feat(bigquery): add bigquery_vector_search sample to run approximate …

bigquery/vector_search/bigquery_vector_search.py

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+# Copyright 2026 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# [START bigquery_vector_search]
+import sys
+
+from google.api_core import exceptions
+from google.cloud import bigquery
+
+
+def vector_search(
+    project_id: str,
+    dataset_id: str,
+    table_id: str,
+) -> None:
+    """Runs an indexed vector similarity search using a parameterized embedding array.
+
+    Args:
+        project_id: Google Cloud project ID (for example, 'example-project').
+        dataset_id: BigQuery dataset ID containing the embeddings table
+            (for example, 'example_dataset').
+        table_id: BigQuery table ID containing the indexed embedding column
+            (for example, 'example_embeddings').
+    """
+    client = bigquery.Client(project=project_id)
+    table_ref = f"{project_id}.{dataset_id}.{table_id}"
+    # Pass the query embedding via ArrayQueryParameter and specify fraction_lists_to_search
+    # to control the recall-latency tradeoff across indexed inverted lists.
+    query_embedding = [1.0, 0.5, 0.25, 0.125]
+    job_config = bigquery.QueryJobConfig(
+        query_parameters=[
+            bigquery.ArrayQueryParameter("query_embedding", "FLOAT64", query_embedding),
+        ]
+    )
+    sql = f"""
+        SELECT
+          base.id AS matched_id,
+          distance
+        FROM VECTOR_SEARCH(
+          TABLE `{table_ref}`,
+          'embedding',
+          (SELECT @query_embedding AS query_embedding),
+          query_column_to_search => 'query_embedding',
+          top_k => 3,
+          distance_type => 'COSINE',
+          options => '{{"fraction_lists_to_search": 0.05}}'
+        )
+        ORDER BY distance ASC, matched_id ASC;
+    """
+
+    try:
+        print(f"Running indexed vector similarity search on table: {table_ref}")
+        query_job = client.query(sql, job_config=job_config)
+        rows = list(query_job.result())
+    except exceptions.NotFound as err:
+        print(
+            f"error: embeddings table '{table_id}' not found in dataset '{dataset_id}' "
+            f"for project '{project_id}': {err.message}",
+            file=sys.stderr,
+        )
+        return
+    except exceptions.GoogleAPICallError as err:
+        print(
+            f"error: failed to run vector search on table '{table_id}' in dataset "
+            f"'{dataset_id}' for project '{project_id}': {err.message}",
+            file=sys.stderr,
+        )
+        return
+
+    print(f"Resource ID: {table_ref}")
+    print("Distance Type: COSINE")
+    print(f"Embedding Dimensions: {len(query_embedding)}")
+    print(f"Job ID: {query_job.job_id}")
+    print(f"Neighbors Returned: {len(rows)}")
+
+
+# [END bigquery_vector_search]

bigquery/vector_search/bigquery_vector_search_test.py

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+# Copyright 2026 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from unittest import mock
+
+import bigquery_vector_search
+from google.api_core import exceptions
+import pytest
+
+
+def test_vector_search_success(
+    capsys: pytest.CaptureFixture[str],
+) -> None:
+    with mock.patch("google.cloud.bigquery.Client") as mock_client_cls:
+        mock_client = mock_client_cls.return_value
+        mock_job = mock.MagicMock()
+        mock_job.job_id = "example-job-123"
+        mock_job.result.return_value = [
+            mock.MagicMock(),
+            mock.MagicMock(),
+            mock.MagicMock(),
+        ]
+        mock_client.query.return_value = mock_job
+
+        bigquery_vector_search.vector_search(
+            project_id="example-project",
+            dataset_id="example_dataset",
+            table_id="example_embeddings",
+        )
+
+        mock_client.query.assert_called_once()
+        sql_called = mock_client.query.call_args[0][0]
+        assert "fraction_lists_to_search" in sql_called
+        captured = capsys.readouterr()
+        assert (
+            "Resource ID: example-project.example_dataset.example_embeddings"
+            in captured.out
+        )
+        assert "Embedding Dimensions: 4" in captured.out
+        assert "Neighbors Returned: 3" in captured.out
+
+
+def test_vector_search_not_found(
+    capsys: pytest.CaptureFixture[str],
+) -> None:
+    with mock.patch("google.cloud.bigquery.Client") as mock_client_cls:
+        mock_client = mock_client_cls.return_value
+        mock_job = mock.MagicMock()
+        mock_job.result.side_effect = exceptions.NotFound("Table not found")
+        mock_client.query.return_value = mock_job
+
+        bigquery_vector_search.vector_search(
+            project_id="example-project",
+            dataset_id="example_dataset",
+            table_id="example_embeddings",
+        )
+
+        captured = capsys.readouterr()
+        assert "error:" in captured.err
+        assert "example_embeddings" in captured.err

bigquery/vector_search/noxfile_config.py

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+# Copyright 2026 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+TEST_CONFIG_OVERRIDE = {
+    # You can opt out from the test for specific Python versions.
+    "ignored_versions": ["2.7", "3.7", "3.8", "3.9", "3.10", "3.11"],
+    # Enforce type hints on new samples.
+    "enforce_type_hints": True,
+    "gcloud_project_env": "GOOGLE_CLOUD_PROJECT",
+    "pip_version_override": None,
+    "envs": {},
+}

bigquery/vector_search/requirements-test.txt

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+pytest==9.0.3; python_version >= "3.10"

bigquery/vector_search/requirements.txt

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+google-cloud-bigquery==3.47.0