SubmitRayJob-阿里云帮助中心

Submits a Ray job.

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RAM authorization

The table below describes the authorization required to call this API. You can define it in a Resource Access Management (RAM) policy. The table's columns are detailed below:

Action: The actions can be used in the Action element of RAM permission policy statements to grant permissions to perform the operation.
API: The API that you can call to perform the action.
Access level: The predefined level of access granted for each API. Valid values: create, list, get, update, and delete.
Resource type: The type of the resource that supports authorization to perform the action. It indicates if the action supports resource-level permission. The specified resource must be compatible with the action. Otherwise, the policy will be ineffective.
- For APIs with resource-level permissions, required resource types are marked with an asterisk (*). Specify the corresponding Alibaba Cloud Resource Name (ARN) in the Resource element of the policy.
- For APIs without resource-level permissions, it is shown as All Resources. Use an asterisk (*) in the Resource element of the policy.
Condition key: The condition keys defined by the service. The key allows for granular control, applying to either actions alone or actions associated with specific resources. In addition to service-specific condition keys, Alibaba Cloud provides a set of common condition keys applicable across all RAM-supported services.
Dependent action: The dependent actions required to run the action. To complete the action, the RAM user or the RAM role must have the permissions to perform all dependent actions.

Action

Access level

Resource type

Condition key

Dependent action

emr-serverless-spark:SubmitRayJob

create

*All Resource

*

None

Request syntax

POST /api/v1/workspaces/{workspaceId}/rayJob HTTP/1.1

Path Parameters

Parameter	Type	Required	Description	Example
workspaceId	string	No	The workspace ID.	w-d2d82aa09155

Request parameters

Parameter	Type	Required	Description	Example
body	object	No	The request struct.
entrypoint	string	No	The startup command.	python -c "print('hello ray job')"
name	string	No	The job name.	my-job
displayReleaseVersion	string	No	The Ray DPI engine version number.	err-1.2.0 (Ray 2.55.1, Python 3.12)
tags	array<object>	No	The tags.
	object	No
key	string	No	The key.	jobname
value	string	No	The value.	test
networkServiceName	string	No	The network connectivity name.	vpc
runtimeEnvJson	string	No	The Ray runtime environment JSON string.	{"pip":["requests==2.26.0","pendulum==2.1.2"],"env_vars":{"KEY":"VALUE"}}
workingDir	string	No	The URL of the job code working directory.	oss://mybucket/rayjob.zip
metadataJson	string	No	The job metadata JSON string.	{"resourceName": "test"}
submissionMode	string	No	The job submission mode.	HTTPMode
entrypointNumCpus	string	No	The number of CPUs requested by the entrypoint task.	1
entrypointNumGpus	string	No	The number of GPUs requested by the entrypoint task.	0
entrypointMemory	string	No	The memory size requested by the entrypoint task.	4Gi
entrypointResources	string	No	The custom resource request JSON string for the entrypoint task.	{"fpu": 1}
shutdownAfterJobFinishes	boolean	No	Specifies whether to automatically destroy the temporary cluster after the job finishes. Default value: true.	true
ttlSecondsAfterFinished	integer	No	The number of seconds to wait before destroying the cluster. This parameter takes effect only when shutdownAfterJobFinishes is set to true.	60
activeDeadlineSeconds	integer	No	The timeout period of the job, which includes the cluster creation time and job runtime. The job is canceled if this period is exceeded.	3600
volumeIds	array	No	The list of mounted volume IDs.
	string	No	The managed file ID.	vol-12345678
headSpec	object	No	The Ray cluster head node parameters.
queueName	string	No	The queue name.	root_queue
cpu	string	No	The number of CPU cores.	2
memory	string	No	The memory size. Unit: GiB.	8Gi
enableAutoScaling	boolean	No	Specifies whether to enable automatic scaling for workers.	true
idleTimeoutSeconds	integer	No	The worker idle timeout period after automatic scaling is enabled.	60
gpuSpec	string	No	The GPU instance type.	ecs.gn6i-c4g1.xlarge
displayReleaseVersion	string	No	The Ray DPI engine version.	err-1.3.0 (Ray 2.55.1, Python 3.12)
workerSpec	array<object>	No	The parameters of the worker nodes in the Ray cluster.
	object	No	The worker node struct.
groupName	string	No	The worker group name.	WorkerGroup1
workerType	string	No	The worker type.	CPU
replica	integer	No	The number of workers.	2
queueName	string	No	The queue name.	root_queue
cpu	string	No	The number of CPU cores.	4
memory	string	No	The memory size. Unit: GiB.	16Gi
minReplica	integer	No	The minimum number of workers after automatic scaling is enabled.	1
maxReplica	integer	No	The maximum number of workers after automatic scaling is enabled.	10
gpuSpec	string	No	The GPU instance type.	ecs.gn6i-c4g1.xlarge
displayReleaseVersion	string	No	The database engine version.	ray-1.2.0 (Ray 2.55.1, Python 3.12)
extraParam	string	No	The extra parameters in a JSON string.	{"userDefinedFiles": "oss://mybucket/artifact/config.json,oss://mybucket/artifact/config2.json", "userRequirementsFile": "oss://mybucket/requirements.txt"}
clusterId	string	No	The ID of an existing Ray cluster to which the job is submitted.	ray-xxxxxxxxx

Response elements

Element	Type	Description	Example
	object	Schema of Response
requestId	string	The request ID.	DD6B1B2A-5837-5237-ABE4-FF0C8944
submissionId	string	Ray Job ID。	rj-k7nm8ahl5te4tg91

Examples

Success response

JSON format

{
  "requestId": "DD6B1B2A-5837-5237-ABE4-FF0C8944",
  "submissionId": "rj-k7nm8ahl5te4tg91"
}

Error codes

See Error Codes for a complete list.

Release notes

See Release Notes for a complete list.