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[ aws . sagemaker ]

describe-transform-job

Description

Returns information about a transform job.

See also: AWS API Documentation

See 'aws help' for descriptions of global parameters.

Synopsis

  describe-transform-job
--transform-job-name <value>
[--cli-input-json <value>]
[--generate-cli-skeleton <value>]

Options

--transform-job-name (string)

The name of the transform job that you want to view details of.

--cli-input-json (string) Performs service operation based on the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, the CLI values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally.

--generate-cli-skeleton (string) Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for --cli-input-json. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command.

See 'aws help' for descriptions of global parameters.

Output

TransformJobName -> (string)

The name of the transform job.

TransformJobArn -> (string)

The Amazon Resource Name (ARN) of the transform job.

TransformJobStatus -> (string)

The status of the transform job. If the transform job failed, the reason is returned in the FailureReason field.

FailureReason -> (string)

If the transform job failed, the reason that it failed.

ModelName -> (string)

The name of the model used in the transform job.

MaxConcurrentTransforms -> (integer)

The maximum number of parallel requests on each instance node that can be launched in a transform job. The default value is 1.

MaxPayloadInMB -> (integer)

The maximum payload size , in MB used in the transform job.

BatchStrategy -> (string)

SingleRecord means only one record was used per a batch. MultiRecord means batches contained as many records that could possibly fit within the MaxPayloadInMB limit.

Environment -> (map)

key -> (string)

value -> (string)

TransformInput -> (structure)

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

DataSource -> (structure)

Describes the location of the channel data, meaning the S3 location of the input data that the model can consume.

S3DataSource -> (structure)

The S3 location of the data source that is associated with a channel.

S3DataType -> (string)

If you choose S3Prefix , S3Uri identifies a key name prefix. Amazon SageMaker uses all objects with the specified key name prefix for batch transform.

If you choose ManifestFile , S3Uri identifies an object that is a manifest file containing a list of object keys that you want Amazon SageMaker to use for batch transform.

S3Uri -> (string)

Depending on the value specified for the S3DataType , identifies either a key name prefix or a manifest. For example:

  • A key name prefix might look like this: s3://bucketname/exampleprefix .
  • A manifest might look like this: s3://bucketname/example.manifest The manifest is an S3 object which is a JSON file with the following format: [ {"prefix": "s3://customer_bucket/some/prefix/"}, "relative/path/to/custdata-1", "relative/path/custdata-2", ... ] The preceding JSON matches the following S3Uris : s3://customer_bucket/some/prefix/relative/path/to/custdata-1 s3://customer_bucket/some/prefix/relative/path/custdata-1 ... The complete set of S3Uris in this manifest constitutes the input data for the channel for this datasource. The object that each S3Uris points to must be readable by the IAM role that Amazon SageMaker uses to perform tasks on your behalf.

ContentType -> (string)

The multipurpose internet mail extension (MIME) type of the data. Amazon SageMaker uses the MIME type with each http call to transfer data to the transform job.

CompressionType -> (string)

Compressing data helps save on storage space. If your transform data is compressed, specify the compression type. Amazon SageMaker automatically decompresses the data for the transform job accordingly. The default value is None .

SplitType -> (string)

The method to use to split the transform job's data into smaller batches. The default value is None . If you don't want to split the data, specify None . If you want to split records on a newline character boundary, specify Line . To split records according to the RecordIO format, specify RecordIO .

Amazon SageMaker will send maximum number of records per batch in each request up to the MaxPayloadInMB limit. For more information, see RecordIO data format .

Note

For information about the RecordIO format, see Data Format .

TransformOutput -> (structure)

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

S3OutputPath -> (string)

The Amazon S3 path where you want Amazon SageMaker to store the results of the transform job. For example, s3://bucket-name/key-name-prefix .

For every S3 object used as input for the transform job, the transformed data is stored in a corresponding subfolder in the location under the output prefix. For example, the input data s3://bucket-name/input-name-prefix/dataset01/data.csv will have the transformed data stored at s3://bucket-name/key-name-prefix/dataset01/ , based on the original name, as a series of .part files (.part0001, part0002, etc).

Accept -> (string)

The MIME type used to specify the output data. Amazon SageMaker uses the MIME type with each http call to transfer data from the transform job.

AssembleWith -> (string)

Defines how to assemble the results of the transform job as a single S3 object. You should select a format that is most convenient to you. To concatenate the results in binary format, specify None . To add a newline character at the end of every transformed record, specify Line .

KmsKeyId -> (string)

The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption. The KmsKeyId can be any of the following formats:

  • // KMS Key ID "1234abcd-12ab-34cd-56ef-1234567890ab"
  • // Amazon Resource Name (ARN) of a KMS Key "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
  • // KMS Key Alias "alias/ExampleAlias"
  • // Amazon Resource Name (ARN) of a KMS Key Alias "arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"

If you don't provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role's account. For more information, see KMS-Managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.

The KMS key policy must grant permission to the IAM role that you specify in your CreateTramsformJob request. For more information, see Using Key Policies in AWS KMS in the AWS Key Management Service Developer Guide .

TransformResources -> (structure)

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

InstanceType -> (string)

The ML compute instance type for the transform job. For using built-in algorithms to transform moderately sized datasets, ml.m4.xlarge or ml.m5.large should suffice. There is no default value for InstanceType .

InstanceCount -> (integer)

The number of ML compute instances to use in the transform job. For distributed transform, provide a value greater than 1. The default value is 1 .

VolumeKmsKeyId -> (string)

The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the batch transform job. The VolumeKmsKeyId can be any of the following formats:

  • // KMS Key ID "1234abcd-12ab-34cd-56ef-1234567890ab"
  • // Amazon Resource Name (ARN) of a KMS Key "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"

CreationTime -> (timestamp)

A timestamp that shows when the transform Job was created.

TransformStartTime -> (timestamp)

Indicates when the transform job starts on ML instances. You are billed for the time interval between this time and the value of TransformEndTime .

TransformEndTime -> (timestamp)

Indicates when the transform job is Completed , Stopped , or Failed . You are billed for the time interval between this time and the value of TransformStartTime .

LabelingJobArn -> (string)

The Amazon Resource Name (ARN) of the Amazon SageMaker Ground Truth labeling job that created the transform or training job.