fix: avoid unnecessary API call in QueryJob.result() when job is already finished

google/cloud/bigquery/_job_helpers.py

@@ -258,15 +258,16 @@ def _to_query_job(
  errors = query_response["errors"]
  query_job._properties["status"]["errors"] = errors
 
- # Transform job state so that QueryJob doesn't try to restart the query.
+ # Avoid an extra call to `getQueryResults` if the query has finished.
  job_complete = query_response.get("jobComplete")
  if job_complete:
- query_job._properties["status"]["state"] = "DONE"
  query_job._query_results = google.cloud.bigquery.query._QueryResults(
  query_response
  )
- else:
- query_job._properties["status"]["state"] = "PENDING"
+
+ # We want job.result() to refresh the job state, so the conversion is
+ # always "PENDING", even if the job is finished.
+ query_job._properties["status"]["state"] = "PENDING"
 
  return query_job
 

google/cloud/bigquery/job/query.py

@@ -17,11 +17,11 @@
 import concurrent.futures
 import copy
 import re
+import time
 import typing
 from typing import Any, Dict, Iterable, List, Optional, Union
 
 from google.api_core import exceptions
-from google.api_core.future import polling as polling_future
 from google.api_core import retry as retries
 import requests
 
@@ -1383,7 +1383,7 @@ def _begin(self, client=None, retry=DEFAULT_RETRY, timeout=None):
  def _reload_query_results(
  self, retry: "retries.Retry" = DEFAULT_RETRY, timeout: Optional[float] = None
  ):
- """Refresh the cached query results.
+ """Refresh the cached query results unless already cached and complete.
 
  Args:
  retry (Optional[google.api_core.retry.Retry]):
@@ -1392,6 +1392,8 @@ def _reload_query_results(
  The number of seconds to wait for the underlying HTTP transport
  before using ``retry``.
  """
+ # Optimization: avoid a call to jobs.getQueryResults if it's already
+ # been fetched, e.g. from jobs.query first page of results.
  if self._query_results and self._query_results.complete:
  return
 
@@ -1430,40 +1432,6 @@ def _reload_query_results(
  timeout=transport_timeout,
  )
 
- def _done_or_raise(self, retry=DEFAULT_RETRY, timeout=None):
- """Check if the query has finished running and raise if it's not.
-
- If the query has finished, also reload the job itself.
- """
- # If an explicit timeout is not given, fall back to the transport timeout
- # stored in _blocking_poll() in the process of polling for job completion.
- transport_timeout = timeout if timeout is not None else self._transport_timeout
-
- try:
- self._reload_query_results(retry=retry, timeout=transport_timeout)
- except exceptions.GoogleAPIError as exc:
- # Reloading also updates error details on self, thus no need for an
- # explicit self.set_exception() call if reloading succeeds.
- try:
- self.reload(retry=retry, timeout=transport_timeout)
- except exceptions.GoogleAPIError:
- # Use the query results reload exception, as it generally contains
- # much more useful error information.
- self.set_exception(exc)
- finally:
- return
-
- # Only reload the job once we know the query is complete.
- # This will ensure that fields such as the destination table are
- # correctly populated.
- if not self._query_results.complete:
- raise polling_future._OperationNotComplete()
- else:
- try:
- self.reload(retry=retry, timeout=transport_timeout)
- except exceptions.GoogleAPIError as exc:
- self.set_exception(exc)
-
  def result( # type: ignore # (incompatible with supertype)
  self,
  page_size: Optional[int] = None,
@@ -1528,6 +1496,10 @@ def result( # type: ignore # (incompatible with supertype)
  If Non-``None`` and non-default ``job_retry`` is
  provided and the job is not retryable.
  """
+ # Note: Since waiting for a query job to finish is more complex than
+ # refreshing the job state in a loop, we avoid calling the superclass
+ # in this method.
+
  if self.dry_run:
  return _EmptyRowIterator(
  project=self.project,
@@ -1548,46 +1520,124 @@ def result( # type: ignore # (incompatible with supertype)
  " provided to the query that created this job."
  )
 
- first = True
+ restart_query_job = False
+
+ def is_job_done():
+ nonlocal restart_query_job
 
-def do_get_result():
-nonlocal first
+ if restart_query_job:
+ restart_query_job = False
 
- if first:
- first = False
- else:
+ # The original job has failed. Create a new one.
+ #
  # Note that we won't get here if retry_do_query is
  # None, because we won't use a retry.
-
- # The orinal job is failed. Create a new one.
  job = retry_do_query()
 
- # If it's already failed, we might as well stop:
- if job.done() and job.exception() is not None:
- raise job.exception()
-
  # Become the new job:
  self.__dict__.clear()
  self.__dict__.update(job.__dict__)
 
- # This shouldn't be necessary, because once we have a good
- # job, it should stay good,and we shouldn't have to retry.
- # But let's be paranoid. :)
+ # It's possible the job fails again and we'll have to
+ # retry that too.
  self._retry_do_query = retry_do_query
  self._job_retry = job_retry
 
- super(QueryJob, self).result(retry=retry, timeout=timeout)
-
- # Since the job could already be "done" (e.g. got a finished job
- # via client.get_job), the superclass call to done() might not
- # set the self._query_results cache.
- if self._query_results is None or not self._query_results.complete:
- self._reload_query_results(retry=retry, timeout=timeout)
+ # Refresh the job status with jobs.get because some of the
+ # exceptions thrown by jobs.getQueryResults like timeout and
+ # rateLimitExceeded errors are ambiguous. We want to know if
+ # the query job failed and not just the call to
+ # jobs.getQueryResults.
+ if self.done(retry=retry, timeout=timeout):
+ # If it's already failed, we might as well stop.
+ job_failed_exception = self.exception()
+ if job_failed_exception is not None:
+ # Only try to restart the query job if the job failed for
+ # a retriable reason. For example, don't restart the query
+ # if the call to reload the job metadata within self.done()
+ # timed out.
+ #
+ # The `restart_query_job` must only be called after a
+ # successful call to the `jobs.get` REST API and we
+ # determine that the job has failed.
+ #
+ # The `jobs.get` REST API
+ # (https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs/get)
+ # is called via `self.done()` which calls
+ # `self.reload()`.
+ #
+ # To determine if the job failed, the `self.exception()`
+ # is set from `self.reload()` via
+ # `self._set_properties()`, which translates the
+ # `Job.status.errorResult` field
+ # (https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#JobStatus.FIELDS.error_result)
+ # into an exception that can be processed by the
+ # `job_retry` predicate.
+ restart_query_job = True
+ raise job_failed_exception
+ else:
+ # Make sure that the _query_results are cached so we
+ # can return a complete RowIterator.
+ #
+ # Note: As an optimization, _reload_query_results
+ # doesn't make any API calls if the query results are
+ # already cached and have jobComplete=True in the
+ # response from the REST API. This ensures we aren't
+ # making any extra API calls if the previous loop
+ # iteration fetched the finished job.
+ self._reload_query_results(retry=retry, timeout=timeout)
+ return True
+
+ # Call jobs.getQueryResults with max results set to 0 just to
+ # wait for the query to finish. Unlike most methods,
+ # jobs.getQueryResults hangs as long as it can to ensure we
+ # know when the query has finished as soon as possible.
+ self._reload_query_results(retry=retry, timeout=timeout)
+
+ # Even if the query is finished now according to
+ # jobs.getQueryResults, we'll want to reload the job status if
+ # it's not already DONE.
+ return False
 
  if retry_do_query is not None and job_retry is not None:
- do_get_result = job_retry(do_get_result)
-
- do_get_result()
+ is_job_done = job_retry(is_job_done)
+
+ # timeout can be a number of seconds, `None`, or a
+ # `google.api_core.future.polling.PollingFuture._DEFAULT_VALUE`
+ # sentinel object indicating a default timeout if we choose to add
+ # one some day. This value can come from our PollingFuture
+ # superclass and was introduced in
+ # https://github.com/googleapis/python-api-core/pull/462.
+ if isinstance(timeout, (float, int)):
+ remaining_timeout = timeout
+ else:
+ # Note: we may need to handle _DEFAULT_VALUE as a separate
+ # case someday, but even then the best we can do for queries
+ # is 72+ hours for hyperparameter tuning jobs:
+ # https://cloud.google.com/bigquery/quotas#query_jobs
+ #
+ # The timeout for a multi-statement query is 24+ hours. See:
+ # https://cloud.google.com/bigquery/quotas#multi_statement_query_limits
+ remaining_timeout = None
+
+ if remaining_timeout is None:
+ # Since is_job_done() calls jobs.getQueryResults, which is a
+ # long-running API, don't delay the next request at all.
+ while not is_job_done():
+ pass
+ else:
+ # Use a monotonic clock since we don't actually care about
+ # daylight savings or similar, just the elapsed time.
+ previous_time = time.monotonic()
+
+ while not is_job_done():
+ current_time = time.monotonic()
+ elapsed_time = current_time - previous_time
+ remaining_timeout = remaining_timeout - elapsed_time
+ previous_time = current_time
+
+ if remaining_timeout < 0:
+ raise concurrent.futures.TimeoutError()
 
  except exceptions.GoogleAPICallError as exc:
  exc.message = _EXCEPTION_FOOTER_TEMPLATE.format(

google/cloud/bigquery/retry.py

@@ -36,10 +36,25 @@
 
 _DEFAULT_RETRY_DEADLINE = 10.0 * 60.0 # 10 minutes
 
-# Allow for a few retries after the API request times out. This relevant for
-# rateLimitExceeded errors, which can be raised either by the Google load
-# balancer or the BigQuery job server.
-_DEFAULT_JOB_DEADLINE = 3.0 * _DEFAULT_RETRY_DEADLINE
+# Ambiguous errors (e.g. internalError, backendError, rateLimitExceeded) retry
+# until the full `_DEFAULT_RETRY_DEADLINE`. This is because the
+# `jobs.getQueryResults` REST API translates a job failure into an HTTP error.
+#
+# TODO(https://github.com/googleapis/python-bigquery/issues/1903): Investigate
+# if we can fail early for ambiguous errors in `QueryJob.result()`'s call to
+# the `jobs.getQueryResult` API.
+#
+# We need `_DEFAULT_JOB_DEADLINE` to be some multiple of
+# `_DEFAULT_RETRY_DEADLINE` to allow for a few retries after the retry
+# timeout is reached.
+#
+# Note: This multiple should actually be a multiple of
+# (2 * _DEFAULT_RETRY_DEADLINE). After an ambiguous exception, the first
+# call from `job_retry()` refreshes the job state without actually restarting
+# the query. The second `job_retry()` actually restarts the query. For a more
+# detailed explanation, see the comments where we set `restart_query_job = True`
+# in `QueryJob.result()`'s inner `is_job_done()` function.
+_DEFAULT_JOB_DEADLINE = 2.0 * (2.0 * _DEFAULT_RETRY_DEADLINE)
 
 
 def _should_retry(exc):
@@ -66,17 +81,44 @@ def _should_retry(exc):
 pass ``retry=bigquery.DEFAULT_RETRY.with_deadline(30)``.
 """
 
+# Note: Take care when updating DEFAULT_TIMEOUT to anything but None. We
+# briefly had a default timeout, but even setting it at more than twice the
+# theoretical server-side default timeout of 2 minutes was not enough for
+# complex queries. See:
+# https://github.com/googleapis/python-bigquery/issues/970#issuecomment-921934647
 DEFAULT_TIMEOUT = None
 """The default API timeout.
 
 This is the time to wait per request. To adjust the total wait time, set a
 deadline on the retry object.
 """
 
-job_retry_reasons = "rateLimitExceeded", "backendError", "jobRateLimitExceeded"
+job_retry_reasons = (
+ "rateLimitExceeded",
+ "backendError",
+ "internalError",
+ "jobRateLimitExceeded",
+)
 
 
 def _job_should_retry(exc):
+ # Sometimes we have ambiguous errors, such as 'backendError' which could
+ # be due to an API problem or a job problem. For these, make sure we retry
+ # our is_job_done() function.
+ #
+ # Note: This won't restart the job unless we know for sure it's because of
+ # the job status and set restart_query_job = True in that loop. This means
+ # that we might end up calling this predicate twice for the same job
+ # but from different paths: (1) from jobs.getQueryResults RetryError and
+ # (2) from translating the job error from the body of a jobs.get response.
+ #
+ # Note: If we start retrying job types other than queries where we don't
+ # call the problematic getQueryResults API to check the status, we need
+ # to provide a different predicate, as there shouldn't be ambiguous
+ # errors in those cases.
+ if isinstance(exc, exceptions.RetryError):
+ exc = exc.cause
+
  if not hasattr(exc, "errors") or len(exc.errors) == 0:
  return False