com.google.cloud.aiplatform.v1beta1

Interface BatchPredictionJob.OutputConfigOrBuilder

All Superinterfaces:

com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder

All Known Implementing Classes:

BatchPredictionJob.OutputConfig, BatchPredictionJob.OutputConfig.Builder

Enclosing class:

BatchPredictionJob

public static interface BatchPredictionJob.OutputConfigOrBuilder
extends com.google.protobuf.MessageOrBuilder

Method Summary

Modifier and Type	Method and Description
BigQueryDestination	getBigqueryDestination() The BigQuery project or dataset location where the output is to be written to.
BigQueryDestinationOrBuilder	getBigqueryDestinationOrBuilder() The BigQuery project or dataset location where the output is to be written to.
BatchPredictionJob.OutputConfig.DestinationCase	getDestinationCase()
GcsDestination	getGcsDestination() The Cloud Storage location of the directory where the output is to be written to.
GcsDestinationOrBuilder	getGcsDestinationOrBuilder() The Cloud Storage location of the directory where the output is to be written to.
String	getPredictionsFormat() Required.
com.google.protobuf.ByteString	getPredictionsFormatBytes() Required.
boolean	hasBigqueryDestination() The BigQuery project or dataset location where the output is to be written to.
boolean	hasGcsDestination() The Cloud Storage location of the directory where the output is to be written to.

Methods inherited from interface com.google.protobuf.MessageOrBuilder

findInitializationErrors, getAllFields, getDefaultInstanceForType, getDescriptorForType, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof

Methods inherited from interface com.google.protobuf.MessageLiteOrBuilder

isInitialized

Method Detail

hasGcsDestination

boolean hasGcsDestination()

 The Cloud Storage location of the directory where the output is
 to be written to. In the given directory a new directory is created.
 Its name is `prediction-<model-display-name>-<job-create-time>`,
 where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format.
 Inside of it files `predictions_0001.<extension>`,
 `predictions_0002.<extension>`, ..., `predictions_N.<extension>`
 are created where `<extension>` depends on chosen
 [predictions_format][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.predictions_format],
 and N may equal 0001 and depends on the total number of successfully
 predicted instances. If the Model has both
 [instance][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri]
 and
 [prediction][google.cloud.aiplatform.v1beta1.PredictSchemata.parameters_schema_uri]
 schemata defined then each such file contains predictions as per the
 [predictions_format][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.predictions_format].
 If prediction for any instance failed (partially or completely), then
 an additional `errors_0001.<extension>`, `errors_0002.<extension>`,...,
 `errors_N.<extension>` files are created (N depends on total number
 of failed predictions). These files contain the failed instances,
 as per their schema, followed by an additional `error` field which as
 value has [google.rpc.Status][google.rpc.Status]
 containing only `code` and `message` fields.
 

.google.cloud.aiplatform.v1beta1.GcsDestination gcs_destination = 2;

Returns:

Whether the gcsDestination field is set.

getGcsDestination

GcsDestination getGcsDestination()

 The Cloud Storage location of the directory where the output is
 to be written to. In the given directory a new directory is created.
 Its name is `prediction-<model-display-name>-<job-create-time>`,
 where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format.
 Inside of it files `predictions_0001.<extension>`,
 `predictions_0002.<extension>`, ..., `predictions_N.<extension>`
 are created where `<extension>` depends on chosen
 [predictions_format][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.predictions_format],
 and N may equal 0001 and depends on the total number of successfully
 predicted instances. If the Model has both
 [instance][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri]
 and
 [prediction][google.cloud.aiplatform.v1beta1.PredictSchemata.parameters_schema_uri]
 schemata defined then each such file contains predictions as per the
 [predictions_format][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.predictions_format].
 If prediction for any instance failed (partially or completely), then
 an additional `errors_0001.<extension>`, `errors_0002.<extension>`,...,
 `errors_N.<extension>` files are created (N depends on total number
 of failed predictions). These files contain the failed instances,
 as per their schema, followed by an additional `error` field which as
 value has [google.rpc.Status][google.rpc.Status]
 containing only `code` and `message` fields.
 

.google.cloud.aiplatform.v1beta1.GcsDestination gcs_destination = 2;

Returns:

The gcsDestination.

getGcsDestinationOrBuilder

GcsDestinationOrBuilder getGcsDestinationOrBuilder()

 The Cloud Storage location of the directory where the output is
 to be written to. In the given directory a new directory is created.
 Its name is `prediction-<model-display-name>-<job-create-time>`,
 where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format.
 Inside of it files `predictions_0001.<extension>`,
 `predictions_0002.<extension>`, ..., `predictions_N.<extension>`
 are created where `<extension>` depends on chosen
 [predictions_format][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.predictions_format],
 and N may equal 0001 and depends on the total number of successfully
 predicted instances. If the Model has both
 [instance][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri]
 and
 [prediction][google.cloud.aiplatform.v1beta1.PredictSchemata.parameters_schema_uri]
 schemata defined then each such file contains predictions as per the
 [predictions_format][google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig.predictions_format].
 If prediction for any instance failed (partially or completely), then
 an additional `errors_0001.<extension>`, `errors_0002.<extension>`,...,
 `errors_N.<extension>` files are created (N depends on total number
 of failed predictions). These files contain the failed instances,
 as per their schema, followed by an additional `error` field which as
 value has [google.rpc.Status][google.rpc.Status]
 containing only `code` and `message` fields.
 

.google.cloud.aiplatform.v1beta1.GcsDestination gcs_destination = 2;

hasBigqueryDestination

boolean hasBigqueryDestination()

 The BigQuery project or dataset location where the output is to be
 written to. If project is provided, a new dataset is created with name
 `prediction_<model-display-name>_<job-create-time>`
 where <model-display-name> is made
 BigQuery-dataset-name compatible (for example, most special characters
 become underscores), and timestamp is in
 YYYY_MM_DDThh_mm_ss_sssZ "based on ISO-8601" format. In the dataset
 two tables will be created, `predictions`, and `errors`.
 If the Model has both
 [instance][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri]
 and
 [prediction][google.cloud.aiplatform.v1beta1.PredictSchemata.parameters_schema_uri]
 schemata defined then the tables have columns as follows: The
 `predictions` table contains instances for which the prediction
 succeeded, it has columns as per a concatenation of the Model's
 instance and prediction schemata. The `errors` table contains rows for
 which the prediction has failed, it has instance columns, as per the
 instance schema, followed by a single "errors" column, which as values
 has [google.rpc.Status][google.rpc.Status]
 represented as a STRUCT, and containing only `code` and `message`.
 

.google.cloud.aiplatform.v1beta1.BigQueryDestination bigquery_destination = 3;

Returns:

Whether the bigqueryDestination field is set.

getBigqueryDestination

BigQueryDestination getBigqueryDestination()

 The BigQuery project or dataset location where the output is to be
 written to. If project is provided, a new dataset is created with name
 `prediction_<model-display-name>_<job-create-time>`
 where <model-display-name> is made
 BigQuery-dataset-name compatible (for example, most special characters
 become underscores), and timestamp is in
 YYYY_MM_DDThh_mm_ss_sssZ "based on ISO-8601" format. In the dataset
 two tables will be created, `predictions`, and `errors`.
 If the Model has both
 [instance][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri]
 and
 [prediction][google.cloud.aiplatform.v1beta1.PredictSchemata.parameters_schema_uri]
 schemata defined then the tables have columns as follows: The
 `predictions` table contains instances for which the prediction
 succeeded, it has columns as per a concatenation of the Model's
 instance and prediction schemata. The `errors` table contains rows for
 which the prediction has failed, it has instance columns, as per the
 instance schema, followed by a single "errors" column, which as values
 has [google.rpc.Status][google.rpc.Status]
 represented as a STRUCT, and containing only `code` and `message`.
 

.google.cloud.aiplatform.v1beta1.BigQueryDestination bigquery_destination = 3;

Returns:

The bigqueryDestination.

getBigqueryDestinationOrBuilder

BigQueryDestinationOrBuilder getBigqueryDestinationOrBuilder()

 The BigQuery project or dataset location where the output is to be
 written to. If project is provided, a new dataset is created with name
 `prediction_<model-display-name>_<job-create-time>`
 where <model-display-name> is made
 BigQuery-dataset-name compatible (for example, most special characters
 become underscores), and timestamp is in
 YYYY_MM_DDThh_mm_ss_sssZ "based on ISO-8601" format. In the dataset
 two tables will be created, `predictions`, and `errors`.
 If the Model has both
 [instance][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri]
 and
 [prediction][google.cloud.aiplatform.v1beta1.PredictSchemata.parameters_schema_uri]
 schemata defined then the tables have columns as follows: The
 `predictions` table contains instances for which the prediction
 succeeded, it has columns as per a concatenation of the Model's
 instance and prediction schemata. The `errors` table contains rows for
 which the prediction has failed, it has instance columns, as per the
 instance schema, followed by a single "errors" column, which as values
 has [google.rpc.Status][google.rpc.Status]
 represented as a STRUCT, and containing only `code` and `message`.
 

.google.cloud.aiplatform.v1beta1.BigQueryDestination bigquery_destination = 3;

getPredictionsFormat

String getPredictionsFormat()

 Required. The format in which Vertex AI gives the predictions, must be
 one of the
 [Model's][google.cloud.aiplatform.v1beta1.BatchPredictionJob.model]
 [supported_output_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_output_storage_formats].
 

string predictions_format = 1 [(.google.api.field_behavior) = REQUIRED];

Returns:

The predictionsFormat.

getPredictionsFormatBytes

com.google.protobuf.ByteString getPredictionsFormatBytes()

 Required. The format in which Vertex AI gives the predictions, must be
 one of the
 [Model's][google.cloud.aiplatform.v1beta1.BatchPredictionJob.model]
 [supported_output_storage_formats][google.cloud.aiplatform.v1beta1.Model.supported_output_storage_formats].
 

string predictions_format = 1 [(.google.api.field_behavior) = REQUIRED];

Returns:

The bytes for predictionsFormat.

getDestinationCase

BatchPredictionJob.OutputConfig.DestinationCase getDestinationCase()