googleapis · alextolpin · Aug 16, 2026 · Aug 16, 2026 · gemini-code-assist · Aug 16, 2026
@@ -0,0 +1,58 @@
+# 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 bigquerystorage_query_and_wait_arrow]
+from typing import Iterable, Optional
+
+from google.cloud import bigquery
+from google.cloud.bigquery import enums
+import pyarrow
+
+
+def query_and_wait_arrow(
+    project_id: Optional[str] = None,
+) -> Iterable[pyarrow.RecordBatch]:
+    """Queries BigQuery and returns results as an iterable of Apache Arrow RecordBatches.
+
+    Args:
+        project_id (Optional[str]): The Google Cloud project ID to bill for the query.
+            If not specified, the project is inferred from the environment.
+
+    Returns:
+        Iterable[pyarrow.RecordBatch]: An iterable of Apache Arrow RecordBatch objects.
+    """
+    # Initialize a BigQuery client.
+    client = bigquery.Client(project=project_id) if project_id else bigquery.Client()
+
+    query = """
+        SELECT name, number, state
+        FROM `bigquery-public-data.usa_names.usa_1910_current`
+        LIMIT 100000
+    """
+
+    # Run the query and wait for results returned directly in Arrow format
+    # compressed with LZ4_FRAME.
+    results = client.query_and_wait(
+        query,
+        query_results_format=enums.QueryResultsFormat.ARROW,
+        compression_codec=enums.QueryResultsCompressionCodec.LZ4_FRAME,
+    )
+
+    # Return results as an iterable of pyarrow.RecordBatch objects.
+    # Each batch contains a slice of the rows in Apache Arrow format.
+    batches = results.to_arrow_iterable()
+    return batches
+
+
+# [END bigquerystorage_query_and_wait_arrow]
@@ -0,0 +1,35 @@
+# 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.
+
+import pyarrow
+
+from . import query_and_wait_arrow
+
+
+def test_query_and_wait_arrow(project_id: str):
+    batches = query_and_wait_arrow.query_and_wait_arrow(project_id=project_id)
+
+    total_rows = 0
+    batch_count = 0
+    for batch in batches:
+        assert isinstance(batch, pyarrow.RecordBatch)
+        assert batch.schema.names == ["name", "number", "state"]
+        assert batch.schema.field("name").type == pyarrow.string()
+        assert batch.schema.field("number").type == pyarrow.int64()
+        assert batch.schema.field("state").type == pyarrow.string()
+        total_rows += batch.num_rows
+        batch_count += 1
+
+    assert total_rows == 100000
+    assert batch_count > 0
@@ -0,0 +1,77 @@
+# 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 bigquerystorage_read_rows_query_job]
+from typing import Iterable, Optional
+
+from google.cloud import bigquery
+from google.cloud import bigquery_storage_v1
+import pyarrow
+
+
+def read_rows_query_job(
+    project_id: Optional[str] = None,
+) -> Iterable[pyarrow.RecordBatch]:
+    """Queries BigQuery and yields batches directly via BigQueryReadClient using a job stream.
+
+    Args:
+        project_id (Optional[str]): The Google Cloud project ID to bill for the query.
+            If not specified, the project is inferred from the environment.
+
+    Yields:
+        pyarrow.RecordBatch: Apache Arrow RecordBatch objects streamed from BigQuery.
+    """
+    # Initialize BigQuery and BigQuery Storage clients.
+    client = bigquery.Client(project=project_id) if project_id else bigquery.Client()
+    read_client = bigquery_storage_v1.BigQueryReadClient()
+
+    query = """
+        SELECT name, number, state
+        FROM `bigquery-public-data.usa_names.usa_1910_current`
+        LIMIT 20000
+    """
+
+    # Start the query job.
+    job = client.query(query)
-    # Start the query job.
-    job = client.query(query)
+    # Start the query job and wait for it to complete.
+    job = client.query(query)
+    job.result()
-    # Start the query job.
-    job = client.query(query)
+    # Start the query job and wait for it to complete.
+    job = client.query(query)
+    job.result()
+
+    # Construct the job default stream name.
+    # Format: projects/{project_id}/locations/{location}/jobs/{job_id}/streams/_default
+    stream = f"projects/{job.project}/locations/{job.location}/jobs/{job.job_id}/streams/_default"
+
+    # Read rows directly from the stream using the Storage Read API.
+    schema: Optional[pyarrow.Schema] = None
+
+    for chunk in read_client.read_rows(name=stream, offset=0):
+        # Extract the schema from the first chunk that provides it.
+        if (
+            schema is None
+            and chunk.arrow_schema
+            and chunk.arrow_schema.serialized_schema
+        ):
+            schema = pyarrow.ipc.read_schema(
+                pyarrow.py_buffer(chunk.arrow_schema.serialized_schema)
+            )
+
+        # Deserialize and yield each record batch using the schema.
+        if (
+            chunk.arrow_record_batch
+            and chunk.arrow_record_batch.serialized_record_batch
+        ):
+            yield pyarrow.ipc.read_record_batch(
+                pyarrow.py_buffer(chunk.arrow_record_batch.serialized_record_batch),
+                schema,
+            )
+
+
+# [END bigquerystorage_read_rows_query_job]
@@ -0,0 +1,35 @@
+# 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.
+
+import pyarrow
+
+from . import read_rows_query_job
+
+
+def test_read_rows_query_job(project_id: str):
+    batches = read_rows_query_job.read_rows_query_job(project_id=project_id)
+
+    total_rows = 0
+    batch_count = 0
+    for batch in batches:
+        assert isinstance(batch, pyarrow.RecordBatch)
+        assert batch.schema.names == ["name", "number", "state"]
+        assert batch.schema.field("name").type == pyarrow.string()
+        assert batch.schema.field("number").type == pyarrow.int64()
+        assert batch.schema.field("state").type == pyarrow.string()
+        total_rows += batch.num_rows
+        batch_count += 1
+
+    assert total_rows == 20000
+    assert batch_count > 0
@@ -1,6 +1,9 @@
 google-cloud-bigquery-storage==2.38.0
 google-cloud-bigquery===3.30.0; python_version <= '3.8'
 google-cloud-bigquery==3.41.0; python_version >= '3.9'
+pyarrow===12.0.1; python_version == '3.7'
+pyarrow===17.0.0; python_version == '3.8'
+pyarrow==24.0.0; python_version >= '3.9'
 pytest===7.4.3; python_version == '3.7'
 pytest===8.3.5; python_version == '3.8'
 pytest==9.0.3; python_version >= '3.9'