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aws_sagemaker_processingjob

account_id

Type: STRING

app_specification

Type: STRUCT
Provider name: AppSpecification
Description: Configures the processing job to run a specified container image.

  • container_arguments
    Type: UNORDERED_LIST_STRING
    Provider name: ContainerArguments
    Description: The arguments for a container used to run a processing job.
  • container_entrypoint
    Type: UNORDERED_LIST_STRING
    Provider name: ContainerEntrypoint
    Description: The entrypoint for a container used to run a processing job.
  • image_uri
    Type: STRING
    Provider name: ImageUri
    Description: The container image to be run by the processing job.

auto_ml_job_arn

Type: STRING
Provider name: AutoMLJobArn
Description: The ARN of an AutoML job associated with this processing job.

creation_time

Type: TIMESTAMP
Provider name: CreationTime
Description: The time at which the processing job was created.

environment

Type: MAP_STRING_STRING
Provider name: Environment
Description: The environment variables set in the Docker container.

exit_message

Type: STRING
Provider name: ExitMessage
Description: An optional string, up to one KB in size, that contains metadata from the processing container when the processing job exits.

experiment_config

Type: STRUCT
Provider name: ExperimentConfig
Description: The configuration information used to create an experiment.

  • experiment_name
    Type: STRING
    Provider name: ExperimentName
    Description: The name of an existing experiment to associate with the trial component.
  • run_name
    Type: STRING
    Provider name: RunName
    Description: The name of the experiment run to associate with the trial component.
  • trial_component_display_name
    Type: STRING
    Provider name: TrialComponentDisplayName
    Description: The display name for the trial component. If this key isn’t specified, the display name is the trial component name.
  • trial_name
    Type: STRING
    Provider name: TrialName
    Description: The name of an existing trial to associate the trial component with. If not specified, a new trial is created.

failure_reason

Type: STRING
Provider name: FailureReason
Description: A string, up to one KB in size, that contains the reason a processing job failed, if it failed.

last_modified_time

Type: TIMESTAMP
Provider name: LastModifiedTime
Description: The time at which the processing job was last modified.

monitoring_schedule_arn

Type: STRING
Provider name: MonitoringScheduleArn
Description: The ARN of a monitoring schedule for an endpoint associated with this processing job.

network_config

Type: STRUCT
Provider name: NetworkConfig
Description: Networking options for a processing job.

  • enable_inter_container_traffic_encryption
    Type: BOOLEAN
    Provider name: EnableInterContainerTrafficEncryption
    Description: Whether to encrypt all communications between distributed processing jobs. Choose True to encrypt communications. Encryption provides greater security for distributed processing jobs, but the processing might take longer.
  • enable_network_isolation
    Type: BOOLEAN
    Provider name: EnableNetworkIsolation
    Description: Whether to allow inbound and outbound network calls to and from the containers used for the processing job.
  • vpc_config
    Type: STRUCT
    Provider name: VpcConfig
    • security_group_ids
      Type: UNORDERED_LIST_STRING
      Provider name: SecurityGroupIds
      Description: The VPC security group IDs, in the form sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.
    • subnets
      Type: UNORDERED_LIST_STRING
      Provider name: Subnets
      Description: The ID of the subnets in the VPC to which you want to connect your training job or model. For information about the availability of specific instance types, see Supported Instance Types and Availability Zones.

processing_end_time

Type: TIMESTAMP
Provider name: ProcessingEndTime
Description: The time at which the processing job completed.

processing_inputs

Type: UNORDERED_LIST_STRUCT
Provider name: ProcessingInputs
Description: The inputs for a processing job.

  • app_managed
    Type: BOOLEAN
    Provider name: AppManaged
    Description: When True, input operations such as data download are managed natively by the processing job application. When False (default), input operations are managed by Amazon SageMaker.
  • dataset_definition
    Type: STRUCT
    Provider name: DatasetDefinition
    Description: Configuration for a Dataset Definition input.
    • athena_dataset_definition
      Type: STRUCT
      Provider name: AthenaDatasetDefinition
      • catalog
        Type: STRING
        Provider name: Catalog
      • database
        Type: STRING
        Provider name: Database
      • kms_key_id
        Type: STRING
        Provider name: KmsKeyId
        Description: The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data generated from an Athena query execution.
      • output_compression
        Type: STRING
        Provider name: OutputCompression
      • output_format
        Type: STRING
        Provider name: OutputFormat
      • output_s3_uri
        Type: STRING
        Provider name: OutputS3Uri
        Description: The location in Amazon S3 where Athena query results are stored.
      • query_string
        Type: STRING
        Provider name: QueryString
      • work_group
        Type: STRING
        Provider name: WorkGroup
    • data_distribution_type
      Type: STRING
      Provider name: DataDistributionType
      Description: Whether the generated dataset is FullyReplicated or ShardedByS3Key (default).
    • input_mode
      Type: STRING
      Provider name: InputMode
      Description: Whether to use File or Pipe input mode. In File (default) mode, Amazon SageMaker copies the data from the input source onto the local Amazon Elastic Block Store (Amazon EBS) volumes before starting your training algorithm. This is the most commonly used input mode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your algorithm without using the EBS volume.
    • local_path
      Type: STRING
      Provider name: LocalPath
      Description: The local path where you want Amazon SageMaker to download the Dataset Definition inputs to run a processing job. LocalPath is an absolute path to the input data. This is a required parameter when AppManaged is False (default).
    • redshift_dataset_definition
      Type: STRUCT
      Provider name: RedshiftDatasetDefinition
      • cluster_id
        Type: STRING
        Provider name: ClusterId
      • cluster_role_arn
        Type: STRING
        Provider name: ClusterRoleArn
        Description: The IAM role attached to your Redshift cluster that Amazon SageMaker uses to generate datasets.
      • database
        Type: STRING
        Provider name: Database
      • db_user
        Type: STRING
        Provider name: DbUser
      • kms_key_id
        Type: STRING
        Provider name: KmsKeyId
        Description: The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data from a Redshift execution.
      • output_compression
        Type: STRING
        Provider name: OutputCompression
      • output_format
        Type: STRING
        Provider name: OutputFormat
      • output_s3_uri
        Type: STRING
        Provider name: OutputS3Uri
        Description: The location in Amazon S3 where the Redshift query results are stored.
      • query_string
        Type: STRING
        Provider name: QueryString
  • input_name
    Type: STRING
    Provider name: InputName
    Description: The name for the processing job input.
  • s3_input
    Type: STRUCT
    Provider name: S3Input
    Description: Configuration for downloading input data from Amazon S3 into the processing container.
    • local_path
      Type: STRING
      Provider name: LocalPath
      Description: The local path in your container where you want Amazon SageMaker to write input data to. LocalPath is an absolute path to the input data and must begin with /opt/ml/processing/. LocalPath is a required parameter when AppManaged is False (default).
    • s3_compression_type
      Type: STRING
      Provider name: S3CompressionType
      Description: Whether to GZIP-decompress the data in Amazon S3 as it is streamed into the processing container. Gzip can only be used when Pipe mode is specified as the S3InputMode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your container without using the EBS volume.
    • s3_data_distribution_type
      Type: STRING
      Provider name: S3DataDistributionType
      Description: Whether to distribute the data from Amazon S3 to all processing instances with FullyReplicated, or whether the data from Amazon S3 is shared by Amazon S3 key, downloading one shard of data to each processing instance.
    • s3_data_type
      Type: STRING
      Provider name: S3DataType
      Description: Whether you use an S3Prefix or a ManifestFile for the data type. If you choose S3Prefix, S3Uri identifies a key name prefix. Amazon SageMaker uses all objects with the specified key name prefix for the processing job. 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 the processing job.
    • s3_input_mode
      Type: STRING
      Provider name: S3InputMode
      Description: Whether to use File or Pipe input mode. In File mode, Amazon SageMaker copies the data from the input source onto the local ML storage volume before starting your processing container. This is the most commonly used input mode. In Pipe mode, Amazon SageMaker streams input data from the source directly to your processing container into named pipes without using the ML storage volume.
    • s3_uri
      Type: STRING
      Provider name: S3Uri
      Description: The URI of the Amazon S3 prefix Amazon SageMaker downloads data required to run a processing job.

processing_job_arn

Type: STRING
Provider name: ProcessingJobArn
Description: The Amazon Resource Name (ARN) of the processing job.

processing_job_name

Type: STRING
Provider name: ProcessingJobName
Description: The name of the processing job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.

processing_job_status

Type: STRING
Provider name: ProcessingJobStatus
Description: Provides the status of a processing job.

processing_output_config

Type: STRUCT
Provider name: ProcessingOutputConfig
Description: Output configuration for the processing job.

  • kms_key_id
    Type: STRING
    Provider name: KmsKeyId
    Description: The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt the processing job output. KmsKeyId can be an ID of a KMS key, ARN of a KMS key, or alias of a KMS key. The KmsKeyId is applied to all outputs.
  • outputs
    Type: UNORDERED_LIST_STRUCT
    Provider name: Outputs
    Description: An array of outputs configuring the data to upload from the processing container.
    • app_managed
      Type: BOOLEAN
      Provider name: AppManaged
      Description: When True, output operations such as data upload are managed natively by the processing job application. When False (default), output operations are managed by Amazon SageMaker.
    • feature_store_output
      Type: STRUCT
      Provider name: FeatureStoreOutput
      Description: Configuration for processing job outputs in Amazon SageMaker Feature Store. This processing output type is only supported when AppManaged is specified.
      • feature_group_name
        Type: STRING
        Provider name: FeatureGroupName
        Description: The name of the Amazon SageMaker FeatureGroup to use as the destination for processing job output. Note that your processing script is responsible for putting records into your Feature Store.
    • output_name
      Type: STRING
      Provider name: OutputName
      Description: The name for the processing job output.
    • s3_output
      Type: STRUCT
      Provider name: S3Output
      Description: Configuration for processing job outputs in Amazon S3.
      • local_path
        Type: STRING
        Provider name: LocalPath
        Description: The local path of a directory where you want Amazon SageMaker to upload its contents to Amazon S3. LocalPath is an absolute path to a directory containing output files. This directory will be created by the platform and exist when your container’s entrypoint is invoked.
      • s3_upload_mode
        Type: STRING
        Provider name: S3UploadMode
        Description: Whether to upload the results of the processing job continuously or after the job completes.
      • s3_uri
        Type: STRING
        Provider name: S3Uri
        Description: A URI that identifies the Amazon S3 bucket where you want Amazon SageMaker to save the results of a processing job.

processing_resources

Type: STRUCT
Provider name: ProcessingResources
Description: Identifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.

  • cluster_config
    Type: STRUCT
    Provider name: ClusterConfig
    Description: The configuration for the resources in a cluster used to run the processing job.
    • instance_count
      Type: INT32
      Provider name: InstanceCount
      Description: The number of ML compute instances to use in the processing job. For distributed processing jobs, specify a value greater than 1. The default value is 1.
    • instance_type
      Type: STRING
      Provider name: InstanceType
      Description: The ML compute instance type for the processing job.
    • volume_kms_key_id
      Type: STRING
      Provider name: VolumeKmsKeyId
      Description: The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the processing job. Certain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can’t request a VolumeKmsKeyId when using an instance type with local storage. For a list of instance types that support local instance storage, see Instance Store Volumes. For more information about local instance storage encryption, see SSD Instance Store Volumes.
    • volume_size_in_gb
      Type: INT32
      Provider name: VolumeSizeInGB
      Description: The size of the ML storage volume in gigabytes that you want to provision. You must specify sufficient ML storage for your scenario. Certain Nitro-based instances include local storage with a fixed total size, dependent on the instance type. When using these instances for processing, Amazon SageMaker mounts the local instance storage instead of Amazon EBS gp2 storage. You can’t request a VolumeSizeInGB greater than the total size of the local instance storage. For a list of instance types that support local instance storage, including the total size per instance type, see Instance Store Volumes.

processing_start_time

Type: TIMESTAMP
Provider name: ProcessingStartTime
Description: The time at which the processing job started.

role_arn

Type: STRING
Provider name: RoleArn
Description: The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.

stopping_condition

Type: STRUCT
Provider name: StoppingCondition
Description: The time limit for how long the processing job is allowed to run.

  • max_runtime_in_seconds
    Type: INT32
    Provider name: MaxRuntimeInSeconds
    Description: Specifies the maximum runtime in seconds.

tags

Type: UNORDERED_LIST_STRING

training_job_arn

Type: STRING
Provider name: TrainingJobArn
Description: The ARN of a training job associated with this processing job.