[BEAM-34076] Added TTL caching for BigQuery table definitions

Author: AbgarSim

sdks/python/apache_beam/io/gcp/bigquery_tools.py

@@ -37,6 +37,7 @@
 import sys
 import time
 import uuid
+import threading
 from json.decoder import JSONDecodeError
 from typing import Optional
 from typing import Sequence
@@ -66,6 +67,8 @@
 from apache_beam.typehints.typehints import Any
 from apache_beam.utils import retry
 from apache_beam.utils.histogram import LinearBucket
+from cachetools import TTLCache, cachedmethod, Cache
+from cachetools.keys import hashkey
 
 # Protect against environments where bigquery library is not available.
 try:
@@ -139,6 +142,12 @@ class ExportCompression(object):
   SNAPPY = 'SNAPPY'
   NONE = 'NONE'
 
+class _NonNoneTTLCache(TTLCache):
+  """TTLCache that does not store None values."""
+  def __setitem__(self, key, value, cache_setitem=Cache.__setitem__):
+    if value is not None:
+      super().__setitem__(key=key, value=value)
+
 
 def default_encoder(obj):
   if isinstance(obj, decimal.Decimal):
@@ -359,6 +368,9 @@ class BigQueryWrapper(object):
 
   HISTOGRAM_METRIC_LOGGER = MetricLogger()
 
+  _TABLE_CACHE = _NonNoneTTLCache(maxsize=1024, ttl=300)
+  _TABLE_CACHE_LOCK = threading.RLock()
+
   def __init__(self, client=None, temp_dataset_id=None, temp_table_ref=None):
     self.client = client or BigQueryWrapper._bigquery_client(PipelineOptions())
     self.gcp_bq_client = client or gcp_bigquery.Client(
@@ -788,27 +800,32 @@ def _insert_all_rows(
           int(time.time() * 1000) - started_millis)
     return not errors, errors
 
+  @cachedmethod(
+    cache=lambda self: self._TABLE_CACHE,
+    lock=lambda self: self._TABLE_CACHE_LOCK,
+    key=lambda self, project_id, dataset_id, table_id: hashkey(
+      project_id, dataset_id, table_id),
+  )
   @retry.with_exponential_backoff(
-      num_retries=MAX_RETRIES,
-      retry_filter=retry.retry_on_server_errors_timeout_or_quota_issues_filter)
+    num_retries=MAX_RETRIES,
+    retry_filter=retry.retry_on_server_errors_timeout_or_quota_issues_filter)
   def get_table(self, project_id, dataset_id, table_id):
-    """Lookup a table's metadata object.
-
-    Args:
-      client: bigquery.BigqueryV2 instance
-      project_id: table lookup parameter
-      dataset_id: table lookup parameter
-      table_id: table lookup parameter
-
-    Returns:
-      bigquery.Table instance
-    Raises:
-      HttpError: if lookup failed.
-    """
+    """Lookup a table's metadata object. (TTL cached at class level).
+
+        Args:
+          client: bigquery.BigqueryV2 instance
+          project_id: table lookup parameter
+          dataset_id: table lookup parameter
+          table_id: table lookup parameter
+
+        Returns:
+          bigquery.Table instance
+        Raises:
+          HttpError: if lookup failed.
+        """
     request = bigquery.BigqueryTablesGetRequest(
-        projectId=project_id, datasetId=dataset_id, tableId=table_id)
-    response = self.client.tables.Get(request)
-    return response
+      projectId=project_id, datasetId=dataset_id, tableId=table_id)
+    return self.client.tables.Get(request)
 
   def _create_table(
       self,

sdks/python/apache_beam/io/gcp/bigquery_tools_test.py

@@ -292,6 +292,80 @@ def test_temporary_dataset_is_unique(self, patched_time_sleep):
       wrapper.create_temporary_dataset('project-id', 'location')
     self.assertTrue(client.datasets.Get.called)
 
+  def test_get_table_invokes_tables_get_and_caches_result(self):
+
+    from apache_beam.io.gcp.bigquery_tools import BigQueryWrapper
+
+    client = mock.Mock()
+    client.tables = mock.Mock()
+
+    returned_table = mock.Mock(name="BigQueryTable")
+    client.tables.Get = mock.Mock(return_value=returned_table)
+
+    wrapper = BigQueryWrapper(client=client)
+
+    project_id = "my-project"
+    dataset_id = "my_dataset"
+    table_id = "my_table"
+
+    table1 = wrapper.get_table(project_id, dataset_id, table_id)
+
+    assert table1 is returned_table
+    assert client.tables.Get.call_count == 1
+
+    (request,), _ = client.tables.Get.call_args
+    assert isinstance(request, bigquery.BigqueryTablesGetRequest)
+    assert request.projectId == project_id
+    assert request.datasetId == dataset_id
+    assert request.tableId == table_id
+
+    table2 = wrapper.get_table(project_id, dataset_id, table_id)
+
+    assert table2 is returned_table
+    assert client.tables.Get.call_count == 1  # still 1 => cached
+
+  def test_get_table_shared_cache_across_wrapper_instances(self):
+    from apache_beam.io.gcp.bigquery_tools import BigQueryWrapper
+
+    # ensure isolation -> clear the shared cache before the test
+    BigQueryWrapper._TABLE_CACHE.clear()
+
+    client = mock.Mock()
+    client.tables = mock.Mock()
+
+    returned_table = mock.Mock(name="BigQueryTable")
+    client.tables.Get = mock.Mock(return_value=returned_table)
+
+    project_id = "my-project"
+    dataset_id = "my_dataset"
+    table_id = "my_table"
+
+    w1 = BigQueryWrapper(client=client)
+    w2 = BigQueryWrapper(client=client)
+    w3 = BigQueryWrapper(client=client)
+
+    # first call -> populate cache
+    t1 = w1.get_table(project_id, dataset_id, table_id)
+    assert t1 is returned_table
+    assert client.tables.Get.call_count == 1
+
+    # verify request shape (from first call)
+    (request,), _ = client.tables.Get.call_args
+    assert isinstance(request, bigquery.BigqueryTablesGetRequest)
+    assert request.projectId == project_id
+    assert request.datasetId == dataset_id
+    assert request.tableId == table_id
+
+    # calls from DIFFERENT wrapper instances -> hit the SAME cache entry
+    t2 = w2.get_table(project_id, dataset_id, table_id)
+    t3 = w3.get_table(project_id, dataset_id, table_id)
+
+    assert t2 is returned_table
+    assert t3 is returned_table
+
+    # still 1 -> record cached across instances
+    assert client.tables.Get.call_count == 1
+
   def test_get_or_create_dataset_created(self):
     client = mock.Mock()
     client.datasets.Get.side_effect = HttpError(