createBatchPrediction method

Future<CreateBatchPredictionOutput> createBatchPrediction({ required String batchPredictionDataSourceId, required String batchPredictionId, required String mLModelId, required String outputUri, String? batchPredictionName, })

Generates predictions for a group of observations. The observations to process exist in one or more data files referenced by a DataSource. This operation creates a new BatchPrediction, and uses an MLModel and the data files referenced by the DataSource as information sources.

CreateBatchPrediction is an asynchronous operation. In response to CreateBatchPrediction, Amazon Machine Learning (Amazon ML) immediately returns and sets the BatchPrediction status to PENDING. After the BatchPrediction completes, Amazon ML sets the status to COMPLETED.

You can poll for status updates by using the GetBatchPrediction operation and checking the Status parameter of the result. After the COMPLETED status appears, the results are available in the location specified by the OutputUri parameter.

May throw InvalidInputException. May throw InternalServerException. May throw IdempotentParameterMismatchException.

Parameter batchPredictionDataSourceId : The ID of the DataSource that points to the group of observations to predict.

Parameter batchPredictionId : A user-supplied ID that uniquely identifies the BatchPrediction.

Parameter mLModelId : The ID of the MLModel that will generate predictions for the group of observations.

Parameter outputUri : The location of an Amazon Simple Storage Service (Amazon S3) bucket or directory to store the batch prediction results. The following substrings are not allowed in the s3 key portion of the outputURI field: ':', '//', '/./', '/../'.

Amazon ML needs permissions to store and retrieve the logs on your behalf. For information about how to set permissions, see the Amazon Machine Learning Developer Guide.

Parameter batchPredictionName : A user-supplied name or description of the BatchPrediction. BatchPredictionName can only use the UTF-8 character set.

Implementation

Future<CreateBatchPredictionOutput> createBatchPrediction({
  required String batchPredictionDataSourceId,
  required String batchPredictionId,
  required String mLModelId,
  required String outputUri,
  String? batchPredictionName,
}) async {
  ArgumentError.checkNotNull(
      batchPredictionDataSourceId, 'batchPredictionDataSourceId');
  _s.validateStringLength(
    'batchPredictionDataSourceId',
    batchPredictionDataSourceId,
    1,
    64,
    isRequired: true,
  );
  ArgumentError.checkNotNull(batchPredictionId, 'batchPredictionId');
  _s.validateStringLength(
    'batchPredictionId',
    batchPredictionId,
    1,
    64,
    isRequired: true,
  );
  ArgumentError.checkNotNull(mLModelId, 'mLModelId');
  _s.validateStringLength(
    'mLModelId',
    mLModelId,
    1,
    64,
    isRequired: true,
  );
  ArgumentError.checkNotNull(outputUri, 'outputUri');
  _s.validateStringLength(
    'outputUri',
    outputUri,
    0,
    2048,
    isRequired: true,
  );
  _s.validateStringLength(
    'batchPredictionName',
    batchPredictionName,
    0,
    1024,
  );
  final headers = <String, String>{
    'Content-Type': 'application/x-amz-json-1.1',
    'X-Amz-Target': 'AmazonML_20141212.CreateBatchPrediction'
  };
  final jsonResponse = await _protocol.send(
    method: 'POST',
    requestUri: '/',
    exceptionFnMap: _exceptionFns,
    // TODO queryParams
    headers: headers,
    payload: {
      'BatchPredictionDataSourceId': batchPredictionDataSourceId,
      'BatchPredictionId': batchPredictionId,
      'MLModelId': mLModelId,
      'OutputUri': outputUri,
      if (batchPredictionName != null)
        'BatchPredictionName': batchPredictionName,
    },
  );

  return CreateBatchPredictionOutput.fromJson(jsonResponse.body);
}