ProcessingJob

sagemaker.services.k8s.aws/v1alpha1

Metadata#

An Amazon SageMaker processing job that is used to analyze data and evaluate models. For more information, see Process Data and Evaluate Models (https://docs.aws.amazon.com/sagemaker/latest/dg/processing-job.html).

Spec#

appSpecification: 
  containerArguments:
  - string
  containerEntrypoint:
  - string
  imageURI: string
environment: {}
experimentConfig: 
  experimentName: string
  trialComponentDisplayName: string
  trialName: string
networkConfig: 
  enableInterContainerTrafficEncryption: boolean
  enableNetworkIsolation: boolean
  vpcConfig: 
    securityGroupIDs:
    - string
    subnets:
    - string
processingInputs:
- appManaged: boolean
  datasetDefinition: 
    athenaDatasetDefinition: 
      catalog: string
      database: string
      kmsKeyID: string
      outputCompression: string
      outputFormat: string
      outputS3URI: string
      queryString: string
      workGroup: string
    dataDistributionType: string
    inputMode: string
    localPath: string
    redshiftDatasetDefinition: 
      clusterID: string
      clusterRoleARN: string
      database: string
      dbUser: string
      kmsKeyID: string
      outputCompression: string
      outputFormat: string
      outputS3URI: string
      queryString: string
  inputName: string
  s3Input: 
    localPath: string
    s3CompressionType: string
    s3DataDistributionType: string
    s3DataType: string
    s3InputMode: string
    s3URI: string
processingJobName: string
processingOutputConfig: 
  kmsKeyID: string
  outputs:
  - appManaged: boolean
    featureStoreOutput: 
      featureGroupName: string
    outputName: string
    s3Output: 
      localPath: string
      s3URI: string
      s3UploadMode: string
processingResources: 
  clusterConfig: 
    instanceCount: integer
    instanceType: string
    volumeKMSKeyID: string
    volumeSizeInGB: integer
roleARN: string
stoppingCondition: 
  maxRuntimeInSeconds: integer
tags:
- key: string
  value: string

You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints. For more information on adding tags to SageMaker resources, see AddTags (https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_AddTags.html).

For more information on adding metadata to your Amazon Web Services resources with tagging, see Tagging Amazon Web Services resources (https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html). For advice on best practices for managing Amazon Web Services resources with tagging, see Tagging Best Practices: Implement an Effective Amazon Web Services Resource Tagging Strategy (https://d1.awsstatic.com/whitepapers/aws-tagging-best-practices.pdf). || tags.[].key
Optional | string
| | tags.[].value
Optional | string
|

Status#

ackResourceMetadata: 
  arn: string
  ownerAccountID: string
  region: string
conditions:
- lastTransitionTime: string
  message: string
  reason: string
  status: string
  type: string
failureReason: string
processingJobStatus: string