pulumi-aws-native-kotlin/com.pulumi.awsnative.sagemaker.kotlin.inputs/DataQualityJobDefinitionBatchTransformInputArgs

DataQualityJobDefinitionBatchTransformInputArgs

data class DataQualityJobDefinitionBatchTransformInputArgs(val dataCapturedDestinationS3Uri: Output<String>, val datasetFormat: Output<DataQualityJobDefinitionDatasetFormatArgs>, val excludeFeaturesAttribute: Output<String>? = null, val localPath: Output<String>, val s3DataDistributionType: Output<DataQualityJobDefinitionBatchTransformInputS3DataDistributionType>? = null, val s3InputMode: Output<DataQualityJobDefinitionBatchTransformInputS3InputMode>? = null) : ConvertibleToJava<DataQualityJobDefinitionBatchTransformInputArgs>

The batch transform input for a monitoring job.

Constructors

fun DataQualityJobDefinitionBatchTransformInputArgs(dataCapturedDestinationS3Uri: Output<String>, datasetFormat: Output<DataQualityJobDefinitionDatasetFormatArgs>, excludeFeaturesAttribute: Output<String>? = null, localPath: Output<String>, s3DataDistributionType: Output<DataQualityJobDefinitionBatchTransformInputS3DataDistributionType>? = null, s3InputMode: Output<DataQualityJobDefinitionBatchTransformInputS3InputMode>? = null)

Functions

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open override fun toJava(): DataQualityJobDefinitionBatchTransformInputArgs

Properties

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val dataCapturedDestinationS3Uri: Output<String>

A URI that identifies the Amazon S3 storage location where Batch Transform Job captures data.

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val excludeFeaturesAttribute: Output<String>? = null

Indexes or names of the features to be excluded from analysis

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val localPath: Output<String>

Path to the filesystem where the endpoint data is available to the container.

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val s3DataDistributionType: Output<DataQualityJobDefinitionBatchTransformInputS3DataDistributionType>? = null

Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defauts to FullyReplicated

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val s3InputMode: Output<DataQualityJobDefinitionBatchTransformInputS3InputMode>? = null

Whether the Pipe or File is used as the input mode for transfering data for the monitoring job. Pipe mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.