docs: improve bigquery_destination_prefix docstring (#1098)

Fixes b/186678558 🦕

Updated the `bigquery_destination_prefix` docstring in `models.py` and `jobs.py` to clarify that both a BQ project URI and full BQ table URI are acceptable inputs.

Author: sararob

google/cloud/aiplatform/jobs.py

@@ -431,24 +431,27 @@ def create(
                 which as value has ```google.rpc.Status`` <Status>`__
                 containing only ``code`` and ``message`` fields.
             bigquery_destination_prefix (Optional[str]):
-                The BigQuery project location where the output is to be
-                written to. In the given project a new dataset is created
-                with name
-                ``prediction_<model-display-name>_<job-create-time>`` where
-                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`` <Status>`__ represented as a STRUCT,
-                and containing only ``code`` and ``message``.
+                The BigQuery URI to a project or table, up to 2000 characters long.
+                When only the project is specified, the Dataset and Table is created.
+                When the full table reference is specified, the Dataset must exist and
+                table must not exist. Accepted forms: ``bq://projectId`` or
+                ``bq://projectId.bqDatasetId`` or
+                ``bq://projectId.bqDatasetId.bqTableId``. If no Dataset is specified,
+                a new one is created with the name
+                ``prediction_<model-display-name>_<job-create-time>``
+                where the table 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`` <Status>`__
+                represented as a STRUCT, and containing only ``code`` and ``message``.
             model_parameters (Optional[Dict]):
                 The parameters that govern the predictions. The schema of
                 the parameters may be specified via the Model's `parameters_schema_uri`.

google/cloud/aiplatform/models.py

@@ -2273,24 +2273,27 @@ def batch_predict(
                 which as value has ```google.rpc.Status`` <Status>`__
                 containing only ``code`` and ``message`` fields.
             bigquery_destination_prefix: Optional[str] = None
-                The BigQuery project location where the output is to be
-                written to. In the given project a new dataset is created
-                with name
-                ``prediction_<model-display-name>_<job-create-time>`` where
-                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`` <Status>`__ represented as a STRUCT,
-                and containing only ``code`` and ``message``.
+                The BigQuery URI to a project or table, up to 2000 characters long.
+                When only the project is specified, the Dataset and Table is created.
+                When the full table reference is specified, the Dataset must exist and
+                table must not exist. Accepted forms: ``bq://projectId`` or
+                ``bq://projectId.bqDatasetId`` or
+                ``bq://projectId.bqDatasetId.bqTableId``. If no Dataset is specified,
+                a new one is created with the name
+                ``prediction_<model-display-name>_<job-create-time>``
+                where the table 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`` <Status>`__
+                represented as a STRUCT, and containing only ``code`` and ``message``.
             predictions_format: str = "jsonl"
                 Required. The format in which Vertex AI outputs the
                 predictions, must be one of the formats specified in