CfnDataQualityJobDefinitionProps¶
-
class
aws_cdk.aws_sagemaker.
CfnDataQualityJobDefinitionProps
(*, data_quality_app_specification, data_quality_job_input, data_quality_job_output_config, job_resources, role_arn, data_quality_baseline_config=None, job_definition_name=None, network_config=None, stopping_condition=None, tags=None)¶ Bases:
object
Properties for defining a
CfnDataQualityJobDefinition
.- Parameters
data_quality_app_specification (
Union
[IResolvable
,DataQualityAppSpecificationProperty
]) – Specifies the container that runs the monitoring job.data_quality_job_input (
Union
[IResolvable
,DataQualityJobInputProperty
]) – A list of inputs for the monitoring job. Currently endpoints are supported as monitoring inputs.data_quality_job_output_config (
Union
[IResolvable
,MonitoringOutputConfigProperty
]) – The output configuration for monitoring jobs.job_resources (
Union
[IResolvable
,MonitoringResourcesProperty
]) – Identifies the resources to deploy for a monitoring job.role_arn (
str
) – The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.data_quality_baseline_config (
Union
[IResolvable
,DataQualityBaselineConfigProperty
,None
]) – Configures the constraints and baselines for the monitoring job.job_definition_name (
Optional
[str
]) – The name for the monitoring job definition.network_config (
Union
[IResolvable
,NetworkConfigProperty
,None
]) – Specifies networking configuration for the monitoring job.stopping_condition (
Union
[IResolvable
,StoppingConditionProperty
,None
]) – A time limit for how long the monitoring job is allowed to run before stopping.tags (
Optional
[Sequence
[CfnTag
]]) – An array of key-value pairs to apply to this resource. For more information, see Tag .
- Link
- ExampleMetadata
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_sagemaker as sagemaker cfn_data_quality_job_definition_props = sagemaker.CfnDataQualityJobDefinitionProps( data_quality_app_specification=sagemaker.CfnDataQualityJobDefinition.DataQualityAppSpecificationProperty( image_uri="imageUri", # the properties below are optional container_arguments=["containerArguments"], container_entrypoint=["containerEntrypoint"], environment={ "environment_key": "environment" }, post_analytics_processor_source_uri="postAnalyticsProcessorSourceUri", record_preprocessor_source_uri="recordPreprocessorSourceUri" ), data_quality_job_input=sagemaker.CfnDataQualityJobDefinition.DataQualityJobInputProperty( endpoint_input=sagemaker.CfnDataQualityJobDefinition.EndpointInputProperty( endpoint_name="endpointName", local_path="localPath", # the properties below are optional s3_data_distribution_type="s3DataDistributionType", s3_input_mode="s3InputMode" ) ), data_quality_job_output_config=sagemaker.CfnDataQualityJobDefinition.MonitoringOutputConfigProperty( monitoring_outputs=[sagemaker.CfnDataQualityJobDefinition.MonitoringOutputProperty( s3_output=sagemaker.CfnDataQualityJobDefinition.S3OutputProperty( local_path="localPath", s3_uri="s3Uri", # the properties below are optional s3_upload_mode="s3UploadMode" ) )], # the properties below are optional kms_key_id="kmsKeyId" ), job_resources=sagemaker.CfnDataQualityJobDefinition.MonitoringResourcesProperty( cluster_config=sagemaker.CfnDataQualityJobDefinition.ClusterConfigProperty( instance_count=123, instance_type="instanceType", volume_size_in_gb=123, # the properties below are optional volume_kms_key_id="volumeKmsKeyId" ) ), role_arn="roleArn", # the properties below are optional data_quality_baseline_config=sagemaker.CfnDataQualityJobDefinition.DataQualityBaselineConfigProperty( baselining_job_name="baseliningJobName", constraints_resource=sagemaker.CfnDataQualityJobDefinition.ConstraintsResourceProperty( s3_uri="s3Uri" ), statistics_resource=sagemaker.CfnDataQualityJobDefinition.StatisticsResourceProperty( s3_uri="s3Uri" ) ), job_definition_name="jobDefinitionName", network_config=sagemaker.CfnDataQualityJobDefinition.NetworkConfigProperty( enable_inter_container_traffic_encryption=False, enable_network_isolation=False, vpc_config=sagemaker.CfnDataQualityJobDefinition.VpcConfigProperty( security_group_ids=["securityGroupIds"], subnets=["subnets"] ) ), stopping_condition=sagemaker.CfnDataQualityJobDefinition.StoppingConditionProperty( max_runtime_in_seconds=123 ), tags=[CfnTag( key="key", value="value" )] )
Attributes
-
data_quality_app_specification
¶ Specifies the container that runs the monitoring job.
-
data_quality_baseline_config
¶ Configures the constraints and baselines for the monitoring job.
-
data_quality_job_input
¶ A list of inputs for the monitoring job.
Currently endpoints are supported as monitoring inputs.
-
data_quality_job_output_config
¶ The output configuration for monitoring jobs.
-
job_definition_name
¶ The name for the monitoring job definition.
-
job_resources
¶ Identifies the resources to deploy for a monitoring job.
-
network_config
¶ Specifies networking configuration for the monitoring job.
-
role_arn
¶ The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
-
stopping_condition
¶ A time limit for how long the monitoring job is allowed to run before stopping.
An array of key-value pairs to apply to this resource.
For more information, see Tag .