aws-cdk-lib.aws_stepfunctions_tasks.SageMakerCreateTransformJobJsonPathProps

SageMakerCreateTransformJobJsonPathProps Struct

Properties for creating an Amazon SageMaker transform job task using JSONPath.

SageMakerCreateTransformJobJsonPathProps

extends

• TaskStateJsonPathBaseProps

Source

aws-stepfunctions-tasks/lib/sagemaker/create-transform-job.ts

Type last changed

v2.178.0 · 6 Feb 2025

Example

// The code below shows an example of how to instantiate this type.
// The values are placeholders you should change.
import * as cdk from 'aws-cdk-lib';
import { aws_ec2 as ec2 } from 'aws-cdk-lib';
import { aws_iam as iam } from 'aws-cdk-lib';
import { aws_stepfunctions as stepfunctions } from 'aws-cdk-lib';
import { aws_stepfunctions_tasks as stepfunctions_tasks } from 'aws-cdk-lib';
import { aws_kms as interfaces_kms } from 'aws-cdk-lib/interfaces';

declare const assign: any;
declare const instanceType: ec2.InstanceType;
declare const keyRef: interfaces_kms.IKeyRef;
declare const resultSelector: any;
declare const role: iam.Role;
declare const size: cdk.Size;
declare const taskRole: stepfunctions.TaskRole;
declare const timeout: stepfunctions.Timeout;
const sageMakerCreateTransformJobJsonPathProps: stepfunctions_tasks.SageMakerCreateTransformJobJsonPathProps = {
  modelName: 'modelName',
  transformInput: {
    transformDataSource: {
      s3DataSource: {
        s3Uri: 's3Uri',

        // the properties below are optional
        s3DataType: stepfunctions_tasks.S3DataType.MANIFEST_FILE,
      },
    },

    // the properties below are optional
    compressionType: stepfunctions_tasks.CompressionType.NONE,
    contentType: 'contentType',
    splitType: stepfunctions_tasks.SplitType.NONE,
  },
  transformJobName: 'transformJobName',
  transformOutput: {
    s3OutputPath: 's3OutputPath',

    // the properties below are optional
    accept: 'accept',
    assembleWith: stepfunctions_tasks.AssembleWith.NONE,
    encryptionKey: keyRef,
  },

  // the properties below are optional
  assign: {
    assignKey: assign,
  },
  batchStrategy: stepfunctions_tasks.BatchStrategy.MULTI_RECORD,
  comment: 'comment',
  credentials: {
    role: taskRole,
  },
  environment: {
    environmentKey: 'environment',
  },
  heartbeat: cdk.Duration.minutes(30),
  heartbeatTimeout: timeout,
  inputPath: 'inputPath',
  integrationPattern: stepfunctions.IntegrationPattern.REQUEST_RESPONSE,
  maxConcurrentTransforms: 123,
  maxPayload: size,
  modelClientOptions: {
    invocationsMaxRetries: 123,
    invocationsTimeout: cdk.Duration.minutes(30),
  },
  outputPath: 'outputPath',
  queryLanguage: stepfunctions.QueryLanguage.JSON_PATH,
  resultPath: 'resultPath',
  resultSelector: {
    resultSelectorKey: resultSelector,
  },
  role: role,
  stateName: 'stateName',
  tags: {
    tagsKey: 'tags',
  },
  taskTimeout: timeout,
  timeout: cdk.Duration.minutes(30),
  transformResources: {
    instanceCount: 123,
    instanceType: instanceType,

    // the properties below are optional
    volumeEncryptionKey: keyRef,
  },
};

Properties

assign?optional{ [key: string]: any }assign?optionaltyping.Mapping[str, Any]assign?optionalMap<String, Object>Assign?optionalIDictionary<string, object>Assign?optional*map[string]interface{}#

Workflow variables to store in this step.

Default: Not assign variables

Using workflow variables, you can store data in a step and retrieve that data in future steps.

batchStrategy?optionalBatchStrategybatch_strategy?optionalBatchStrategybatchStrategy?optionalBatchStrategyBatchStrategy?optionalBatchStrategyBatchStrategy?optionalBatchStrategy#

Number of records to include in a mini-batch for an HTTP inference request.

Default: No batch strategy

comment?optionalstringcomment?optionalstrcomment?optionalStringComment?optionalstringComment?optional*string#

A comment describing this state.

Default: No comment

credentials?optionalCredentialscredentials?optionalCredentialscredentials?optionalCredentialsCredentials?optionalCredentialsCredentials?optionalCredentials#

Credentials for an IAM Role that the State Machine assumes for executing the task.

Default: None (Task is executed using the State Machine's execution role)

This enables cross-account resource invocations.

environment?optional{ [key: string]: string }environment?optionaltyping.Mapping[str, str]environment?optionalMap<String, String>Environment?optionalIDictionary<string, string>Environment?optional*map[string]*string#

Environment variables to set in the Docker container.

Default: No environment variables

heartbeat?optionalDurationheartbeat?optionalDurationheartbeat?optionalDurationHeartbeat?optionalDurationHeartbeat?optionalDuration= Nonedeprecated#

use `heartbeatTimeout`

heartbeatTimeout?optionalTimeoutheartbeat_timeout?optionalTimeoutheartbeatTimeout?optionalTimeoutHeartbeatTimeout?optionalTimeoutHeartbeatTimeout?optionalTimeout= None#

Timeout for the heartbeat.

[disable-awslint:duration-prop-type] is needed because all props interface in aws-stepfunctions-tasks extend this interface

inputPath?optionalstringinput_path?optionalstrinputPath?optionalStringInputPath?optionalstringInputPath?optional*string= $#

JSONPath expression to select part of the state to be the input to this state.

May also be the special value JsonPath.DISCARD, which will cause the effective input to be the empty object {}.

integrationPattern?optionalIntegrationPatternintegration_pattern?optionalIntegrationPatternintegrationPattern?optionalIntegrationPatternIntegrationPattern?optionalIntegrationPatternIntegrationPattern?optionalIntegrationPattern#

AWS Step Functions integrates with services directly in the Amazon States Language.

Default: IntegrationPattern.REQUEST_RESPONSE for most tasks. IntegrationPattern.RUN_JOB for the following exceptions: BatchSubmitJob, EmrAddStep, EmrCreateCluster, EmrTerminationCluster, and EmrContainersStartJobRun.

You can control these AWS services using service integration patterns.

Depending on the AWS Service, the Service Integration Pattern availability will vary.

maxConcurrentTransforms?optionalnumbermax_concurrent_transforms?optionalint | floatmaxConcurrentTransforms?optionalNumberMaxConcurrentTransforms?optionaldoubleMaxConcurrentTransforms?optional*float64#

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

Default: Amazon SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm. If the execution-parameters endpoint is not enabled, the default value is 1.

maxPayload?optionalSizemax_payload?optionalSizemaxPayload?optionalSizeMaxPayload?optionalSizeMaxPayload?optionalSize= 6#

Maximum allowed size of the payload, in MB.

modelClientOptions?optionalModelClientOptionsmodel_client_options?optionalModelClientOptionsmodelClientOptions?optionalModelClientOptionsModelClientOptions?optionalModelClientOptionsModelClientOptions?optionalModelClientOptions#

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

Default: 0 retries and 60 seconds of timeout

modelNamestringmodel_namestrmodelNameStringModelNamestringModelName*stringrequired#

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

outputPath?optionalstringoutput_path?optionalstroutputPath?optionalStringOutputPath?optionalstringOutputPath?optional*string= $#

JSONPath expression to select part of the state to be the output to this state.

May also be the special value JsonPath.DISCARD, which will cause the effective output to be the empty object {}.

queryLanguage?optionalQueryLanguagequery_language?optionalQueryLanguagequeryLanguage?optionalQueryLanguageQueryLanguage?optionalQueryLanguageQueryLanguage?optionalQueryLanguage= JSONPath#

The name of the query language used by the state.

If the state does not contain a queryLanguage field, then it will use the query language specified in the top-level queryLanguage field.

resultPath?optionalstringresult_path?optionalstrresultPath?optionalStringResultPath?optionalstringResultPath?optional*string= $#

JSONPath expression to indicate where to inject the state's output.

May also be the special value JsonPath.DISCARD, which will cause the state's input to become its output.

resultSelector?optional{ [key: string]: any }result_selector?optionaltyping.Mapping[str, Any]resultSelector?optionalMap<String, Object>ResultSelector?optionalIDictionary<string, object>ResultSelector?optional*map[string]interface{}= None#

The JSON that will replace the state's raw result and become the effective result before ResultPath is applied.

You can use ResultSelector to create a payload with values that are static or selected from the state's raw result.

role?optionalIRolerole?optionalIRolerole?optionalIRoleRole?optionalIRoleRole?optionalIRole#

Role for the Transform Job.

Default: A role is created with AmazonSageMakerFullAccess managed policy

stateName?optionalstringstate_name?optionalstrstateName?optionalStringStateName?optionalstringStateName?optional*string#

Optional name for this state.

Default: The construct ID will be used as state name

tags?optional{ [key: string]: string }tags?optionaltyping.Mapping[str, str]tags?optionalMap<String, String>Tags?optionalIDictionary<string, string>Tags?optional*map[string]*string#

Tags to be applied to the train job.

Default: No tags

taskTimeout?optionalTimeouttask_timeout?optionalTimeouttaskTimeout?optionalTimeoutTaskTimeout?optionalTimeoutTaskTimeout?optionalTimeout= None#

Timeout for the task.

[disable-awslint:duration-prop-type] is needed because all props interface in aws-stepfunctions-tasks extend this interface

timeout?optionalDurationtimeout?optionalDurationtimeout?optionalDurationTimeout?optionalDurationTimeout?optionalDuration= Nonedeprecated#

use `taskTimeout`

transformInputTransformInputtransform_inputTransformInputtransformInputTransformInputTransformInputTransformInputTransformInputTransformInputrequired#

Dataset to be transformed and the Amazon S3 location where it is stored.

transformJobNamestringtransform_job_namestrtransformJobNameStringTransformJobNamestringTransformJobName*stringrequired#

Transform Job Name.

transformOutputTransformOutputtransform_outputTransformOutputtransformOutputTransformOutputTransformOutputTransformOutputTransformOutputTransformOutputrequired#

S3 location where you want Amazon SageMaker to save the results from the transform job.

transformResources?optionalTransformResourcestransform_resources?optionalTransformResourcestransformResources?optionalTransformResourcesTransformResources?optionalTransformResourcesTransformResources?optionalTransformResources#

ML compute instances for the transform job.

Default: 1 instance of type M4.XLarge