S3DataSource
- class aws_cdk.aws_stepfunctions_tasks.S3DataSource(*, s3_location, attribute_names=None, s3_data_distribution_type=None, s3_data_type=None)
Bases:
object
S3 location of the channel data.
- Parameters:
s3_location (
S3Location
) – S3 Uri.attribute_names (
Optional
[Sequence
[str
]]) – List of one or more attribute names to use that are found in a specified augmented manifest file. Default: - No attribute namess3_data_distribution_type (
Optional
[S3DataDistributionType
]) – S3 Data Distribution Type. Default: - Nones3_data_type (
Optional
[S3DataType
]) – S3 Data Type. Default: S3_PREFIX
- See:
https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_S3DataSource.html
- ExampleMetadata:
infused
Example:
tasks.SageMakerCreateTrainingJob(self, "TrainSagemaker", training_job_name=sfn.JsonPath.string_at("$.JobName"), algorithm_specification=tasks.AlgorithmSpecification( algorithm_name="BlazingText", training_input_mode=tasks.InputMode.FILE ), input_data_config=[tasks.Channel( channel_name="train", data_source=tasks.DataSource( s3_data_source=tasks.S3DataSource( s3_data_type=tasks.S3DataType.S3_PREFIX, s3_location=tasks.S3Location.from_json_expression("$.S3Bucket") ) ) )], output_data_config=tasks.OutputDataConfig( s3_output_location=tasks.S3Location.from_bucket(s3.Bucket.from_bucket_name(self, "Bucket", "amzn-s3-demo-bucket"), "myoutputpath") ), resource_config=tasks.ResourceConfig( instance_count=1, instance_type=ec2.InstanceType(sfn.JsonPath.string_at("$.InstanceType")), volume_size=Size.gibibytes(50) ), # optional: default is 1 instance of EC2 `M4.XLarge` with `10GB` volume stopping_condition=tasks.StoppingCondition( max_runtime=Duration.hours(2) ) )
Attributes
- attribute_names
List of one or more attribute names to use that are found in a specified augmented manifest file.
- Default:
No attribute names
- s3_data_distribution_type
S3 Data Distribution Type.
- Default:
None
- s3_data_type
S3 Data Type.
- Default:
S3_PREFIX
- s3_location
S3 Uri.