class Aws::SageMaker::Types::TransformJob
A batch transform job. For information about SageMaker
batch transform, see [Use Batch Transform].
[1]: docs.aws.amazon.com/sagemaker/latest/dg/batch-transform.html
@!attribute [rw] transform_job_name
The name of the transform job. @return [String]
@!attribute [rw] transform_job_arn
The Amazon Resource Name (ARN) of the transform job. @return [String]
@!attribute [rw] transform_job_status
The status of the transform job. Transform job statuses are: * `InProgress` - The job is in progress. * `Completed` - The job has completed. * `Failed` - The transform job has failed. To see the reason for the failure, see the `FailureReason` field in the response to a `DescribeTransformJob` call. * `Stopping` - The transform job is stopping. * `Stopped` - The transform job has stopped. @return [String]
@!attribute [rw] failure_reason
If the transform job failed, the reason it failed. @return [String]
@!attribute [rw] model_name
The name of the model associated with the transform job. @return [String]
@!attribute [rw] max_concurrent_transforms
The maximum number of parallel requests that can be sent to each instance in a transform job. If `MaxConcurrentTransforms` is set to 0 or left unset, 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. For built-in algorithms, you don't need to set a value for `MaxConcurrentTransforms`. @return [Integer]
@!attribute [rw] model_client_config
Configures the timeout and maximum number of retries for processing a transform job invocation. @return [Types::ModelClientConfig]
@!attribute [rw] max_payload_in_mb
The maximum allowed size of the payload, in MB. A payload is the data portion of a record (without metadata). The value in `MaxPayloadInMB` must be greater than, or equal to, the size of a single record. To estimate the size of a record in MB, divide the size of your dataset by the number of records. To ensure that the records fit within the maximum payload size, we recommend using a slightly larger value. The default value is 6 MB. For cases where the payload might be arbitrarily large and is transmitted using HTTP chunked encoding, set the value to 0. This feature works only in supported algorithms. Currently, SageMaker built-in algorithms do not support HTTP chunked encoding. @return [Integer]
@!attribute [rw] batch_strategy
Specifies the number of records to include in a mini-batch for an HTTP inference request. A record is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record. @return [String]
@!attribute [rw] environment
The environment variables to set in the Docker container. We support up to 16 key and values entries in the map. @return [Hash<String,String>]
@!attribute [rw] transform_input
Describes the input source of a transform job and the way the transform job consumes it. @return [Types::TransformInput]
@!attribute [rw] transform_output
Describes the results of a transform job. @return [Types::TransformOutput]
@!attribute [rw] transform_resources
Describes the resources, including ML instance types and ML instance count, to use for transform job. @return [Types::TransformResources]
@!attribute [rw] creation_time
A timestamp that shows when the transform Job was created. @return [Time]
@!attribute [rw] transform_start_time
Indicates when the transform job starts on ML instances. You are billed for the time interval between this time and the value of `TransformEndTime`. @return [Time]
@!attribute [rw] transform_end_time
Indicates when the transform job has been completed, or has stopped or failed. You are billed for the time interval between this time and the value of `TransformStartTime`. @return [Time]
@!attribute [rw] labeling_job_arn
The Amazon Resource Name (ARN) of the labeling job that created the transform job. @return [String]
@!attribute [rw] auto_ml_job_arn
The Amazon Resource Name (ARN) of the AutoML job that created the transform job. @return [String]
@!attribute [rw] data_processing
The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see [Associate Prediction Results with their Corresponding Input Records][1]. [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html @return [Types::DataProcessing]
@!attribute [rw] experiment_config
Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs: * CreateProcessingJob * CreateTrainingJob * CreateTransformJob @return [Types::ExperimentConfig]
@!attribute [rw] tags
A list of tags associated with the transform job. @return [Array<Types::Tag>]
@see docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TransformJob AWS API Documentation
Constants
- SENSITIVE