: 20 + # Additional options in the boto docs. +# Provider-specific config for worker nodes, e.g. instance type. By default +# Ray will auto-configure unspecified fields such as SubnetId and KeyName. +# For more documentation on available fields, see: +# http://boto3.readthedocs.io/en/latest/reference/services/ec2.html#EC2.ServiceResource.create_instances +worker_nodes: + InstanceType: m4.4xlarge + ImageId: ami-06d51e91cea0dac8d # Ubuntu 18.04 + # Run workers on spot by default. Comment this out to use on-demand. + InstanceMarketOptions: + MarketType: spot + # Additional options can be found in the boto docs, e.g. + # SpotOptions: + # MaxPrice: MAX_HOURLY_PRICE +# Files or directories to copy to the head and worker nodes. The format is a +# dictionary from REMOTE_PATH: LOCAL_PATH, e.g. +file_mounts: { +# "/path1/on/remote/machine": "/path1/on/local/machine", +# "/path2/on/remote/machine": "/path2/on/local/machine", +} +# List of commands that will be run before `setup_commands`. If docker is +# enabled, these commands will run outside the container and before docker +# is setup. +initialization_commands: + - sudo apt-get update + - sudo apt-get install -y maven + - git clone https://github.com/wuisawesome/ray-word-count.git || (pushd ray-word-count; git pull; popd) + - pushd ray-word-count; mvn clean package; popd + - cp -rv ray-word-count/files ./ +# List of shell commands to run to set up nodes. +setup_commands: + - sudo apt-get install -y python3 python3-pip + - python3 -m pip install --upgrade pip + - 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 +# Custom commands that will be run on the head node after common setup. +head_setup_commands: + - python3 -m pip install boto3==1.4.8 # 1.4.8 adds InstanceMarketOptions +# Custom commands that will be run on worker nodes after common setup. +worker_setup_commands: [] +# Command to start ray on the head node. You don't need to change this. +head_start_ray_commands: + - ray stop + - 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 +# Command to start ray on worker nodes. You don't need to change this. +worker_start_ray_commands: + - ray stop + - ulimit -n 65536; ray start --address=$RAY_HEAD_IP:6379 --object-manager-port=8076 --code-search-path=ray-word-count/target + +# 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"`