chore: import upstream snapshot with attribution

python/ray/autoscaler/aws/example-java.yaml

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+# 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 will be launched in the first listed availability zone and will
+    # be tried in the subsequent availability zones if launching fails.
+    availability_zone: us-west-2a,us-west-2b
+# How Ray will authenticate with newly launched nodes.
+auth:
+    ssh_user: ubuntu
+
+
+# Tell the autoscaler the allowed node types and the resources they provide.
+# The key is the name of the node type, which is just for debugging purposes.
+# The node config specifies the launch config and physical instance type.
+available_node_types:
+    ray.head.default:
+      node_config:
+        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.
+    ray.worker.default:
+      node_config:
+        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
+# 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-cp37-cp37m-manylinux2014_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
+# 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
+
+# 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 -Dray.job.code-search-path=ray-word-count/target"`