Class BatchPredictionJob.OutputConfig.Builder (3.3.0)

public static final class BatchPredictionJob.OutputConfig.Builder extends GeneratedMessageV3.Builder<BatchPredictionJob.OutputConfig.Builder> implements BatchPredictionJob.OutputConfigOrBuilder

Configures the output of BatchPredictionJob. See Model.supported_output_storage_formats for supported output formats, and how predictions are expressed via any of them.

Protobuf type google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig

Static Methods

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()
Returns
TypeDescription
Descriptor

Methods

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

public BatchPredictionJob.OutputConfig.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
Parameters
NameDescription
fieldFieldDescriptor
valueObject
Returns
TypeDescription
BatchPredictionJob.OutputConfig.Builder
Overrides

build()

public BatchPredictionJob.OutputConfig build()
Returns
TypeDescription
BatchPredictionJob.OutputConfig

buildPartial()

public BatchPredictionJob.OutputConfig buildPartial()
Returns
TypeDescription
BatchPredictionJob.OutputConfig

clear()

public BatchPredictionJob.OutputConfig.Builder clear()
Returns
TypeDescription
BatchPredictionJob.OutputConfig.Builder
Overrides

clearBigqueryDestination()

public BatchPredictionJob.OutputConfig.Builder clearBigqueryDestination()

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 and prediction 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 represented as a STRUCT, and containing only code and message.

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

Returns
TypeDescription
BatchPredictionJob.OutputConfig.Builder

clearDestination()

public BatchPredictionJob.OutputConfig.Builder clearDestination()
Returns
TypeDescription
BatchPredictionJob.OutputConfig.Builder

clearField(Descriptors.FieldDescriptor field)

public BatchPredictionJob.OutputConfig.Builder clearField(Descriptors.FieldDescriptor field)
Parameter
NameDescription
fieldFieldDescriptor
Returns
TypeDescription
BatchPredictionJob.OutputConfig.Builder
Overrides

clearGcsDestination()

public BatchPredictionJob.OutputConfig.Builder clearGcsDestination()

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, and N may equal 0001 and depends on the total number of successfully predicted instances. If the Model has both instance and prediction schemata defined then each such file contains predictions as per the 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 containing only code and message fields.

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

Returns
TypeDescription
BatchPredictionJob.OutputConfig.Builder

clearOneof(Descriptors.OneofDescriptor oneof)

public BatchPredictionJob.OutputConfig.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Parameter
NameDescription
oneofOneofDescriptor
Returns
TypeDescription
BatchPredictionJob.OutputConfig.Builder
Overrides

clearPredictionsFormat()

public BatchPredictionJob.OutputConfig.Builder clearPredictionsFormat()

Required. The format in which Vertex AI gives the predictions, must be one of the Model's supported_output_storage_formats.

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

Returns
TypeDescription
BatchPredictionJob.OutputConfig.Builder

This builder for chaining.

clone()

public BatchPredictionJob.OutputConfig.Builder clone()
Returns
TypeDescription
BatchPredictionJob.OutputConfig.Builder
Overrides

getBigqueryDestination()

public 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 and prediction 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 represented as a STRUCT, and containing only code and message.

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

Returns
TypeDescription
BigQueryDestination

The bigqueryDestination.

getBigqueryDestinationBuilder()

public BigQueryDestination.Builder getBigqueryDestinationBuilder()

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 and prediction 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 represented as a STRUCT, and containing only code and message.

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

Returns
TypeDescription
BigQueryDestination.Builder

getBigqueryDestinationOrBuilder()

public 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 and prediction 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 represented as a STRUCT, and containing only code and message.

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

Returns
TypeDescription
BigQueryDestinationOrBuilder

getDefaultInstanceForType()

public BatchPredictionJob.OutputConfig getDefaultInstanceForType()
Returns
TypeDescription
BatchPredictionJob.OutputConfig

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()
Returns
TypeDescription
Descriptor
Overrides

getDestinationCase()

public BatchPredictionJob.OutputConfig.DestinationCase getDestinationCase()
Returns
TypeDescription
BatchPredictionJob.OutputConfig.DestinationCase

getGcsDestination()

public 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, and N may equal 0001 and depends on the total number of successfully predicted instances. If the Model has both instance and prediction schemata defined then each such file contains predictions as per the 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 containing only code and message fields.

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

Returns
TypeDescription
GcsDestination

The gcsDestination.

getGcsDestinationBuilder()

public GcsDestination.Builder getGcsDestinationBuilder()

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, and N may equal 0001 and depends on the total number of successfully predicted instances. If the Model has both instance and prediction schemata defined then each such file contains predictions as per the 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 containing only code and message fields.

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

Returns
TypeDescription
GcsDestination.Builder

getGcsDestinationOrBuilder()

public 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, and N may equal 0001 and depends on the total number of successfully predicted instances. If the Model has both instance and prediction schemata defined then each such file contains predictions as per the 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 containing only code and message fields.

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

Returns
TypeDescription
GcsDestinationOrBuilder

getPredictionsFormat()

public String getPredictionsFormat()

Required. The format in which Vertex AI gives the predictions, must be one of the Model's supported_output_storage_formats.

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

Returns
TypeDescription
String

The predictionsFormat.

getPredictionsFormatBytes()

public ByteString getPredictionsFormatBytes()

Required. The format in which Vertex AI gives the predictions, must be one of the Model's supported_output_storage_formats.

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

Returns
TypeDescription
ByteString

The bytes for predictionsFormat.

hasBigqueryDestination()

public 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 and prediction 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 represented as a STRUCT, and containing only code and message.

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

Returns
TypeDescription
boolean

Whether the bigqueryDestination field is set.

hasGcsDestination()

public 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, and N may equal 0001 and depends on the total number of successfully predicted instances. If the Model has both instance and prediction schemata defined then each such file contains predictions as per the 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 containing only code and message fields.

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

Returns
TypeDescription
boolean

Whether the gcsDestination field is set.

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
TypeDescription
FieldAccessorTable
Overrides

isInitialized()

public final boolean isInitialized()
Returns
TypeDescription
boolean
Overrides

mergeBigqueryDestination(BigQueryDestination value)

public BatchPredictionJob.OutputConfig.Builder mergeBigqueryDestination(BigQueryDestination value)

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 and prediction 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 represented as a STRUCT, and containing only code and message.

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

Parameter
NameDescription
valueBigQueryDestination
Returns
TypeDescription
BatchPredictionJob.OutputConfig.Builder

mergeFrom(BatchPredictionJob.OutputConfig other)

public BatchPredictionJob.OutputConfig.Builder mergeFrom(BatchPredictionJob.OutputConfig other)
Parameter
NameDescription
otherBatchPredictionJob.OutputConfig
Returns
TypeDescription
BatchPredictionJob.OutputConfig.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public BatchPredictionJob.OutputConfig.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
inputCodedInputStream
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
BatchPredictionJob.OutputConfig.Builder
Overrides Exceptions
TypeDescription
IOException

mergeFrom(Message other)

public BatchPredictionJob.OutputConfig.Builder mergeFrom(Message other)
Parameter
NameDescription
otherMessage
Returns
TypeDescription
BatchPredictionJob.OutputConfig.Builder
Overrides

mergeGcsDestination(GcsDestination value)

public BatchPredictionJob.OutputConfig.Builder mergeGcsDestination(GcsDestination value)

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, and N may equal 0001 and depends on the total number of successfully predicted instances. If the Model has both instance and prediction schemata defined then each such file contains predictions as per the 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 containing only code and message fields.

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

Parameter
NameDescription
valueGcsDestination
Returns
TypeDescription
BatchPredictionJob.OutputConfig.Builder

mergeUnknownFields(UnknownFieldSet unknownFields)

public final BatchPredictionJob.OutputConfig.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Parameter
NameDescription
unknownFieldsUnknownFieldSet
Returns
TypeDescription
BatchPredictionJob.OutputConfig.Builder
Overrides

setBigqueryDestination(BigQueryDestination value)

public BatchPredictionJob.OutputConfig.Builder setBigqueryDestination(BigQueryDestination value)

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 and prediction 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 represented as a STRUCT, and containing only code and message.

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

Parameter
NameDescription
valueBigQueryDestination
Returns
TypeDescription
BatchPredictionJob.OutputConfig.Builder

setBigqueryDestination(BigQueryDestination.Builder builderForValue)

public BatchPredictionJob.OutputConfig.Builder setBigqueryDestination(BigQueryDestination.Builder builderForValue)

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 and prediction 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 represented as a STRUCT, and containing only code and message.

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

Parameter
NameDescription
builderForValueBigQueryDestination.Builder
Returns
TypeDescription
BatchPredictionJob.OutputConfig.Builder

setField(Descriptors.FieldDescriptor field, Object value)

public BatchPredictionJob.OutputConfig.Builder setField(Descriptors.FieldDescriptor field, Object value)
Parameters
NameDescription
fieldFieldDescriptor
valueObject
Returns
TypeDescription
BatchPredictionJob.OutputConfig.Builder
Overrides

setGcsDestination(GcsDestination value)

public BatchPredictionJob.OutputConfig.Builder setGcsDestination(GcsDestination value)

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, and N may equal 0001 and depends on the total number of successfully predicted instances. If the Model has both instance and prediction schemata defined then each such file contains predictions as per the 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 containing only code and message fields.

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

Parameter
NameDescription
valueGcsDestination
Returns
TypeDescription
BatchPredictionJob.OutputConfig.Builder

setGcsDestination(GcsDestination.Builder builderForValue)

public BatchPredictionJob.OutputConfig.Builder setGcsDestination(GcsDestination.Builder builderForValue)

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, and N may equal 0001 and depends on the total number of successfully predicted instances. If the Model has both instance and prediction schemata defined then each such file contains predictions as per the 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 containing only code and message fields.

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

Parameter
NameDescription
builderForValueGcsDestination.Builder
Returns
TypeDescription
BatchPredictionJob.OutputConfig.Builder

setPredictionsFormat(String value)

public BatchPredictionJob.OutputConfig.Builder setPredictionsFormat(String value)

Required. The format in which Vertex AI gives the predictions, must be one of the Model's supported_output_storage_formats.

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

Parameter
NameDescription
valueString

The predictionsFormat to set.

Returns
TypeDescription
BatchPredictionJob.OutputConfig.Builder

This builder for chaining.

setPredictionsFormatBytes(ByteString value)

public BatchPredictionJob.OutputConfig.Builder setPredictionsFormatBytes(ByteString value)

Required. The format in which Vertex AI gives the predictions, must be one of the Model's supported_output_storage_formats.

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

Parameter
NameDescription
valueByteString

The bytes for predictionsFormat to set.

Returns
TypeDescription
BatchPredictionJob.OutputConfig.Builder

This builder for chaining.

setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

public BatchPredictionJob.OutputConfig.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
Parameters
NameDescription
fieldFieldDescriptor
indexint
valueObject
Returns
TypeDescription
BatchPredictionJob.OutputConfig.Builder
Overrides

setUnknownFields(UnknownFieldSet unknownFields)

public final BatchPredictionJob.OutputConfig.Builder setUnknownFields(UnknownFieldSet unknownFields)
Parameter
NameDescription
unknownFieldsUnknownFieldSet
Returns
TypeDescription
BatchPredictionJob.OutputConfig.Builder
Overrides