fix: retry is_job_done on ConnectionError (#1930)

google/cloud/bigquery/retry.py

@@ -119,6 +119,14 @@ def _job_should_retry(exc):
     if isinstance(exc, exceptions.RetryError):
         exc = exc.cause
 
+    # Per https://github.com/googleapis/python-bigquery/issues/1929, sometimes
+    # retriable errors make their way here. Because of the separate
+    # `restart_query_job` logic to make sure we aren't restarting non-failed
+    # jobs, it should be safe to continue and not totally fail our attempt at
+    # waiting for the query to complete.
+    if _should_retry(exc):
+        return True
+
     if not hasattr(exc, "errors") or len(exc.errors) == 0:
         return False
 

tests/unit/test_job_retry.py

@@ -21,6 +21,7 @@
 import google.api_core.exceptions
 import google.api_core.retry
 import freezegun
+import requests.exceptions
 
 from google.cloud.bigquery.client import Client
 from google.cloud.bigquery import _job_helpers
@@ -126,6 +127,122 @@ def api_request(method, path, query_params=None, data=None, **kw):
     assert job.job_id == orig_job_id
 
 
+def test_retry_connection_error_with_default_retries_and_successful_first_job(
+    monkeypatch, client
+):
+    """
+    Make sure ConnectionError can be retried at `is_job_done` level, even if
+    retries are exhaused by API-level retry.
+
+    Note: Because restart_query_job is set to True only in the case of a
+    confirmed job failure, this should be safe to do even when a job is not
+    idempotent.
+
+    Regression test for issue
+    https://github.com/googleapis/python-bigquery/issues/1929
+    """
+    job_counter = 0
+
+    def make_job_id(*args, **kwargs):
+        nonlocal job_counter
+        job_counter += 1
+        return f"{job_counter}"
+
+    monkeypatch.setattr(_job_helpers, "make_job_id", make_job_id)
+    conn = client._connection = make_connection()
+    project = client.project
+    job_reference_1 = {"projectId": project, "jobId": "1", "location": "test-loc"}
+    NUM_API_RETRIES = 2
+
+    with freezegun.freeze_time(
+        "2024-01-01 00:00:00",
+        # Note: because of exponential backoff and a bit of jitter,
+        # NUM_API_RETRIES will get less accurate the greater the value.
+        # We add 1 because we know there will be at least some additional
+        # calls to fetch the time / sleep before the retry deadline is hit.
+        auto_tick_seconds=(
+            google.cloud.bigquery.retry._DEFAULT_RETRY_DEADLINE / NUM_API_RETRIES
+        )
+        + 1,
+    ):
+        conn.api_request.side_effect = [
+            # jobs.insert
+            {"jobReference": job_reference_1, "status": {"state": "PENDING"}},
+            # jobs.get
+            {"jobReference": job_reference_1, "status": {"state": "RUNNING"}},
+            # jobs.getQueryResults x2
+            requests.exceptions.ConnectionError(),
+            requests.exceptions.ConnectionError(),
+            # jobs.get
+            # Job actually succeeeded, so we shouldn't be restarting the job,
+            # even though we are retrying at the `is_job_done` level.
+            {"jobReference": job_reference_1, "status": {"state": "DONE"}},
+            # jobs.getQueryResults
+            {"jobReference": job_reference_1, "jobComplete": True},
+        ]
+
+        job = client.query("select 1")
+        rows_iter = job.result()
+
+    assert job.done()  # Shouldn't make any additional API calls.
+    assert rows_iter is not None
+
+    # Should only have created one job, even though we did call job_retry.
+    assert job_counter == 1
+
+    # Double-check that we made the API calls we expected to make.
+    conn.api_request.assert_has_calls(
+        [
+            # jobs.insert
+            mock.call(
+                method="POST",
+                path="/projects/PROJECT/jobs",
+                data={
+                    "jobReference": {"jobId": "1", "projectId": "PROJECT"},
+                    "configuration": {
+                        "query": {"useLegacySql": False, "query": "select 1"}
+                    },
+                },
+                timeout=None,
+            ),
+            # jobs.get
+            mock.call(
+                method="GET",
+                path="/projects/PROJECT/jobs/1",
+                query_params={"location": "test-loc"},
+                timeout=None,
+            ),
+            # jobs.getQueryResults x2
+            mock.call(
+                method="GET",
+                path="/projects/PROJECT/queries/1",
+                query_params={"maxResults": 0, "location": "test-loc"},
+                timeout=None,
+            ),
+            mock.call(
+                method="GET",
+                path="/projects/PROJECT/queries/1",
+                query_params={"maxResults": 0, "location": "test-loc"},
+                timeout=None,
+            ),
+            # jobs.get -- is_job_done checking again
+            mock.call(
+                method="GET",
+                path="/projects/PROJECT/jobs/1",
+                query_params={"location": "test-loc"},
+                timeout=None,
+            ),
+            # jobs.getQueryResults
+            mock.call(
+                method="GET",
+                path="/projects/PROJECT/queries/1",
+                query_params={"maxResults": 0, "location": "test-loc"},
+                timeout=120,
+            ),
+        ],
+    )
+
+
 def test_query_retry_with_default_retry_and_ambiguous_errors_only_retries_with_failed_job(
     client, monkeypatch
 ):