Package com.google.cloud.aiplatform.v1

Class BatchPredictionJob.OutputConfig.Builder

java.lang.Object
com.google.protobuf.AbstractMessageLite.Builder
com.google.protobuf.AbstractMessage.Builder<BuilderT>
com.google.protobuf.GeneratedMessage.Builder<BatchPredictionJob.OutputConfig.Builder>
com.google.cloud.aiplatform.v1.BatchPredictionJob.OutputConfig.Builder
All Implemented Interfaces:
BatchPredictionJob.OutputConfigOrBuilder, com.google.protobuf.Message.Builder, com.google.protobuf.MessageLite.Builder, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, Cloneable
Enclosing class:
BatchPredictionJob.OutputConfig
public static final class BatchPredictionJob.OutputConfig.Builder extends com.google.protobuf.GeneratedMessage.Builder<BatchPredictionJob.OutputConfig.Builder> implements BatchPredictionJob.OutputConfigOrBuilder
 Configures the output of
 [BatchPredictionJob][google.cloud.aiplatform.v1.BatchPredictionJob]. See
 [Model.supported_output_storage_formats][google.cloud.aiplatform.v1.Model.supported_output_storage_formats]
 for supported output formats, and how predictions are expressed via any of
 them.
Protobuf type google.cloud.aiplatform.v1.BatchPredictionJob.OutputConfig

  • Method Details

    • getDescriptor

      public static final com.google.protobuf.Descriptors.Descriptor getDescriptor()

    • internalGetFieldAccessorTable

      protected com.google.protobuf.GeneratedMessage.FieldAccessorTable internalGetFieldAccessorTable()
      Specified by:
      internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessage.Builder<BatchPredictionJob.OutputConfig.Builder>

    • clear

      public BatchPredictionJob.OutputConfig.Builder clear()
      Specified by:
      clear in interface com.google.protobuf.Message.Builder
      Specified by:
      clear in interface com.google.protobuf.MessageLite.Builder
      Overrides:
      clear in class com.google.protobuf.GeneratedMessage.Builder<BatchPredictionJob.OutputConfig.Builder>

    • getDescriptorForType

      public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()
      Specified by:
      getDescriptorForType in interface com.google.protobuf.Message.Builder
      Specified by:
      getDescriptorForType in interface com.google.protobuf.MessageOrBuilder
      Overrides:
      getDescriptorForType in class com.google.protobuf.GeneratedMessage.Builder<BatchPredictionJob.OutputConfig.Builder>

    • getDefaultInstanceForType

      public BatchPredictionJob.OutputConfig getDefaultInstanceForType()
      Specified by:
      getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuilder
      Specified by:
      getDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilder

    • build

      public BatchPredictionJob.OutputConfig build()
      Specified by:
      build in interface com.google.protobuf.Message.Builder
      Specified by:
      build in interface com.google.protobuf.MessageLite.Builder

    • buildPartial

      public BatchPredictionJob.OutputConfig buildPartial()
      Specified by:
      buildPartial in interface com.google.protobuf.Message.Builder
      Specified by:
      buildPartial in interface com.google.protobuf.MessageLite.Builder

    • mergeFrom

      public BatchPredictionJob.OutputConfig.Builder mergeFrom(com.google.protobuf.Message other)
      Specified by:
      mergeFrom in interface com.google.protobuf.Message.Builder
      Overrides:
      mergeFrom in class com.google.protobuf.AbstractMessage.Builder<BatchPredictionJob.OutputConfig.Builder>

    • mergeFrom

      public BatchPredictionJob.OutputConfig.Builder mergeFrom(BatchPredictionJob.OutputConfig other)

    • isInitialized

      public final boolean isInitialized()
      Specified by:
      isInitialized in interface com.google.protobuf.MessageLiteOrBuilder
      Overrides:
      isInitialized in class com.google.protobuf.GeneratedMessage.Builder<BatchPredictionJob.OutputConfig.Builder>

    • mergeFrom

      public BatchPredictionJob.OutputConfig.Builder mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
      Specified by:
      mergeFrom in interface com.google.protobuf.Message.Builder
      Specified by:
      mergeFrom in interface com.google.protobuf.MessageLite.Builder
      Overrides:
      mergeFrom in class com.google.protobuf.AbstractMessage.Builder<BatchPredictionJob.OutputConfig.Builder>
      Throws:
      IOException

    • getDestinationCase

      public BatchPredictionJob.OutputConfig.DestinationCase getDestinationCase()
      Specified by:
      getDestinationCase in interface BatchPredictionJob.OutputConfigOrBuilder

    • clearDestination

      public BatchPredictionJob.OutputConfig.Builder clearDestination()

    • 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][google.cloud.aiplatform.v1.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.v1.PredictSchemata.instance_schema_uri]
 and
 [prediction][google.cloud.aiplatform.v1.PredictSchemata.parameters_schema_uri]
 schemata defined then each such file contains predictions as per the
 [predictions_format][google.cloud.aiplatform.v1.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.v1.GcsDestination gcs_destination = 2;
      Specified by:
      hasGcsDestination in interface BatchPredictionJob.OutputConfigOrBuilder
      Returns:
      Whether the gcsDestination field is set.

    • 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][google.cloud.aiplatform.v1.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.v1.PredictSchemata.instance_schema_uri]
 and
 [prediction][google.cloud.aiplatform.v1.PredictSchemata.parameters_schema_uri]
 schemata defined then each such file contains predictions as per the
 [predictions_format][google.cloud.aiplatform.v1.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.v1.GcsDestination gcs_destination = 2;
      Specified by:
      getGcsDestination in interface BatchPredictionJob.OutputConfigOrBuilder
      Returns:
      The gcsDestination.

    • setGcsDestination

      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][google.cloud.aiplatform.v1.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.v1.PredictSchemata.instance_schema_uri]
 and
 [prediction][google.cloud.aiplatform.v1.PredictSchemata.parameters_schema_uri]
 schemata defined then each such file contains predictions as per the
 [predictions_format][google.cloud.aiplatform.v1.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.v1.GcsDestination gcs_destination = 2;

    • setGcsDestination

      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][google.cloud.aiplatform.v1.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.v1.PredictSchemata.instance_schema_uri]
 and
 [prediction][google.cloud.aiplatform.v1.PredictSchemata.parameters_schema_uri]
 schemata defined then each such file contains predictions as per the
 [predictions_format][google.cloud.aiplatform.v1.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.v1.GcsDestination gcs_destination = 2;

    • mergeGcsDestination

      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][google.cloud.aiplatform.v1.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.v1.PredictSchemata.instance_schema_uri]
 and
 [prediction][google.cloud.aiplatform.v1.PredictSchemata.parameters_schema_uri]
 schemata defined then each such file contains predictions as per the
 [predictions_format][google.cloud.aiplatform.v1.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.v1.GcsDestination gcs_destination = 2;

    • 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][google.cloud.aiplatform.v1.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.v1.PredictSchemata.instance_schema_uri]
 and
 [prediction][google.cloud.aiplatform.v1.PredictSchemata.parameters_schema_uri]
 schemata defined then each such file contains predictions as per the
 [predictions_format][google.cloud.aiplatform.v1.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.v1.GcsDestination gcs_destination = 2;

    • 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][google.cloud.aiplatform.v1.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.v1.PredictSchemata.instance_schema_uri]
 and
 [prediction][google.cloud.aiplatform.v1.PredictSchemata.parameters_schema_uri]
 schemata defined then each such file contains predictions as per the
 [predictions_format][google.cloud.aiplatform.v1.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.v1.GcsDestination gcs_destination = 2;

    • 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][google.cloud.aiplatform.v1.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.v1.PredictSchemata.instance_schema_uri]
 and
 [prediction][google.cloud.aiplatform.v1.PredictSchemata.parameters_schema_uri]
 schemata defined then each such file contains predictions as per the
 [predictions_format][google.cloud.aiplatform.v1.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.v1.GcsDestination gcs_destination = 2;
      Specified by:
      getGcsDestinationOrBuilder in interface BatchPredictionJob.OutputConfigOrBuilder

    • 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][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri]
 and
 [prediction][google.cloud.aiplatform.v1.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.v1.BigQueryDestination bigquery_destination = 3;
      Specified by:
      hasBigqueryDestination in interface BatchPredictionJob.OutputConfigOrBuilder
      Returns:
      Whether the bigqueryDestination field is set.

    • 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][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri]
 and
 [prediction][google.cloud.aiplatform.v1.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.v1.BigQueryDestination bigquery_destination = 3;
      Specified by:
      getBigqueryDestination in interface BatchPredictionJob.OutputConfigOrBuilder
      Returns:
      The bigqueryDestination.

    • setBigqueryDestination

      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][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri]
 and
 [prediction][google.cloud.aiplatform.v1.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.v1.BigQueryDestination bigquery_destination = 3;

    • setBigqueryDestination

      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][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri]
 and
 [prediction][google.cloud.aiplatform.v1.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.v1.BigQueryDestination bigquery_destination = 3;

    • mergeBigqueryDestination

      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][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri]
 and
 [prediction][google.cloud.aiplatform.v1.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.v1.BigQueryDestination bigquery_destination = 3;

    • 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][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri]
 and
 [prediction][google.cloud.aiplatform.v1.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.v1.BigQueryDestination bigquery_destination = 3;

    • 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][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri]
 and
 [prediction][google.cloud.aiplatform.v1.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.v1.BigQueryDestination bigquery_destination = 3;

    • 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][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri]
 and
 [prediction][google.cloud.aiplatform.v1.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.v1.BigQueryDestination bigquery_destination = 3;
      Specified by:
      getBigqueryDestinationOrBuilder in interface BatchPredictionJob.OutputConfigOrBuilder

    • hasVertexMultimodalDatasetDestination

      public boolean hasVertexMultimodalDatasetDestination()
       The details for a Vertex Multimodal Dataset that will be created for
 the output.
      .google.cloud.aiplatform.v1.VertexMultimodalDatasetDestination vertex_multimodal_dataset_destination = 6;
      Specified by:
      hasVertexMultimodalDatasetDestination in interface BatchPredictionJob.OutputConfigOrBuilder
      Returns:
      Whether the vertexMultimodalDatasetDestination field is set.

    • getVertexMultimodalDatasetDestination

      public VertexMultimodalDatasetDestination getVertexMultimodalDatasetDestination()
       The details for a Vertex Multimodal Dataset that will be created for
 the output.
      .google.cloud.aiplatform.v1.VertexMultimodalDatasetDestination vertex_multimodal_dataset_destination = 6;
      Specified by:
      getVertexMultimodalDatasetDestination in interface BatchPredictionJob.OutputConfigOrBuilder
      Returns:
      The vertexMultimodalDatasetDestination.

    • setVertexMultimodalDatasetDestination

      public BatchPredictionJob.OutputConfig.Builder setVertexMultimodalDatasetDestination(VertexMultimodalDatasetDestination value)
       The details for a Vertex Multimodal Dataset that will be created for
 the output.
      .google.cloud.aiplatform.v1.VertexMultimodalDatasetDestination vertex_multimodal_dataset_destination = 6;

    • setVertexMultimodalDatasetDestination

      public BatchPredictionJob.OutputConfig.Builder setVertexMultimodalDatasetDestination(VertexMultimodalDatasetDestination.Builder builderForValue)
       The details for a Vertex Multimodal Dataset that will be created for
 the output.
      .google.cloud.aiplatform.v1.VertexMultimodalDatasetDestination vertex_multimodal_dataset_destination = 6;

    • mergeVertexMultimodalDatasetDestination

      public BatchPredictionJob.OutputConfig.Builder mergeVertexMultimodalDatasetDestination(VertexMultimodalDatasetDestination value)
       The details for a Vertex Multimodal Dataset that will be created for
 the output.
      .google.cloud.aiplatform.v1.VertexMultimodalDatasetDestination vertex_multimodal_dataset_destination = 6;

    • clearVertexMultimodalDatasetDestination

      public BatchPredictionJob.OutputConfig.Builder clearVertexMultimodalDatasetDestination()
       The details for a Vertex Multimodal Dataset that will be created for
 the output.
      .google.cloud.aiplatform.v1.VertexMultimodalDatasetDestination vertex_multimodal_dataset_destination = 6;

    • getVertexMultimodalDatasetDestinationBuilder

      public VertexMultimodalDatasetDestination.Builder getVertexMultimodalDatasetDestinationBuilder()
       The details for a Vertex Multimodal Dataset that will be created for
 the output.
      .google.cloud.aiplatform.v1.VertexMultimodalDatasetDestination vertex_multimodal_dataset_destination = 6;

    • getVertexMultimodalDatasetDestinationOrBuilder

      public VertexMultimodalDatasetDestinationOrBuilder getVertexMultimodalDatasetDestinationOrBuilder()
       The details for a Vertex Multimodal Dataset that will be created for
 the output.
      .google.cloud.aiplatform.v1.VertexMultimodalDatasetDestination vertex_multimodal_dataset_destination = 6;
      Specified by:
      getVertexMultimodalDatasetDestinationOrBuilder in interface BatchPredictionJob.OutputConfigOrBuilder

    • getPredictionsFormat

      public String getPredictionsFormat()
       Required. The format in which Vertex AI gives the predictions, must be
 one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
 [supported_output_storage_formats][google.cloud.aiplatform.v1.Model.supported_output_storage_formats].
      string predictions_format = 1 [(.google.api.field_behavior) = REQUIRED];
      Specified by:
      getPredictionsFormat in interface BatchPredictionJob.OutputConfigOrBuilder
      Returns:
      The predictionsFormat.

    • getPredictionsFormatBytes

      public 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.v1.BatchPredictionJob.model]
 [supported_output_storage_formats][google.cloud.aiplatform.v1.Model.supported_output_storage_formats].
      string predictions_format = 1 [(.google.api.field_behavior) = REQUIRED];
      Specified by:
      getPredictionsFormatBytes in interface BatchPredictionJob.OutputConfigOrBuilder
      Returns:
      The bytes for predictionsFormat.

    • setPredictionsFormat

      public BatchPredictionJob.OutputConfig.Builder setPredictionsFormat(String value)
       Required. The format in which Vertex AI gives the predictions, must be
 one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
 [supported_output_storage_formats][google.cloud.aiplatform.v1.Model.supported_output_storage_formats].
      string predictions_format = 1 [(.google.api.field_behavior) = REQUIRED];
      Parameters:
      value - The predictionsFormat to set.
      Returns:
      This builder for chaining.

    • clearPredictionsFormat

      public BatchPredictionJob.OutputConfig.Builder clearPredictionsFormat()
       Required. The format in which Vertex AI gives the predictions, must be
 one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
 [supported_output_storage_formats][google.cloud.aiplatform.v1.Model.supported_output_storage_formats].
      string predictions_format = 1 [(.google.api.field_behavior) = REQUIRED];
      Returns:
      This builder for chaining.

    • setPredictionsFormatBytes

      public BatchPredictionJob.OutputConfig.Builder setPredictionsFormatBytes(com.google.protobuf.ByteString value)
       Required. The format in which Vertex AI gives the predictions, must be
 one of the [Model's][google.cloud.aiplatform.v1.BatchPredictionJob.model]
 [supported_output_storage_formats][google.cloud.aiplatform.v1.Model.supported_output_storage_formats].
      string predictions_format = 1 [(.google.api.field_behavior) = REQUIRED];
      Parameters:
      value - The bytes for predictionsFormat to set.
      Returns:
      This builder for chaining.