Package com.google.cloud.aiplatform.v1beta1

Class 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.GeneratedMessageV3.Builder<BatchPredictionJob.OutputConfig.Builder>
implements BatchPredictionJob.OutputConfigOrBuilder
     Configures the output of
 [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob].
 See
 [Model.supported_output_storage_formats][google.cloud.aiplatform.v1beta1.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

    • Method Detail

      • getDescriptor

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

      • internalGetFieldAccessorTable

        protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
        Specified by:
        internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessageV3.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.GeneratedMessageV3.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

      • isInitialized

        public final boolean isInitialized()
        Specified by:
        isInitialized in interface com.google.protobuf.MessageLiteOrBuilder
        Overrides:
        isInitialized in class com.google.protobuf.GeneratedMessageV3.Builder<BatchPredictionJob.OutputConfig.Builder>

      • 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.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;
        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.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;
        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.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;

      • 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.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;

      • 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.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;

      • 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.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;

      • 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.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;

      • 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.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;
        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.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;
        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.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;
        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.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;

      • 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.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;

      • 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.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;

      • 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.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;

      • 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.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;

      • 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.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;
        Specified by:
        getBigqueryDestinationOrBuilder 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.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];
        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.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];
        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.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];
        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.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:
        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.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];
        Parameters:
        value - The bytes for predictionsFormat to set.
        Returns:
        This builder for chaining.