interface CfnTransformJobProps

Language	Type name
.NET	`Amazon.CDK.AWS.Sagemaker.CfnTransformJobProps`
Go	`github.com/aws/aws-cdk-go/awscdk/v2/awssagemaker#CfnTransformJobProps`
Java	`software.amazon.awscdk.services.sagemaker.CfnTransformJobProps`
Python	`aws_cdk.aws_sagemaker.CfnTransformJobProps`
TypeScript	`aws-cdk-lib` » `aws_sagemaker` » `CfnTransformJobProps`

Properties for defining a CfnTransformJob.

Example

// The code below shows an example of how to instantiate this type.
// The values are placeholders you should change.
import { aws_sagemaker as sagemaker } from 'aws-cdk-lib';
const cfnTransformJobProps: sagemaker.CfnTransformJobProps = {
  modelName: 'modelName',
  transformInput: {
    dataSource: {
      s3DataSource: {
        s3DataType: 's3DataType',
        s3Uri: 's3Uri',
      },
    },

    // the properties below are optional
    compressionType: 'compressionType',
    contentType: 'contentType',
    splitType: 'splitType',
  },
  transformOutput: {
    s3OutputPath: 's3OutputPath',

    // the properties below are optional
    accept: 'accept',
    assembleWith: 'assembleWith',
    kmsKeyId: 'kmsKeyId',
  },
  transformResources: {
    instanceCount: 123,
    instanceType: 'instanceType',

    // the properties below are optional
    volumeKmsKeyId: 'volumeKmsKeyId',
  },

  // the properties below are optional
  batchStrategy: 'batchStrategy',
  dataCaptureConfig: {
    destinationS3Uri: 'destinationS3Uri',

    // the properties below are optional
    generateInferenceId: false,
    kmsKeyId: 'kmsKeyId',
  },
  dataProcessing: {
    inputFilter: 'inputFilter',
    joinSource: 'joinSource',
    outputFilter: 'outputFilter',
  },
  environment: {
    environmentKey: 'environment',
  },
  experimentConfig: {
    experimentName: 'experimentName',
    trialComponentDisplayName: 'trialComponentDisplayName',
    trialName: 'trialName',
  },
  maxConcurrentTransforms: 123,
  maxPayloadInMb: 123,
  modelClientConfig: {
    invocationsMaxRetries: 123,
    invocationsTimeoutInSeconds: 123,
  },
  tags: [{
    key: 'key',
    value: 'value',
  }],
};

Properties

Name	Type	Description
modelName	`string`	The name of the model that you want to use for the transform job.
transformInput	`IResolvable` `\|` `TransformInputProperty`	Describes the input source and the way the transform job consumes it.
transformOutput	`IResolvable` `\|` `TransformOutputProperty`	Describes the results of the transform job.
transformResources	`IResolvable` `\|` `TransformResourcesProperty`	Describes the resources, including ML instance types and ML instance count, to use for the transform job.
batchStrategy?	`string`	Specifies the number of records to include in a mini-batch for an HTTP inference request.
dataCaptureConfig?	`IResolvable` `\|` `DataCaptureConfigProperty`	Configuration to control how SageMaker captures inference data.
dataProcessing?	`IResolvable` `\|` `DataProcessingProperty`	The data structure used to specify the data to be used for inference in a batch transform job.
environment?	`IResolvable` `\| { [string]: string }`	The environment variables to set in the Docker container.
experimentConfig?	`IResolvable` `\|` `ExperimentConfigProperty`	Associates a SageMaker job as a trial component with an experiment and trial.
maxConcurrentTransforms?	`number`	The maximum number of parallel requests that can be sent to each instance in a transform job.
maxPayloadInMb?	`number`	The maximum allowed size of the payload, in MB.
modelClientConfig?	`IResolvable` `\|` `ModelClientConfigProperty`	Configures the timeout and maximum number of retries for processing a transform job invocation.
tags?	`TagsItemsProperty[]`	An array of key-value pairs.

modelName

Type: string

The name of the model that you want to use for the transform job.

transformInput

Type: IResolvable | TransformInputProperty

Describes the input source and the way the transform job consumes it.

transformOutput

Type: IResolvable | TransformOutputProperty

Describes the results of the transform job.

transformResources

Type: IResolvable | TransformResourcesProperty

Describes the resources, including ML instance types and ML instance count, to use for the transform job.

batchStrategy?

Type: string (optional)

Specifies the number of records to include in a mini-batch for an HTTP inference request.

dataCaptureConfig?

Type: IResolvable | DataCaptureConfigProperty (optional)

Configuration to control how SageMaker captures inference data.

dataProcessing?

Type: IResolvable | DataProcessingProperty (optional)

The data structure used to specify the data to be used for inference in a batch transform job.

environment?

Type: IResolvable | { [string]: string } (optional)

The environment variables to set in the Docker container.

experimentConfig?

Type: IResolvable | ExperimentConfigProperty (optional)

Associates a SageMaker job as a trial component with an experiment and trial.

maxConcurrentTransforms?

Type: number (optional)

The maximum number of parallel requests that can be sent to each instance in a transform job.

maxPayloadInMb?

Type: number (optional)

The maximum allowed size of the payload, in MB.

modelClientConfig?

Type: IResolvable | ModelClientConfigProperty (optional)

Configures the timeout and maximum number of retries for processing a transform job invocation.

tags?

Type: TagsItemsProperty[] (optional)

An array of key-value pairs.

AWS CDK

2.264.0