pabloem commented on a change in pull request #16841:
URL: https://github.com/apache/beam/pull/16841#discussion_r839098985
##########
File path:
sdks/python/apache_beam/runners/portability/fn_api_runner/fn_runner.py
##########
@@ -363,68 +364,164 @@ def run_stages(self,
self.NUM_FUSED_STAGES_COUNTER,
urn='internal:' + self.NUM_FUSED_STAGES_COUNTER)).update(
len(stages))
- monitoring_infos_by_stage = {}
+ monitoring_infos_by_stage: MutableMapping[
+ str, Iterable['metrics_pb2.MonitoringInfo']] = {}
runner_execution_context = execution.FnApiRunnerExecutionContext(
stages,
worker_handler_manager,
stage_context.components,
stage_context.safe_coders,
- stage_context.data_channel_coders)
+ stage_context.data_channel_coders,
+ self._num_workers)
try:
with self.maybe_profile():
- for stage in stages:
- bundle_context_manager = execution.BundleContextManager(
- runner_execution_context, stage, self._num_workers)
-
- assert (
- runner_execution_context.watermark_manager.get_stage_node(
- bundle_context_manager.stage.name
- ).input_watermark() == timestamp.MAX_TIMESTAMP), (
- 'wrong watermark for %s. Expected %s, but got %s.' % (
- runner_execution_context.watermark_manager.get_stage_node(
- bundle_context_manager.stage.name),
- timestamp.MAX_TIMESTAMP,
- runner_execution_context.watermark_manager.get_stage_node(
- bundle_context_manager.stage.name
- ).input_watermark()
- )
- )
-
- stage_results = self._run_stage(
- runner_execution_context, bundle_context_manager)
-
- assert (
- runner_execution_context.watermark_manager.get_stage_node(
- bundle_context_manager.stage.name
- ).input_watermark() == timestamp.MAX_TIMESTAMP), (
- 'wrong input watermark for %s. Expected %s, but got %s.' % (
- runner_execution_context.watermark_manager.get_stage_node(
- bundle_context_manager.stage.name),
- timestamp.MAX_TIMESTAMP,
- runner_execution_context.watermark_manager.get_stage_node(
- bundle_context_manager.stage.name
- ).output_watermark())
- )
-
- monitoring_infos_by_stage[stage.name] = (
- list(stage_results.process_bundle.monitoring_infos))
-
- monitoring_infos_by_stage[''] = list(
- pipeline_metrics.to_runner_api_monitoring_infos('').values())
+ # Initialize Runner context:
+ # - Pipeline dictionaries, initial inputs and pipeline triggers
+ # - Replace Data API endpoints in protobufs.
+ runner_execution_context.setup()
+
+ bundle_counter = 0
+ # Start executing all ready bundles.
+ while len(runner_execution_context.queues.ready_inputs) > 0:
+ _LOGGER.debug(
+ "Remaining ready bundles: %s\n"
+ "\tWatermark pending bunbles: %s\n"
+ "\tTime pending bunbles: %s",
+ len(runner_execution_context.queues.ready_inputs),
+ len(runner_execution_context.queues.watermark_pending_inputs),
+ len(runner_execution_context.queues.time_pending_inputs))
+ consuming_stage_name, bundle_input = (
+ runner_execution_context.queues.ready_inputs.deque())
+ stage = runner_execution_context.stages[consuming_stage_name]
+ bundle_context_manager = runner_execution_context.bundle_manager_for(
+ stage)
+ _BUNDLE_LOGGER.debug(
+ 'Running bundle for stage %s\n\tExpected outputs: %s timers: %s',
+ bundle_context_manager.stage.name,
+ bundle_context_manager.stage_data_outputs,
+ bundle_context_manager.stage_timer_outputs)
+ assert consuming_stage_name == bundle_context_manager.stage.name
+
+ bundle_counter += 1
+ bundle_results = self._execute_bundle(
+ runner_execution_context, bundle_context_manager, bundle_input)
+
+ if consuming_stage_name in monitoring_infos_by_stage:
+ monitoring_infos_by_stage[
+ consuming_stage_name] = consolidate_monitoring_infos(
+ itertools.chain(
+ bundle_results.process_bundle.monitoring_infos,
+ monitoring_infos_by_stage[consuming_stage_name]))
+ else:
+ assert isinstance(
+ bundle_results.process_bundle.monitoring_infos, Iterable)
+ monitoring_infos_by_stage[consuming_stage_name] = \
+ bundle_results.process_bundle.monitoring_infos
+
+ if '' not in monitoring_infos_by_stage:
Review comment:
done
##########
File path:
sdks/python/apache_beam/runners/portability/fn_api_runner/execution.py
##########
@@ -187,6 +222,9 @@ def __init__(self,
self._windowing = windowing
self._grouped_output = None # type: Optional[List[List[bytes]]]
+ def copy(self) -> 'GroupingBuffer':
+ return self
Review comment:
added. thanks!
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: [email protected]
For queries about this service, please contact Infrastructure at:
[email protected]
